Success factors of breakthrough technology push projects in ICT context
University of Oulu Graduate School University of Oulu, Faculty of Information Technology and Electrical Engineering, Department of Information Processing Science Licentiate thesis Jari Sarja 12.9.2014
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Abstract The main task for most development-intensive organisations is to create, develop and commercialize new products and services. The technology push (TP) concept is considered an important competitive advantage for companies trying to create breakthrough products. Because development processes are risky and failure rates are high, especially in the case of technology pushed projects, unambiguous success factors are valuable knowledge for the management of development-intensive firms. The prime objective of this study is to present a compact set of the success factors of TP projects in an information and communication technology (ICT) context. Because the literature on new product development and innovation has presented many success factors for developed products but has done so in a way that presents the factors as having a nebulous nature, the specification of TP success factors is also presented. After an extensive review and screening of the technology push success factor related literature, a total of 13 success factors were rationalized and transcribed according the previous literature. As a result, three separate keynotes were recognized, and the survey instrument framework was proposed. According to current knowledge, TP success factors are industry independent. The practical relevance of this study is to help firm management to recognize the real actions needed to reduce product development risks and also to help scholars to focus on key issues when studying the key factors of breakthrough development cases. Key words: New product development, technology push, radical innovation, ICT, content analysis, success factor.
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Acknowledgements I present my warmest thanks to my supervisor Professor Samuli Saukkonen for the great guidance I have received during my postgraduate studies and the first phase of dissertation work. I appreciate the way of discussion, the feedback given and mutual respect shown. I want to thank the Ahti Pekkala Foundation, the Riitta and Jorma J. Takanen foundation, the University of Oulu Scholarship foundation and the University of Oulu Graduate School (travel grant) for financial support for this project. I am glad for the understanding of my research topic’s importance not only for the new product development industry in general but also for regional innovation schemes. Independent financial support is extremely important for individual research projects outside research groups and has helped me to stay on schedule. I acknowledge the staff of the University of Oulu Raahe Unit and the staff of PBOL cooperative laboratory for the warm and supporting working environment and the great facility.
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Abbreviations GPT
General Purpose Technology
HCI
Human-computer Interaction
ICT
Information and Communications Technologies
MA
Meta Analyses
MIS
Management Information Systems [Quarterly]
MP
Market Pull
NPD
New Product Development
R&D
Research and Development
TAM
Technology Acceptance Model
TP
Technology Push
UTAUT
Unified Theory of Acceptance and Use Technology
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List of original publications I
Sarja, J. (2014). Key factors of successful technology push projects in ICT context: A review of the literature. Manuscript. Approved for the International Journal of Information Technology and Management.
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Sarja, J. (2014). The explanatory definitions of the technology push success factors. Manuscript.
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Sarja, J. (2012). A review of the Getting Real software development approach. International Journal of Agile and Extreme Software Development, 1 (1), 78-94.
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Content Abstract ........................................................................................................................ 2 Acknowledgements ....................................................................................................... 3 Abbreviations ............................................................................................................... 4 List of original publications .......................................................................................... 5 Content ......................................................................................................................... 6 1. Introduction .............................................................................................................. 7 1.1 Research process ............................................................................................ 11 1.2 Research design ............................................................................................. 12 2. Theoretical foundation: Innovation drivers, innovation types and success factors .................................................................................................................... 14 2.1 Technology push and market pull innovation drivers ...................................... 14 2.2 Radical and incremental innovations .............................................................. 16 2.3 NPD success factor research ........................................................................... 17 2.3.1 NPD key factors by landmarks ............................................................ 17 3. The success factors of technology push projects ..................................................... 20 3.1 TP success factors by landmarks .................................................................... 22 3.2 TP research in ICT context ............................................................................. 24 4. Specification of the TP success factors ................................................................... 27 4.1 Market related success factors ........................................................................ 27 4.2 Product related success factors ....................................................................... 30 4.3 Management related success factors ............................................................... 31 4.4 Organization related success factors ............................................................... 32 4.5 The survey instrument framework .................................................................. 33 4.6 A short case: Basecamp .................................................................................. 33 5. Discussion .............................................................................................................. 37 6. Conclusions ............................................................................................................ 40 References .................................................................................................................. 41 Appendix 1 ................................................................................................................. 47 Original Publications .................................................................................................. 52
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1.
Introduction
Developing new and successful products to market is necessary for most companies (e.g., Balachandra & Friar, 1997; Cooper, 1994; Ernst, 2002). Because development processes are very risky and failure rates are high, it is obvious that the management of development-intensive firms must be interested in those factors that lead to successful innovations. In general, [critical] success factors are defined to mean limited number of elements or areas where “things must go right” for the business to flourish. These areas of activities must be constantly and carefully monitored by the management, and they are necessary for an organization or project to achieve the end points that they try to reach (Rockart, 1979). Previous literature on New Product Development (NPD) has presented conflicting findings regarding two key concepts: technology push (TP) and market pull (MP) (e.g., Samli & Weber, 2000; Herstatt & Lettl, 2004). The TP school maintains that innovation is driven by science, whereas the MP school argues that the users’ needs are the key drivers of innovation (Chau & Tam, 2000). Most literature stresses that emphasis should be on MP (e.g. by Myers & Marquis, 1969; Langrish, 1972; Rothwell et al., 1974; Utterback, 1974). However, numerous successful TP products have been launched. Probably the most reputed TP innovator – or at least one of them – is the Apple company. “. . . But it was hard to explain what an iPad was . . . The first set of ads showed we didn’t know what we were doing.” “Some people say, ‘Give the customers what they want.’ but that’s not my approach. Our job is to figure out what they’re going to want before they do. I think Henry Ford once said, ‘If I’d asked customers what they wanted, they would have told me, ‘A faster horse!’’ People don’t know what they want until you show it to them. That’s why I never rely on market research. Our task is to read things that are not yet on the page.” Steve Jobs by Walter Isaacson (2011 pp. 529, 598) There are many similar kinds of examples. “We don't even know what it is yet. We don't know what it is. We don't know what it can be, we don't know what it will be, we know that it is cool.” Mark Zuckerberg’s character in the movie “The Social Network”.
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“As a software development company, you have to act as a filter. Not everything everyone suggests is the right answer. We consider all requests but the customer is not always right.” Jason Fried & David Heinemeier Hansson, Basecamp. The discussions regarding whether TP or MP is more important are futile. There are plenty of success stories and even more failures related to both driving forces (e.g., Balachandra & Friar, 1997). The current literature does not judge either concept. Instead, the concepts are linked strongly to particular innovation types: TP to radical and MP to incremental innovations (e.g., Samli & Weber, 2000; Bishop & Magleby, 2004; Herstatt & Lettl, 2004; Brem & Voigt, 2009). Radical innovations, also called as breakthroughs, are the innovations which change people’s life permanently (Samli & Weber, 2000). There have been many studies clarifying the success factors of NPD. Many of the key studies have not attempted to distinguish between radical and incremental innovation. By not distinguishing these two innovation types, the success factors of TP products are not explicitly known (Samli & Weber, 2000). For instance, the meta-analysis by Ernst (2002) encompassing dozens of widely cited NPD studies, including Cooper and Kleinschmidt’s almost 30 papers, handles different types of innovation as one broad category. General NPD research, which does not take innovation type into account, is mostly too universal for studies of the success factors of TP. Because of the quantity of NPD and innovation management research that exists, representing different levels, different scopes and some with conflicting findings, we need to define a manageable set of success factors for further research. As Siggelkow (2007) states: “Theories and models are always simplifications. If they were as complex as reality, they would not be useful”. Cusumano (2010) follows the same philosophy to some degree when speaking about his six principles of creating competitive advantage: “In reflecting on what I have learned, I concluded that a handful of principles – I have chosen six – appear to have been essential to the effective management . . . I have focused on principles supported by considerable theoretical and empirical research undertaken by a variety of scholars . . .”. The prime objective of this study is to present a compact set of the success factors of TP projects in an information and communication technology (ICT) context. The success factors of ICT companies’ TP projects are led by studying the research on success factors in three levels. There are only a few research works on success factors specific to TP. Samli and Weber (2000) have generated and tested eight hypotheses of factors leading to breakthroughs. Bishop and Magleby (2004) have categorised eight themes of TP development success factors in their literature review.
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It seems that there are only a small number of studies on TP success factors in an ICT context1. Isaacs and Tang (1996) and Spivey et al. (1997) had the desired context in their technology transfer studies but those are too case oriented for deriving universal success factors. The TP concept is considered an important competitive advantage for R&D-intensive companies trying to create breakthrough products (Samli & Weber, 2000; Herstatt & Lettl, 2004). The research question in this study is: What are the success factors of successful technology push projects in ICT context? This has been done by reviewing researches on success factors in three levels: NPD, TP and TP in an ICT context. The weight is in TP success factor research because we concluded that the success factors of TP products are industry independent. The first level is general NPD research. By the epithet general, we mean NPD studies without any limitations of innovation drivers, innovation types, or industry. There are countless works in the literature about success factors in this level and it has been a significant research target during the past four decades (e.g., Balachandra & Friar, 1997; Ernst, 2002). The second level is the success factor research limited to TP products. When we discuss technology push, or the TP concept, we are not limiting it to any specific industry. The quantity of the literature in this level is more manageable (e.g., Bishop & Magleby, 2004). It is notable that the focus of NPD research has changed during the decades and it is clear that the MP models have had more attention from researchers and practitioners. However, MP projects are not within the scope of this study and therefore they are ignored. The third level is the literature on success factor research for TP projects limited to an ICT context. Even though the ICT industry is defined as one of the General Purpose Technology (GPT) industries (e.g., David and Wright, 1999), there are only a few ICTfocused success factor research works. For example, only two out of ten TP studies in meta-analysis by Bishop and Magleby (2004) are solely in an ICT context. The extent of the NPD success factor research is presented in Table 1. MP research is not within scope of this study and it is marked with a grey background.
1 Definition of ICT context ICT (information and communications technology (or technologies)) is an umbrella term that covers all communication devices and applications, including computers and network hardware and software, mobile phones, various services and applications associated with them (e.g., videoconferencing) but also more mature applications, such as radio and television (Asabere, 2012). We have used a narrower definition of ICT in this study by limiting it to computers, mobile phones and network application industries, including both hardware devices and software systems.
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Table 1 Level 1. NPD
Extent Countless
(2. MP products)
Multitude
2. TP products
Several
3. TP products in ICT context
Few
Model expressions ”The literature discussing success in product innovation is vast” (Balachandra & Friar, 1997). ”NPD research has retained a high level of popularity over the last 30 years" (Ernst, 2002). "Because of the numerous works available on this topic, a fact expressed in the many publications of review articles and meta-analyses" (Ernst, 2002). ”Much of these new product research efforts have made no attempt to distinguish between simple product line extensions and breakthroughs” (Samli & Weber, 2000). "Both MP and TP models have formally existed since the 1960s though MP models have clearly had greater attention from researchers and practitioners" (Bishop & Magleby, 2004). "A large and rapidly growing literature on new product development [answers these questions] for the more incremental forms of innovation. But discontinuous innovation is very different in character,…" (Lynn et al., 1996). ”Several researchers and practitioners have identified factors that are associated or correlated with TP product development resulting in successful products” (Bishop & Magleby, 2004). Only two out of ten TP studies analysed by Bishop & Magleby (2004) are solely in an ICT context (The author’s design).
Table 1. Extent of NPD success factor research in different levels
The research question, (what are the success factors of successful technology push projects in ICT context) is answered by a journal article 1 (approved manuscript in the thesis writing moment). The content of the success factors is clarified in article 2 (manuscript in the thesis writing moment). Partial validation of the success factors is presented in article 3. Figure 1 illustrates the framing of this work and also the relationships of the original publications. The contributions of these publications are combined in this thesis summary.
Figure 1. The framing and original publications
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The prime objective of this study is to present a compact set of the success factors of TP projects in an ICT context. The thesis proceeds as follows. The following subsection provides the content analysis research processes. Then we have introduced the TP and MP concepts, innovation types and their connections with each other. The following sections deal with the main themes of the thesis: How we derived the compact set of TP success factors, and the explanatory definitions of these descriptive vague topics. A short case study illustrating the empirical application of some success factors will also be presented. We conclude by discussing the concepts of the TP success factor set.
1.1 Research process This work has various goals, but the general aim is to find out what the success factors are of successful technology push projects in the ICT context. The research method in this work is qualitative content analysis. Content analysis is a widely used method in literature review type research papers and meta-analyses, but it is very seldom introduced in research papers. For example, most NPD related papers used as empirical sources in this work based on previous literature, regardless of the level of the journal, do not introduce the review method in a straight way. Content analysis is used in many works in nursing science, and it has a long history in that discipline (Elo & Kyngäs, 2007). Content analysis is a method of analysing written, verbal or visual communication messages (Cole, 1988). It is also known as a document analysis method (Elo & Kyngäs, 2007). It can be said that qualitative content analysis is a basic form of qualitative research, and that data will be categorised accordingly and possibly reprocessed with different methods (Ronkainen et al., 2011). Practically, it is a systematic and objective way of describing and quantifying a phenomenon (e.g., Sandelowski, 1995). It is possible to distil the findings, usually words and phrases, into fewer content related categories during the analysing process. The aim of the method is to describe the phenomenon in a condensed and broad way. The purpose of the categorised concepts is to build up a model, conceptual system, map or category. There are some derivative methods in other disciplines such as nursing or medical science, for example systematic review (Kitchenham, 2004) for software engineering research. As Kitchenham (2004) states, software engineering research methods are not as rigorous as those used by medical researchers. In general, systematic review is a method for identifying, evaluating and interpreting all available research that is relevant to a particular research question, topic area or studied phenomenon. There are three main reasons for applying systematic review: to summarise the existing evidence of a treatment or technology, to identify gaps in current research in order to propose areas for further research and to provide a framework or background for new research activities (Kitchenham, 2004) The premise of our study is identical to the systematic review method. In this study, we are applying somewhat the review method introduced by Kitchenham (2004) and the data categorization method of Elo and Kyngäs (2007). At first, we searched all available research relevant to the phenomenon. This was done by utilizing prominent databases licensed for use in the University of Oulu, including Scopus, ACM Digital Library and IEEE Xplore. The headwords in data searching were
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similar to the key words of this thesis. Also, numerous synonyms and word and phrase combinations were used. Then, the results, or found success factors, were introduced in three levels: success factors of NPD in general, success factors of TP products and success factors of TP products in the ICT context (even though we found later that TP success factors are industry independent according the current view). For getting highly filtered data, we preferred review type articles, including meta-analyses. After analysing dozens of papers, we chose those, which best met our research questions as landmarks. In NPD level, they were Balachandra and Friar (1997) and Ernst (2002). Both papers are meta-analyses, encompassing altogether nearly 100 research studies. As discussed before (see table 1), the research studies limited to TP products are few, and it was hard to take into account the level or age of the papers. Finally, we chose Samli and Weber (2000) and Bishop and Magleby (2004) as landmarks. Together, these TP studies summarized 10 studies and 29 breakthrough cases. The found success factors were collected from the landmark papers. Secondly, in order to obtain a clearer understanding of the success factors, we classified them into categories. We started categorising with the same themes as Balachandra and Friar (1997), namely market, technology, environment and organisation [related to]. Also, the classification method developed during the process; when the success factors were filtered to be more TP related, we needed to revise the categorisation in order to derive factor sets that were more consistent. The natural common themes for the revised categories we found were market, product, management and organisation [related to]. After concluding that the found success factors were not very exact and were rather descriptive vague topics with a nature that was too wide or had too many different meanings, we restarted the content analysis review again for rationalising and transcribing them. This was done by reviewing all relevant definitions and descriptions at factor level in a systematic way as discussed previously. As a result of the transcription, the specifications of TP success factors are presented. Finally, the survey instrument framework is presented. One sub goal of this work is to give a framework for the future research of TP cases, and an example type of an interview questionnaire based on the framework is proposed (Appendix 1).
1.2 Research design For ensuring the trustworthiness, we designed our work based on the four design tests introduced by Yin (2009, pp. 40–41). The author explains that these research design tactics (construct validity, internal validity, external validity and reliability) are commonly used to establish the quality of any empirical social research study. He explores them specifically from the perspective of case study methodology. Because our work is, by nature, literature study without noticeable empiricism, we have used a lighter version of the model. Construct validity is tested by using multiple sources of evidence. The data related to the research question is collected from numerous sources, and many of them are metaanalyses. In practise, this assures that the findings are concluded from hundreds of peerreviewed studies, and we can consider that the validity of the results is adequate.
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The problem of internal validity testing is that each researcher may interpret the data from his or her subjective perspective, and co-researchers can conclude an alternative interpretation (Sandelowski, 1995). Content validation needs to use a panel of experts to support an outcome (Elo & Kyngäs, 2007). Graneheim and Lundman (2004) encourage dialogue among co-researchers to agree on how data are labelled. We have defended our content by submitting the essential parts of the work to peer-reviewed requisite level journals. Because the nature of the work is “research of the research” (Salminen, 2011), the data is collected from previously published research studies. Therefore, the evaluation of external validity of this work is not very applicable, and the results are arguably generalized. The reliability of the work is discussed in terms of repeatability. Right from the beginning, our ambition was to clarify why some TP cases in the ICT industry, for example certain Apple or Basecamp products, have been successful. From this starting point, we generated only one but explicit research question. We see that, following the research process discussed previously and limiting the data collection accordingly from a general NPD level to a TP level, the research is repeatable and the research question would be answered similarly. We also assume that the same conclusion regarding the nature of the findings would be discussed.
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2.
Theoretical foundation: Innovation drivers, innovation types and success factors
The core task for most NPD-intensive organisations is to generate and commercialise new products and services; however, this is a complex and difficult task. Most new products fail, that is, they do not meet their commercial targets (e.g., Balachandra & Friar, 1997). A turbulent environment with ever-shortening development-cycle times and a rapidly changing and increasingly competitive market cause these challenges (Herstatt & Lettl, 2004). Because NPD is the backbone of many industries, it is obvious that it is of significant interest to multidisciplinary research. The quantity of NPD research during recent decades has been tremendous (e.g., Balachandra & Friar, 1997; Ernst, 2002). The objective of these research works has been, almost without exception, to identify the success factors of new products. The impulse for the development of a new product comes either from customer needs (MP), or internal or external research (TP).
2.1 Technology push and market pull innovation drivers TP (Schumpeter, 1939) and MP (Schmookler, 1962) are the basic concepts for the driving forces behind innovations. There exist few synonyms in the literature for the concepts of technology push (e.g., science push, discovery push), and market pull (e.g., demand pull, need pull). The concept of MP suggests that market demand is the primary driver of innovation. In the concept of TP, the driving force for innovation is internal or external research and the goal is to develop new technology for commercial use. Two schools of thought have debated which the most advisable approach is. Traditionally, empirical research has been concerned with the question how these approaches influence the success of innovation (Herstatt & Lettl, 2004). Chidamber and Kon (1994) suggest that confrontation between the two approaches is due to different research objectives, definitions and models. Differences in problem statement and research constructs may also cause incongruity in research findings. Chidamber and Kon (1994) found that innovation research could be done at different levels; firm project, single innovation, industry, or even at national levels. A result found at a certain level is often inconsistent with results discovered at other levels. The four significant key studies of each school, most often cited in the literature, are (Chidamber & Kon, 1994): Technology push: Mowery & Rosenberg (1979) Freeman (1982) Casey (1976) Pavitt (1971)
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Market Pull: Project SAPPHO (1974) by Rothwell et al. Meyers & Marquis (1969) Langrish (1972) Utterback (1974) A comparison between the characteristics of innovation drivers is presented in Table 2. Table 2 Attribute Technology uncertainty R&D expense R&D duration Time to market Innovation process Market-related uncertainty R&D customer integration Customer experience Customer education Market research type Need for changing customer behaviour
Technology push High High Long Unknown “Probe and learn” type High Difficult None present Usually necessary Qualitative “exploratory” research Extensive
Market pull Low Low Short Known “Stage-gate” type Low Easy Present Not necessary Quantitative conventional market research Minimal
Table 2. Innovation driver comparison (Herstatt & Lettl, 2004; Gerpott, 2005)
Herstatt and Lettl (2004) explain that the degree, or newness, of innovation influences the development investments of both time and money, to the certainty level of technology and market. Lynn et al. (1996) state that the certainty level of technology and market causes different development processes: experimental probe-and-learn-type in TP cases and confirming stage-gate-type in MP cases. The knowledge of the needs of the market is different for both drivers. The TP strategy represents future markets that are difficult to predict and the MP strategy represents the current market situation. Therefore, the market research methods employed are also different: exploratory qualitative for TP and conventional quantitative (e.g., surveys) for MP (e.g., Herstatt & Lettl, 2004). The TP concept is linked traditionally with radical innovation, whereas MP is linked with incremental innovation (e.g., Herstatt & Lettl, 2004; Gerpott, 2005; Brem & Voigt, 2009). Therefore, it can be said that the more radical the innovation, the more the customer behaviour must change in order to adopt the innovation (Schiffman & Kanuk, 1997). Integrated models Even though some firms may be on the right track by focusing only on TP or MP, some researchers (e.g., Brem & Voigt, 2009) suggest that firms should not focus on a onesided innovation strategy in the long term. The strategy decisions should be done case by case, or preferably, using a combination of both strategies (e.g., Freeman, 1982; Zmud, 1984; Munro & Noori, 1988; Ulrich & Eppinger, 2008).
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Many researchers (e.g., Souder, 1989; Herstatt & Lettl, 2009) emphasise that innovation usually consists of hybrids of both concepts. Freeman (1982) found that the ability to connect technical and market opportunities is a success factor of innovation. The weight has been in the market-related activities in TP projects (e.g., Herstatt & Lettl, 2009). Ulrich and Eppinger (2008) have defined the known generic product development process, which follows somewhat the MP process concept. They simplify the TP thought by adding technology-market matching to the first (out of six) phase (planning) of the [market pull] process. Even recent NPD literature does not present a black and white case in the TP-MP debate, leaving some space for interpretation in the case level (Herstatt & Lettl, 2004) and giving a change for combining both strategies. As mentioned before, many successful firms in the market adhere to the TP approach, either intentionally or accidentally. Two great examples in different scales are Apple (Isaacson, 2011), who did not market researched, and 37signals (Sarja, 2012), who defend their stance of not listening to customers in the development phase. As stated before, the TP strategy dominates radical innovation and MP dominates incremental innovation.
2.2 Radical and incremental innovations Innovation is generally defined as a new technology or combination of technologies that offer valuable benefits to the user. The difference between radical and incremental innovation is the degree of novelty. Radical innovation involves the development of significantly new technologies or market ideas previously unknown, or that require remarkable changes to what currently exists in the market. Incremental innovation is an extension to current products or existing processes (e.g., McDermott & O’Connor, 2002). Even though the definition of radical innovation varies in the literature (e.g., Green et al., 1995; McDermott & O’Connor, 2002), one valid and measurable definition by Green et al. (1995) incorporates four dimensions: technological uncertainty, technical inexperience, business inexperience and technology cost. Many researchers also add the change dimensions: the change of customer behaviour (e.g., Samli & Weber, 2000) and the change of the existing market (e.g., McDermott & O’Connor, 2002). As radical innovation is a consequence of the TP development strategy and incremental innovation is a consequence of the MP strategy, the characteristics of both types are identical with development strategies (see Table 2). By collating and summarising the characteristics, it is clear that the development of radical projects has higher risks but also higher profit expectations (e.g., Christensen, 1997; Samli & Weber, 2000). The radicalness of innovation projects is a fundamental aspect, which has been referred to and examined under many different labels (Green et al., 1995). The most well-known synonyms of the concepts are presented in Table 3.
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Table 3 Radical Discontinuous Breakthrough Revolutionary Pioneering New-to-the-world Discovery push Original
Incremental Continuous Line extension Evolutionary Routine Extension Modifying Adapted
Table 3. Synonyms of innovation types
Successful radical innovations are exceptional compared with incremental innovations but two aspects make it an interesting research topic. If it succeeds, it is a competitive advantage for the firm (e.g., Lynn et al. 1996; Lynn & Reilly, 2002) and incremental innovation would not exist without radical innovation, because the former always follows the latter (Utterback & Abernathy, 1978).
2.3 NPD success factor research New product development and commercialisation of innovation has been an important research topic for decades, because it is a core task for development-intensive organisations (e.g., Balachandra & Friar, 1997; Ernst, 2002). Because of rapidly developing technologies, stiff competition and shifting markets, it is also a very complex and difficult process (Cooper, 1994). What we mean here by NPD success factor research, is a literature of general level development activities without distinguishing the innovation drivers and innovation types. The framework of NPD success factor research is illustrated in Figure 2.
Figure 2. The framework of NPD success factor research
2.3.1 NPD key factors by landmarks We have chosen two NPD-related landmark papers for closer examination: Ernst (2002) and Balachandra and Friar (1997). These NPD-related papers are clearly focused on research of the success factors. Both papers are meta-analyses in nature giving broader outcomes of the topic. They are acknowledged and widely cited within a large range of source material including elementary studies of NPD.
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Ernst Ernst has reviewed dozens of NPD-related papers including Cooper and Kleinschmidt’s 28 papers. The success factor in the categorisation mode used by Ernst is that originally used by Cooper and Kleinschmidt (1995). The defined categories are NPD process, organisation, culture, [senior] management commitment and strategy. The NPD process category is universal by nature and is also slightly misleading. It does not take a stand for a development process itself. Most factors sorted to this category are marketing related: the continuous commercial assessment during all phases of the NPD process, the NPD process orienting to the market needs, the distinguishing between market orientation and customer integration into NPD and the quality of planning before the development phase. The individual aspects of the organisation category are explicit: cross-functional project team members; strong, responsible and committed team leaders; responsible and committed project team members; intensive internal communication during the project and finally, the correct form of project organisation. The culture category refers to the atmosphere of innovation within the company. The objective is to create systematically an innovation-friendly and entrepreneurial climate within the firm. Enabling work with their own and other unofficial projects and enabling the realisation of creative ideas can be a way to achieve that objective. The role and commitment of senior management addresses mostly the question of adequate resource allocation for the project. According to Ernst, new product strategy has been barely examined and it requires further research. The project must be defined and the project goals must be clearly communicated. The project must have a strategic focus, which gives overall direction to the individual NPD projects and it must be a part of a long-term NP portfolio. Balachandra and Friar Balachandra and Friar reviewed more than 60 papers in the fields of R&D projects and product innovation. The authors categorised the found factors according to the method used in marketing strategy studies (Aaker, 1992). The categories are market, technology, environment and organisation. The original success factor list identified by the examined material was long, totalling 72 factors. The final 14 factors chosen were those cited by four or more studies. This selection method omitted single and caserelated factors. The noteworthy result is that the selected categorisation mode was not perfectly suitable after screening the factors, because there was no factor related to technology and only one related to the environment. Most of the success factors found by the authors are organisation related and few of them are market related. The findings of landmark papers are submitted in Table 4. It can be seen that the aspect of these meta-analyses is somewhat different. Ernst (2002) settled on finding success factors at the organisation level, whereas Balachandra and Friar also took account of external factors. The same principle goes for the original categories by Aaker (1992) and by Cooper and Kleinschmidt (1995). It can be said, that organisational-level factors are influenced by the organisations own management but that the external factors are partly given. Therefore, all factor categories used by Ernst (2002) can be included in Balachandra’s category named organisation.
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Table 4 Market related Probability of tech. success
MA¹
Technology related
Market existence
BF
Emphasise marketing
BF
Need to lower cost
BF
R&D process well planned
BF,E
Competitive environment
BF
Marketing & tech. are strengths/cross functional team
BF, E
Timing
BF
Commercial assessment, create market interphase, customer integration, process orienteering to market needs Training & experience of staff
BF, E
Project staff commitment
BF,E
Team leader capability and commitment
E
Tech. strategy tied to business strategy
BF,E
Project definition, strategic focus, NP portfolio
E
Internal communication
E
Innovation friendly climate
E
Entrepreneurial climate
E
Form of the project organisation
E
BF²
MA
Environment related Availability of raw materials
MA BF
Organisation related High level mgmt. support
MA BF,E³
Resource allocation
BF
¹ meta-analyses ² Author: Balachandra & Friar (1997) ³ Author: Ernst (2002)
Table 4. NPD success factors
It can be concluded that the findings of the NPD literature, without distinguishing the innovation driver types, are in most cases organisation and process related and do not observe the success factors related to project outcome, e.g., technology or product. The impetus for all NPD processes comes from TP or MP innovation drivers (Herstatt & Lettl, 2004; Brem & Voigt, 2009). The focus of this study is in technology push research.
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3.
The success factors of technology push projects
In the NPD literature, for example, the widely cited works of Cooper (1979–1994), Cooper and Kleinschmidt (1986–1996) and the landmark papers of Balachandra and Friar (1997) and Ernst (2002), no attempt has been made to distinguish between radical and incremental products, or to acknowledge that the emphasis has been on MP projects. The number of studies on success factors related to TP projects is limited. We have chosen two meta-analyses landmark papers for closer examination: Bishop and Magleby (2004) and Samli and Weber (2000). Figure 3 illustrates the framework limited to success factor research of TP products.
Figure 3. The framework of TP products success factor research
These two landmark papers were chosen for several reasons. First, they are focused solely on TP projects. Secondly, the perspective of both papers is clearly to trawl success factors. Thus, the focus of the selected papers is very similar to ours. The only difference is that the selected papers are not limited to a certain industry, whereas we consider the ICT context only. Both papers are wide-ranging and cover several research targets. Samli and Weber researched 30 separate long life cycle radical product cases and Bishop and Magleby reviewed 10 different level papers concerning the success factors of TP products. Finally, both papers are relatively new in this topic area. The authors of both papers have ranked their findings according to relative importance by using justified metrics. These findings are based on specific cases and in different contexts; thus it is clear that their findings are comparable only within the meta-analysis but not between them.
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Bishop and Magleby researched the evolution of TP models for further research. They also studied the success factors of TP-developed products and thematized them into eight categories for further TP model research purposes. They studied 10 separate sources of differing natures, representing different levels of studies. The sources are from the period 1987 (Paul) to 2003 (Himmelfarb). The meta-analysis consists of:
Five journal articles. One out of five articles is poor according to today’s standards. Its length is only two pages, has no quotes and does not reveal how the results and conclusions are achieved.
One article published only on the Internet, which no longer exists.
One panel discussion note (linked with a journal article by the same authors).
Three business books.
The varying level of sources over a long period confirms the understanding that the quantity of TP-focused success factor research is limited. From our perspective, it is notable that only two studies in this meta-analysis were wholly within the ICT context. Samli and Weber researched 29 separate long life cycle radical product cases. They make a clear distinction between incremental and radical innovation research and they lambasted other NPD research for not distinguishing the innovation types but keeping them as one broad new product category. The authors chose 30 long life cycle (over 10 years) products from the breakthrough innovation list identified by the Business Week magazine (one company did not take part in the study). They tested their hypotheses by interviewing the marketing division staff of the organisations behind the chosen products. Six out of eight hypotheses were supported regarding the success factors of radical innovation. From our perspective, it is notable that none of researched cases was within our narrower limited ICT context (see our definition of ICT context). The environments of the landmark studies are presented in Figure 4.
Figure 4. The landmark TP meta-analyses
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3.1 TP success factors by landmarks Bishop and Magleby Bishop and Magleby state that each of the papers they studied was written by authors of different backgrounds and was aimed for different audiences. The backgrounds of the authors varied from engineering, marketing, consulting and R&D management. The background of the audience ranged from practitioners to researchers. The same principle works between both landmark papers. Bishop and Magleby divided the success factors they found into eight categories. According to the authors, the success factors are as follows, arranged in order of significance: 1. There is a focus on customer/end user needs Customer or end user needs were considered during the development of the product. 2. Internal/external networks were used Networks internal and/or external to the company were used during product development, which were beyond interacting with customers and end users. 3. There is management support There existed support from the management either directly or through methods, such that management generally have control over such as the organisation model. 4.
The development team is dynamic, motivated and/or talented
There was a high level of expertise, motivation and/or ability within the product development team. 5. A combination of MP and TP is used Both MP and TP methods were used in the same product development process beyond simply including customer and end user needs with TP elements. 6. The market is developed during or directly after product development The market was developed, instructed or prepared simultaneously with development of the product. 7. The technology offers a clear advantages The product offers a clear advantage over other, similar products, directly because that technology was the basis for the development. 8. Alternatives were examined carefully Alternative technologies, products and markets were examined carefully by the product developers during development. The authors state that because of the diverse audiences and researchers, the success factors are written using terminology that is inconsistent. Perhaps because of this, the
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developed factors are intangible by nature and somewhat difficult to measure, define and even distinguish from each other (e.g., factors 1, 5 and 6). For instance, roughly speaking, if we are using a combination of TP and MP, we are focusing on customers and we are developing for the market. Samli and Weber Samli and Weber constructed a series of eight hypotheses for testing the relevance of their universal model of breakthrough development. Six out of eight hypotheses were supported. The hypotheses are introduced in order of significance (the pair H2 & H3 is equivalent). 1. Technological push results in new products that are not readily adopted. The development of technology push products is a long-term action. From the firm’s point of view, it means a commitment to technology push projects in the long run. 2. The degree to which a new product is a breakthrough will increase the length of time before the product is adopted by the market, i.e., technophobia. The novelty of technology push products affect the adoption time by the market. In reference to the target of our study, we see this factor as very close to the previous one, technophobia, such that we discuss them as one factor. 3. The greater the percentage expenditures on new product development and related research, the greater the number of new successful products introduced. More than 62% of the respondents to the landmark papers spent over 20% of their total budget developing new products. 4. The level of a breakthrough has a direct correlation with the longevity of the product. Even though technology push products are not accepted quickly by the market, they display longer life cycles than minor product developments or line extensions. 5. Technophobia This factor is combined with the degree of novelty factor (nr. 2). 6. Products that fill an unrecognised need will have greater longevity than those that do not. If the firm has no knowledge of the market and it is proceeding completely with an internal technology push, it is not likely to be successful. The order of significance is calculated in a different way in each meta-analysis. Therefore, the order is valid only inside the same meta-analysis and it is not comparable between the meta-analyses. In order to simplify the factors of both papers and to enable links between them, we have thematized all the findings according to common factors. This was done by thematizing the found success factors. Thematization enables a comparison of the
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occurrence of certain themes (Eskola & Suoranta, 1998). We compiled four different categories: market, product, management and organisation [related] factors. The different aspects of management- and organisation-related success factors existed so clearly that we distinguished them as separate categories. We also shortened the findings for simpler representation. The summary of TP success factors is illustrated in Table 5. Table 5 Market related
MA¹
Product related
MA
Management related
MA
Focus on customer needs
BM²
TP for difficult adopted
SW
Management support
BM
MP methods used
BM
Life cycle
SW
Degree of funding
SW
Market development
BM
Fill an unrecognised need
SW
Alternative study
BM
Technological advantages
SW
Adoption time/ SW³ technophobia ¹ meta-analyses ² Author: Bishop & Magleby (2004) ³ Author: Samli & Weber (2000)
Organisation related Networking
MA
Project team skills
BM
BM
BM
Table 5. TP success factors
3.2 TP research in ICT context The ICT context in our study is limited to hardware and software products in computer, mobile phone and network applications industries only. Only two studies out of the ten in the meta-analysis by Bishop and Magleby were solely within the ICT context (Isaacs & Tang, 1996 and Spivey et al., 1997); moreover, one study had one ICT case study out of four within the desired context (Lynn et al., 1996). The other landmark paper by Samli and Weber had no cases within an ICT context. They categorised four researched radical products as “Telecomm.” applications but those products do not fit our definition for ICT (fibre optic phones, a book-size video camera and two different HI-FI TVs). The position of the ICT-related TP products within the entire NPD field is illustrated in Figure 5.
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Figure 5. The framework of ICT-related TP products success factor research
We have gathered the success factors within an ICT context categorised by Bishop and Magleby. The aforementioned two ICT-related sources of the study give the following factors: 1.
Internal/external networks are used
2. There is management support 3. There is a focus on customers/end users 4. The development team is dynamic, motivated and/or talented 5. The market is developed during or directly after product development 6. The technology offers clear advantages Limiting the context from general TP projects to ICT projects causes a change in factor category ranking. Factors 1 and 2 are referenced by both studies and factors 3–6 are referenced by one or the other. The order of the remaining factors is according to the original meta-analysis. Table 6 represents the factors according to the familiar categories. Some conflicting issues led us to constitute a premise. First, the quantity of source material is too slight in terms of our target; a concrete set of the success factors. The discovered factors are intangible by nature for deriving concrete factors. Paradoxically, the findings of these two studies within an ICT context have already covered six out of the eight factor categories, which were defined without the industry limitation when all ten studies in the meta-analysis were investigated. Comparing the general TP research and the TP research limited to an ICT context, we can conclude a premise: The success factors of the TP products are industry independent.
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Cusumano (2010) made same kind of assumption with his Six Principles [of effective management of strategy and innovation]: “What I offer is a selective list, mainly from the automobile, computer software, telecommunications, consumer electronics, and Internet service industries. But, because of their generality, I am convinced that these principles provide essential lessons for managers in nearly any industry.” In practice, the premise means that we can constitute the list of the success factors of ICT-related TP products with TP research in any industry. The industry independent success factor set of TP products was discussed in chapter 3.1. Table 6 Market related Focus on customer needs Market development
Product related Technological advantages
Management related Management support
Organisation related Networking Development team skills
Table 6. TP success factors limited to ICT industry by landmark study
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4.
Specification of the TP success factors
The NPD and innovation literature have presented many success factors for developed products. Parts of these factors are comprehensible, but, unfortunately, many of them have conspicuous characteristics; they are nebulous in nature. Many times, they can be explained many ways. Balachandra and Friar (1997) concluded this previously, and, as an example, they underlined that the terms “emphasize marketing” and “support of top management” may take many different forms. The authors explain the factors that are considered so self-evident in many cases that no clear definitions are given, even though they may have different meanings. The same phenomenon applies to the previous study of Sarja (2014a). As the author concludes, “The current literature does not provide exact key factors but instead, rather descriptive vague topics.” For rationalizing the success factors, we have divided them into smaller, precise pieces and proposed a reasoning of the factors.
4.1 Market related success factors MP methods used We see that MP thought is not a method but rather is an innovation driver approach (e.g., Herstatt & Lettl, 2004; Sarja 2014a), and this key factor covers somewhat the next three market related success factors: a focus on customer needs, market development and alternative study. In addition, following the MP based generic development process introduced by Ulrich and Eppinger (2008), the MP approach will be taken into consideration. The general level description of the generic development process is illustrated in figure 5.
Figure 5. Generic development process (source: Ulrich & Eppinger, 2008)
The generic development process describes the market-pull situation. The authors separate the TP and MP situations, explaining that, in the TP case, a firm begins with a new technology and tries to find an appropriate market; whereas, in the MP case, a firm begins development with a market opportunity and tries to satisfy market needs using whatever technologies are available. This separation is done by adding technologymarket matching to the first phase (planning) of the (market pull) process. In summary, it can be concluded that the development process itself should be the same regardless of the innovation driver (TP or MP). This premise is supported by numerous studies with different NPD perspectives, for example, marketing-R&D co-operations or TP-MP integrated models (e.g., Freeman, 1982; Zmud, 1984; Munro & Noori, 1988; Souder, 1989; Herstatt & Lettl, 2009).
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Focus on customer needs Customer needs means basically that the customer solves some problem by purchasing a product (a good or service). Most literature about NPD, also TP-focused, stresses that customer needs must be identified at the beginning of the development process. For example, Ulrich and Eppinger (2008) examine preparatory customer related studies, including customer needs collection for the two first phases (0=planning, 1=concept development), in their generic development process. After articulating market opportunities and defining market segments in the planning phase, the needs of segmented customers (e.g., Kotler & Armstrong, 1987, pp. 203–224) in a target market should be identified in the concept development phase. The output of identifying customer needs is a constructed list of customer need statements, organized in hierarchical order with importance weightings. The five-step process for identifying customer needs is: 1. Gather raw data from customers 2. Interpret the raw data in terms of customer needs 3. Organize the needs into a hierarchy of primary, secondary and (if necessary) tertiary needs 4. Establish the relative importance of the needs 5. Reflect on the results and the process Market development The term market development has many statements. Thinking about the found success factor of a TP product, it is reasonable to adopt the commonly used Ansoff model (Figure 3). The Ansoff model describes firm growth strategy opportunities. It contains four growth options that are used based on product and market maturities.
Figure 6. The Ansoff model (Ansoff, 1957)
In the model, market development means a firm’s attempt to identify and develop new markets for current products. However, it does not apply to the new product context. Therefore, when we use the concept of market development in this paper, we actually mean the concepts of product development (new products for existing markets) and diversification (new products for new markets). Bishop and Magleby (2004) state that the market must be developed, instructed or prepared simultaneously with the development of a product (see Sarja, 2014a). We agree with this view in terms of the definition of a target market by a development firm.
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Alternative study Alternative study regards a kind of sub-process in the concept development phase of the development process that is similar to customer needs identification. Time-wise these two processes will be actualized simultaneously. Ulrich and Eppinger (2008) state that the alternative product concept must be generated and evaluated in the concept development phase. There are numerous studies of competitor analysis in marketing literature (e.g., Chen, 1996; Peteraf & Bergen, 2002; 2003). We would like to note a slight difference between the concepts of alternative analysis and competitor analysis. Competitor analysis is a marketing related term concerning products, whereas alternative study (or analysis) concerns only new products, processes and methods (in the market). Because there is not a significant number of studies about alternative analysis, we make an assumption that alternative studies can be done with the same method as competitor analyses. A significant argument was found by Lewitt (1960). He stated that business should not be defined in terms of product types but in terms of customer needs to be served. This thought encourages management to study business and growth opportunities more broadly (Peteraf & Bergen, 2003). An example of this aspect is the electric car. The other brands are not the only competitors; other economical vehicles and even public transportation are also competitors. With a similar thought, Chen (1996) defined the framework for competitor analyses. It was based on two dimensions: market commonality and resource similarity. The framework maps three kinds of competitors, indirect (substitutes), direct and potential, depending on the degree of dimensions. The framework of competitor analysis is illustrated in figure 7.
Figure 7. The framework of competitor analysis (based on Chen, 1996; Bergen &
Peteraf, 2002) Adoption time, technophobia Adoption time is the space of time when the consumer adopts new products or ideas. The more dramatic a new product is, the longer the adoption time (e.g. Samli & Weber, 2000). There are many models to explain adoption (e.g., Mahajan & Wind, 1986; Mahajan et al., 1990; Sultan et al., 1990, Narayanan, 1992). Most models are based on the Bass (1969) model (Narayanan, 1992).
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There are many definitions for the noun technophobia, and the early definitions are from the PC era. Brosnan (1998) uses the most commonly cited definition of Jay (1981) in his landmark book about technophobia. Jay (1981) defines technophobia as the following: 1) A resistance to talking about computers or even thinking about computers 2) Fear or anxiety towards computers 3) Hostile or aggressive thoughts about computers Briefly, Brosnan (1998, p. 33) states that the overall concept of technophobia is a combination of computer anxiety and a negative attitude. In this study, we deal with the given definitions, but we expand the cause of technophobia from computers to any technology based new product. We see that these two concepts, adoption time and technophobia, have a clear linkage in the field of NPD research, particularly when speaking about technology pushed products. Many scholars and research communities are in step with us, for example when explaining that user acceptance has been a long-term issue in highly esteemed MIS2 research (Davis, 1989). Brosnan (1998, p. 171) and the HCI3 community (Davis, 1989) emphasize a commercial motivation for continued user-friendliness in hardware and software due to an attempt to appeal to technophobes. Different technology acceptance models support this thought; users must feel that an application is useful (perceived usefulness) and easy to use (perceived ease of use). The roots of acceptance models are multidisciplinary, from sociology and psychology to information system research (IS) (see e.g., Venkatesh et al., 2003). In NPD research, the most known and highly cited technology acceptance model is TAM (Davis, 1989) and its extensions, TAM 2 (Venkatesh & Davis, 2000), TAM 3 (Venkatesh & Bala, 2008) and the unified theory of acceptance and use of technology (UTAUT) (Venkatesh et al., 2003). Technology acceptance models explain why users adopt or do not adopt new applications and give tools to promote positive adoption. The weakness of the models is that they do not take into account the time of adoption.
4.2 Product related success factors TP for difficult adopted TP driven products typically take longer to be adopted by the majority of customers (see the categories of adopters by Rogers, 1962). The adoption time from the customer’s point of view and the natural resistance of users to new solutions is discussed above. This factor is the adoption time domain from the developers’ perspective. The longer the adoption time from a firm’s point of view, the longer the run commitment to a project, especially in terms of resources. This is one reason, which makes TP projects risky. If risk is controlled and a product succeeds, the expected life cycle is also longer.
2
Management Information Systems [Quarterly]
3
Human-computer interaction
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Life cycle Firms develop new products to get long-term profits (Griffin & Hauser, 1996). A good example of the expected longer life cycle of successful technology push (also called as breakthrough) products is a study of Samli and Weber (2000), where they examined successful breakthrough developers, in total, 130 firms with 143 products, which had been in the market for over a decade. Product life cycle means total product existence from raw material sourcing to manufacturing steps, usage and, finally, to discarding or recycling (e.g., Tseng & Chen, 2004). For the firm’s perspective, we widen this concept by including also the development phase. The basic idea behind the life cycle factor, from an idea until the end of a product’s life, is economic planning. Samli and Weber (2000) see life cycle reasoning as a financial and human resource issue. Fill an unrecognized need The importance of focusing on customer needs in the development phase is discussed above. In the ideal world, a radical or breakthrough product fills a need customers did not consider. However, proceeding totally with an internal technology push is a lottery game. Samli and Weber (2000) emphasize that a new product must fulfil at least a somewhat recognized need. Calantone and Li (1998) are in step, stating that if a company has no knowledge of the market, it is not likely to be successful. Technological advantages Technological advantage is a multilevel concept. Depending on the study, the aspect can vary from country level to firm or project level. At firm level, technological advantage represents a firm’s ability to develop technology pushed breakthrough products instead of just satisfying existing demand (Samli & Weber, 2000). At project (or product) level, technological advantage means the overall benefits of a product (compared to other similar products), which has been developed on the basis of technology. Cooper and Kleinschmidt (1995) found that the success factors may be different at firm level and project level. There are many reasons for this, but, generalizing, there can be many different projects with different degrees of investment within the same firm. This principle applies to any success factor, including technological advantage. In this context we are primarily interested in technological advantages at project level and, secondarily, at firm level.
4.3 Management related success factors Management support Since management is too large a complex of issues to divide in this context, we share Ernst’s (2002) view that the most important support from management is to ensure needed resources. Ernst also emphasizes that non-material support may be nothing more than lip-service. Samli and Weber (2000) explain that management must have adequate financial and human resources for generating breakthrough products.
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Degree of funding The degree of funding is an important part of a firm’s NPD strategy. In a study of Samli and Weber (2000), a generous majority of researched firms spent more than 20 per cent of their total budgets on developing new products, and this fact was the most important consideration. In general, adequate funding [and personnel] must be available, and it must be maintained during the development process for carrying out the research and development process (Samli & Weber, 2000). Ulrich and Eppinger (2008) suggest that aggregate planning for firms in terms of efficient use of their resources is pursuing only projects which can reasonably completed with budgeted resources. In a planning phase, management must prioritize the most important projects in terms of the success of the firm, those projects that are realizable with adequate resources. Other projects can be stopped or postponed.
4.4 Organization related success factors Project team skills In a study of Sarja (2014a) had found few characteristics of development personnel: training, experience, commitment, expertise, motivation and ability. The author summarized these characteristics as team skills. In this study we limit out the skills in individual level, and we focus to thought that the team skills are the consequence of cross functional teams. Actually, this was the original idea of teams (e.g. Marquis & Straight, 1965). In general, many cross-functional team related studies emphasize the relationships between marketing and R&D (e.g., Griffin & Hauser, 1996). Cross-functionality has been found, without exception, to be a success factor of NPD (e.g., Cooper & Kleinschmidt, 1995). We share our focus with Ulrich and Eppinger (2008); a product development team should have expertise at least in marketing, design and manufacturing functions. Networking The way to consolidate in-house know how and resources is networking. The first phase of the networking concept includes lead users or customers in the development process (e.g., von Hippel, 1988; Kristensson et al., 2004). Bishop and Magleby (2004 in Sarja, 2014a) required (but not described) more; networking must be beyond interacting with customers and end users. The next logical step is supplier involvement (e.g., Ragatz et al., 2002). Freel (2003) explored the relationship between networking with three horizontal actors: competitors, universities and the public sector. Aside from consolidating in-house know how, the benefits of networking are also risk and cost sharing, access to new technologies and markets and attempts to shorten development time (Ledwith & Coughlan, 2005). While networking was recognized as one of the key factors of technology pushed products, Ledwith and Coughlan (2005) found that there are conflicting findings in several studies between networking on a new product development and increased success. Their own study of 60 electronics firms found the same results. Therefore, the authors suggested a framework for managing networking in NPD projects for reaching successful collaboration. The framework is based on three variables:
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1) The type of organization with which to collaborate Who? Which organizations should firms involve in their NPD projects? 2) The skills or absorptive capacity of the firm Skills? Do the firms have the necessary skills to benefit from the collaboration? 3) A firm’s new product strategy Why? Are the reasons for collaboration consistent with the firms NPD strategy?
4.5 The survey instrument framework The research push case study survey instrument framework is based on the introduced success factors. The framework is illustrated in figure 8. The proposed framework is relatively broad and it is possible to use only part of it depending on the focus of the case study. The framework is meant to be used in various types of data collection in case studies, for example interviews, surveys, document and literature analyses and so on. One proposal question list based on the framework is presented in Appendix 1. The framework leads to a focus to marketing related activities, organizational abilities and resource and time aspects, and these determinants are discussed in chapter 5.
Figure 8. The survey instrument framework
4.6 A short case: Basecamp The objective of this short case narrative is to support partly presented success factors. Interpretive short case demonstrates how the small company named Basecamp has
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included the characteristics need recognition, lowering adoption time and technological advantages to their developing processes and working methods. The case is broadly studied (Sarja, 2011) by the author and concluded to the research paper (Sarja, 2012). The Basecamp company, formerly known as 37Signals, is a software developing company and it has broken through with its web applications. The firm is a kind of phenomenon and followed increasingly. Regardless of its small size, the firm is a famous case in software engineering craft, especially in US. The unique and popular products, the outcome of the small firm, the books wrote by the key men of the firm, and the own way of business thinking has raised it to spotlight. Their most known products are project management tool Basecamp and web development platform Ruby on Rails. Basecamp is the first ranked application in its own category [according to webpage of the company], and Ruby on Rails is increasingly embraced by programmers (e.g. Paulson, 2007). As previously discussed, the TP approach mean stimulus for the new products and processes come from firms’ own know-how (e.g. Brem & Voigt, 2009). The new product can be the result of emerging technology, new combination of existing technologies, or process innovation (e.g. Mowery & Rosenberg, 1979; Herstatt & Lettl, 2004). Rest on deep examination (Sarja, 2011; Sarja 2012) Basecamp is a good example about the TP-oriented firm in many ways. First, technologies are combined in a new way in its products (e.g. Ruby on Rails). Second, the products are differentiated from competitors by simplifying them in radical way. The key men of the firm call that as “underdoing the competition”. This resembles greatly Bower and Christensen’s (1995) disruptive technologies pattern: purely technically or performance vice the disruptive technologies are not the most advanced, but rather simpler, cheaper, reliable and easier to use. In many cases simplified design means also new ways of technology combinations, and it is supported, for example, by Agile Manifesto 4 (Simplicity – the art of maximizing the amount of work not done – is essential) and the heuristic evaluation method by Nielsen & Mack (1994). Third, the case firm has created whole new processes, for example the software development approach named Getting Real (Sarja, 2011; 2012). Fourth, one of the main principles of the case firm has been not to market research or not to communicate with customers in development phase. Brem & Voigt (2009) explain the goal of the TP products is to make commercial use of new knowhow. The impulse is coming from application push or technical capability without considering if a certain demand already exists or not. The matters around these four TP characteristics – from the firms’ point of view - are thoroughly discussed in two books wrote by the key men of the case company. Among other things these TP characteristics seem to be also the competitive advantage of the firm. This narrative based on the empirical material of the original studies of the author (Sarja 2011; Sarja 2012). The empirical material of original studies consists of two books wrote by the key men of the firm (Getting Real, 2006; Rework, 2010), approximately 5 hours of transcribed video material and professional literature with magazine articles. The narrative of the TP case firm supports three success factors previously represented in this work; need recognition, technological advantages and lowering adoption time.
4
The Agile Manifesto includes general rules and principles for agile software development methods and it was signed by seventeen influential persons in the field in 2001 (e.g. Cohen et al., 2004).
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Need recognition Theme need recognition combines two different success factors, focus on customer needs and fill an unrecognized need. Although the perspective of factors is slightly different the both factors are valid and can be handled in this case narrative in one. The product related success factor, in general level, suggests that the developed product must fulfil at least somewhat recognized needs (e.g. Samli and Weber, 2000). This thought realizes with the case company as the key men emphasize most of their products has created solving the own problems of the company. They justify this approach by being strong aware what is the real problem and how to find solution for that. They give two product examples in the book Rework about this successful approach; Basecamp and Highrise cloud applications. Another driver for the development work has been dissatisfaction with products on the market. Then, it is likely that someone else has a same problem. In Basecamp application case they chose design firms as a target market, and focused to serve only them. In that phase the targeted customers, with the help of the case company, solved their specific problems and the perceived usefulness of the product increased. Gradually the application reached also the other customer groups. The Basecamp case gets great support from the disruptive technology model (Bower & Christensen, 1995; Christensen, 1997), but also from Moore’s (1991) widely cited crossing the chasm theory. The approach of the case firm is relatively lean in nature, but the identification of customer need in the beginning of the NPD process (e.g. Ulrich & Eppinger, 2008) was done (though without any formal process) as well as the customer segmentation (e.g. Kotler & Armstrong, 1987). Technological advantages The technological advantage of the case company is definitely a product design. All applications are designed simplified way. In practical, it means that the product comprises only features needed to fulfil the customers’ needs, and all other features have left out. Furthermore, the case company has concentrate carefully to details of user interface in word level, aiming at design consultative applications. The key people of the case company have created the design philosophy which they call as modus operandi: “We believe software is too complex. Too many features, too many buttons, too much to learn. Our products do less than the competition – intentionally. We build products that work smarter, feel better, allow you to do things your way, and are easier to use”. The modus operandi summarizes how the case company has differentiated itself, and the competitive and technological advantages of the company. Very carefully studied interfaces give user strong perceived ease of use feeling, which decreases anxiety and resistance to new application (aka technophobia), as well as adoption time (Sarja, 2012.) Reduced adoption time naturally speeds up the cash flow financing. The ability of the case company to develop technology pushed breakthrough products (instead of just satisfying the existing demand, Samli & Weber, 2000) consists of own processes and developing approaches (Getting Real), own tools for programming (Ruby
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on Rails) and project management (e.g. Basecamp, Campfire) and admitted ability to user interface design. Lowering adoption time As formerly discussed, the user must feel the usefulness and easiness of the product for avoiding resistance and for adopting it sooner, and therefore the user experience have been researched widely already decades. In Basecamp case lowering adoption time is overlapping factor with two previously discussed factors. It can be said that lowering adoption time is outgrowth of need recognition of the targeted customer group outside the mainstream and minimalist design with advanced user interface design. In many sources the key men of the company emphasizes minimalist design with only limited amount of the features. The features included to the product should be only those that are necessary for complete the task. The product with selected features appeals to at least some extent all users, unlike the congested ones. They believe people like the lean applications solving single problems. The lean application has an opinionated nature, and minimizes the decisions the user must made. The user interface is designed in word-level and the user knows all the time what to do. It is notable, that lowering adoption time success factor - from developers’ perspective produces a quicker faster cash flow. The tricks needed to implement the factor reduce testing time and the amount of bugs, lowers the cost of change and decrease the maintenance work.
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5.
Discussion
The aim of the recognition of TP success factors is on the other hand to help firm’s management to recognize the real actions needed to reduce the product development risks, but also help scholars to focus to right issues when studying the success factors of breakthrough cases on the other. For example, different survey instruments (e.g. questionnaires, surveys) can be built accordingly. As background information, we studied two meta-analyses. We found relatively long lists of NPD success factors. However, there are a few complications with those findings. Firstly, they are too universal by nature. They do not distinguish innovation drivers and/or innovation types; therefore, they are basically only good for general level hints on how to manage project oriented organisations. On the other hand, the universality concerns the forms of factor expression. Most of the factors are ambiguous and they are more like categories (as Bishop and Magleby termed them) than exact factors. After limiting success factor studies initially to TP projects only and then later, to TP projects within the ICT industry, we realised that in today’s literature, the key factors of TP projects are industry independent. There might be some branch-related factors but the current research does not provide answers to that assumption. After ICT industry limitations, we needed to turn back to the general TP level. We found only one of the studied meta-analyses, which was that of Bishop and Magleby, had two ICT-related examples. Paradoxically, even though the data source was clearly too small, the findings were almost the same than without the industry limitation. We also noticed that there was no reason to omit the remaining findings of mentioned landmark and that the same applies to the other studied landmark of Samli and Weber. All found success factors could also apply to ICT projects. We also obtained some support for our premise from other independent NPD literature, e.g., Cusumano (2010) that the success factors are industry independent. This feedback is illustrated in Figure 9.
Figure 9. Findings after the premise
Therefore, we examine the general TP success factors in closer detail (represented in Table 5). As practically all NPD-related literature, regardless of perspective, emphasises the market-related factors, so too does TP research. We categorised five relatively broad
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success factors found by landmark works under the theme of market. The factors named “market development” and “focus on customer needs” are also found by NPD-level literature, restated in slightly different wording. The factor “MP methods used” is more or less pointless in this context; we think it covers roughly all market-related actions, issues and factors and it is difficult to see it as an individual success factor. The factors “alternative study” and “technophobia” are obviously success factors for research pushed new products. It is important to compare the alternatives, question individual output and to outline the real benefits of the innovation. The novelty of TP products is always in the higher level and the adoption time is longer, whereupon the usability must be studied carefully in order to avoid technophobia. As TP projects are run comprehensively around the developed product, the TP-level literature takes into account naturally the product-related success factors, unlike general NPD research. The factor “technological advantages”, together with the market-related factors above, obtains support from the NPD level (“marketing and technology are strengths”). The other product-related factors are strongly time centred: the duration of adoption time and the length of the life cycle. Longer adoption times, from the firm’s perspective, mean long-term commitment, especially regarding resources. However, in a case of product success, the expected life cycle is longer. A contextually different product-related success factor suggests the product must “fill an unrecognised need”. It is a matter of opinion as to which category to position it in (market or product). Because it is somewhat unpredictable, we see it more as a consequence of development work than as a clear success factor. The management- and organisation-related factors are approximately the same as in the general NPD literature. The main points are resource ensuring, networking and a multitalented development team. In order to obtain the exact success factors, the found factors were divided to exact pieces. For example, the factor named “emphasise marketing” can really mean many specific things in practice. Secondly, almost all found success factors belong to marketor organisation-related categories. For sure, no one in a development intensive business challenges the importance of market needs and the skills and enthusiasm of the organisations. However, we think there must be some technological- or product-related factors that are important when trying to find out why some products are successful. Taking account of the universality of the found NPD success factors and missing product-related factors, we conclude that before starting to develop a research pushed product, a firm should ensure the basic things – the NPD level success factors – are taken into account. After defining the content of TP success factors, we found three keynotes, which combine the definitions. The first keynote in the study is market observation activities in parallel with product development, or, rather, embedding them as a part of the development process. This can be seen from different angles in terms of several success factors. MP methods used guides the start of market observation immediately when planning a new product idea. This success factor also emphasizes another important issue; the development process, including marketing activities, should be the same regardless of the innovation driver (TP or MP). Consequently, customer needs must be identified systematically (focus on customer needs, fill an unrecognized need), and alternative solutions in the market must
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be studied in terms of customer needs instead of in terms of just itemizing competitors (alternative study). The outgrowth of these studies is the target market (existing or new) definition (market development). Technological ability contributes to developing valuable new products for customers, filling recognized – and in the ideal case – also unrecognized needs (technological advantages). The second keynote relates to organizational ability. The core task of a firm’s management from the product development perspective is to ensure needed resources for development work (management support). Because resources are always limited, they must be allocated in terms of the results of aggregate planning and project prioritizing (degree of funding). Generally, resources consist of human and financial domains (Samli & Weber, 2000). A capable development team is cross functional (project team skills), and the way to consolidate in-house know how and resources is networking (networking). Because of previous conflicting findings between NPD and increased success, networking activities must be planned strategically (Ledwith & Coughlan, 2005). The third keynote associates financial resources and different time aspects. As discussed, a long adoption time of TP products lies ahead. From a customer perspective, this means the acceptance time of new technology. At least partly, the acceptance time can be shortened by user-friendly design (adoption time, technophobia). From a firm’s perspective, a long run commitment to a project is required, in the other words, adequate financing (TP for difficult adopted). Finally, if the project is well planned and it pulls through the development phase, the end of the life (and payback) time is expected to be longer (life cycle). It is notable that an important factor in terms of product attributes is user-friendliness. Most probably it is the most significant product attribute, and has a clear relation to product related success factors. As an attribute it is easy to perceive, measurable, and strongly supported by the previous literature, and for example, by the interpretive short case introduced in this research (see chapter 4.6). There might be some other technological- or product-related attributes as well, but it seems that the current literature does not recognize them. Another notable thing is that, depending on research angle, a single success factor can be thematized differently. The novelty of this work is screening and identification of TP success factors and definitions of them, and in that sense it confirms and refines previous studies. The reliability and validity of the work are somewhat how we described them in a research design phase (see chapter 1.2). For further research we propose to test suggested success factors in breakthrough case studies. Naturally, there is some space when applying the results of this study. If some success factors are in closer examination in a case study, it is possible to go deeper.
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6.
Conclusions
Based on large literature content analysis in NPD domain, thirteen TP success factors were identified and categorized. The market related success factors are: focus on customer needs, MP methods used, market development, alternative study and adoption time/technophobia. The product related success factors are: TP for difficult adopted, life cycle, fill an unrecognized needs and technological advantages. The management related success factors are management support and degree of funding, and the organization related factors are networking and project team skills. During the study we realised – with the support from other researches – that in today’s literature, the success factors of TP projects are industry independent. There might be some branch-related factors but the current research does not provide answers to that assumption. Therefore, the ICT context has treated like any industry with TP development activities. The current literature does not introduce many of firm’s success factors clearly. The factors may be presented too widely. In many cases, the factors were found to be selfevident, but, on closer examination they may have different meanings. The second round of content analysis, based this time on each success factors individually, gave proposal transcripted definitions of the TP success factors which are presented in chapter 4. For supporting future research cases in this field, the proposal survey instrument framework has led from the transcripted definitions of the success factors. The framework leads to focus to marketing related activities, organizational ability, resource ensuring and time aspects.
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Appendix 1 Example of interview question list 0. Aloituskysymykset (nimi, organisaatio jne.) 0. Background questions (name, organization etc.) [Questions about the Market related success factors] A. MP methods used 1a. Oliko käytössänne jokin määritelty ja/tai dokumentoitu tuotekehitysprosessi? 1b. Did you have any descripted and/or documented product development process in use? 2a. Yritittekö löytää teknologiallenne sopiva asiakkaita ennen tuotekehitysprosessia tai sen alussa? 2b. In the beginning of the development process, did you try to find appropriate customers for your technology? 3a. Olitteko yhteydessä asiakkaisiin ennen tuotekehitysprosessin alkua tai sen alkuaikoina? Esimeriksi esittelittekö tuotteen asiakkaalle? 3b. In the beginning of the development process, did you contact the customer in some way? For example, did you introduce the product to him/her? 4a. Pidittekö asiakkaan tietoisena tai mukana tuotekehitysprosessissa sen aikana? 4b. Did you keep the customer in the loop during the development process? 5a. Oliko markkinointi (henkilö, organisaatio) mukana tuotekehitysprosessin alussa ja/tai aikana? 5b. Did the marketing sector (person or organization) belong to the development team? B. Focus on customer needs 6a. Teittekö asiakassegmentointia ennen tuotekehitysprosessia tai sen alussa? 6b. In the beginning of the development process, did you segment your appropriate customers? 7a. Yritittekö selvittää asiakkaan täsmälliset tarpeet ennen tuotekehitysprosessia tai sen alussa? 7b. In the beginning of the development process, did you try to define the exact need(s) of the customer/customer segments? 8a. Dokumentoitteko asiakkaisiin liittyvät havainnot ja löydökset jollain tavalla? Kuinka? 8b. How did you document customer related findings? 9a. Tutkitteko ja tulkitsitteko havaintoja jotenkin? 9b. Did you interpret findings somehow?
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10a. Järjestittekö tai painotitteko asiakastarpeita jollakin tavalla (esimerkiksi tärkeyden mukaan)? 10b. Did you order/weight the needs somehow (e.g., importance)? 11a. Päivitittekö asiakastarvedokumentteja tuotekehitysprosessin aikana? 11b. Did you update customer need (list) during the development process? C. Market development 12a. Määrittelittekö kohdemarkkinoita ennen tuotekehitysprosessia tai sen alussa (olemassa olevat/uudet markkinat)? 12b. In the beginning of the development process, did you define the target market (existing/new)? 13a. Määrittelittekö kohdemarkkinoita jollakin muulla tarkemmalla tavalla? 13b. In the beginning of the development process, did you define the target market by some other more specific way? 14a. Päivitittekö tai määrittelittekö uudelleen kohdemarkkinoita tuotekehitysprosessin aikana? 14b. Did you update/redefine the target market during the development process? D. Alternative study 15a. Tutkitteko vaihtoehtoisia ratkaisuja asiakkaan ongelmaan ennen tuotekehitysprosessia tai sen alussa? 15b. In the beginning of the development process, did you make an alternative study? 16a. Huomioitteko vaihtoehtoisina ratkaisuina (alternative study) muitakin kuin suorien kilpailijoiden tuotteet (esimerkiksi muut/potentiaaliset teknologiat)? 16b. Did you notice the other solutions for customer needs than direct competitors (e.g., other indirect/potential technologies etc.)? 17a. Päivitittekö vaihtoehtoisien ratkaisujen listaa (alternative study) tuotekehitysprosessin aikana? 17b. Did you update the alternative study during the development process? E. Adoption time/technophobia 18a. Millä tavalla huomioitte tuotekehitysprosessin aikana tulevaan asiakkaan [tuotteen] omaksumisaikaan? 18b. During the development process, how did you prepare yourself for customer adoption time in advance? 19a. Millä tavalla huomioitte asiakkaan omaksumisajan? Yritittekö lyhentää sitä? Miten? 19b. How did you take into consideration customer adoption time? How did you try to shorten it? 20a. Otitteko tuotekehitysprosessin aikana huomioon asiakkaan tuntemukset tuotteen hyödyllisyydestä? Miten?
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20b. During the development process, did you take into consideration the customer’s feeling about the usefulness of the product? How? 21a. Otitteko tuotekehitysprosessin aikana huomioon tuotteen helppokäyttöisyyden? Miten? 21b. During the development process, did you take the ease of use into consideration? How? [Questions about the Product related success factors] F. TP for difficult adopted 22a. Kuinka yrityksen/organisaation johto valmisteli projektia omaksumisajasta selviämiseen? 22b. How did the management prepare the project for the adoption time? 23a. Miten johdon sitoutuneisuus projektiin ilmeni? 23b. How was the commitment of management shown? 24a. Millä tavalla resurssien riittävyys oli organisoitu? 24b. How was resource ensuring organized? G. Lifecycle 25a. Millä tavalla tuotteen elinkaari oli huomioitu tuotekehitysprosessin aikana? 25b. How was the product’s life cycle taken into consideration during the development process? 26a. Tehtiinkö tuotekehitysprosessin aikana taloudellisia suunnitelmia tuotteen elinkaaren ajaksi? 26b. Was there any kind of economic planning for the life cycle period in the development phase? 27a. Tehtiinkö tuotekehitysprosessin aikana henkilöstösuunnittelua tuotteen elinkaaren ajaksi? 27b. Was there human resource planning for the life cycle period in development phase? H. Technological advantages 28a. Kuinka näette projektinne teknologisen kyvykkyyden menestystuotteen kehittämiseksi? 28b. How do you see the technological ability of your project to develop as a breakthrough product? 29a. Kuinka kuvailisitte kehitystiiminne teknologista etuasemaa? 29b. How would you describe the technological advantage of your development team? 30a. Mitä teknologisia etuja kehittämässänne tuotteessa on verrattuna muihin saatavilla oleviin ratkaisuihin? 30b. What technological advantages does your product have as compared to competitors or other available solutions?
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[Questions about the Management related success factors] I. Management support 31a. Mikä oli tärkeintä tukea projektillenne yrityksen johdolta? 31b. What was the most important support from the firm’s management for your project? 32a. Oliko projektinne käytössä riittävä määrä taloudellisia resursseja ja työntekijöitä? 32b. Did you have the needed financial and human resources for your project? J. Degree of funding 33a. Oliko yrityksenne strategiassa määritelty tuotekehitykseen käytettävää rahamäärää (esimerkiksi osuutta kokonaisbudjetista)? 33b. Was the degree of funding (e.g., the agreed percentage of the total budget) included in the firm’s strategy? How much was that share? 34a. Oliko tuotekehitysprojektinne priorisoitu keskenään taloudelliselta kannalta katsottuna? 34b. Was the development project prioritized from an economic point of view? 35a. Kuinka projektin rahoitusta seurattiin kehitysprosessin aikana? 35b. How was the project funding monitored during the development process? [Questions about the Organization related success factors] K. Project team skills 36a. Kuinka kuvailisit kehitystiimin jäsenten kokemusta? 36b. How would you describe the experience of the development team members? 37a. Järjestettiinkö kehitysprosessin aikana tiimikoulutusta? Millaista? 37b. Was any kind of team training arranged during the development process? 38a. Kuinka kuvailisitte kehitystiimin jäsenten ammattitaitoa, kyvykkyyttä ja sitoutumista projektiin? 38b. How would you describe the development team members’ expertise and ability? 39a. Kuinka kuvailisitte kehitystiimin monitaitoisuutta? Oliko eri alojen ammattiosaaminen edustettuna? 39b. How would you describe the versatility of development team? Was the team crossfunctional? L. Networking 40a. Verkottuiko yrityksenne tai projektinne tuotekehitysprosessin aikana muiden toimijoiden kanssa (yritykset tai julkinen sektori, esimerkiksi tutkimuslaitokset)? 40b. Did your project network with the other organizations (firms or public sector e.g., research institutes)? 41a. Jos näin tehtiin, niin miksi? Mitä etuja siitä saavutettiin? 41b. If this was the case, why did you do that? What benefits were achieved?
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42a. Millä tavalla tai perusteella projektinne löysi tai valitsi yhteistyökumppaninsa? 42b. How did your project find or justify the network partners?
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Original Publications
Int. J. , Vol. x, No. x, xxxx
1
Key factors of successful technology push projects in the ICT context: A review of the literature Abstract: The technology push (TP) concept is considered an important competitive advantage for R&D-intensive companies trying to create breakthrough products. The prime objective of this study is to present a compact set of the key factors of TP projects in an information and communication technology (ICT) context. In addition, a theorybased conceptual framework is introduced which could be used in studies to clarify the key factors of individual TP projects or products in an ICT context. The TP key factors are related to market, product, management, and organisational themes. According to current knowledge, TP key factors are industry independent. Because development processes are risky and failure rates are high, especially in the case of TP projects, the recognised key factors are valuable knowledge for the management of developmentintensive firms. Keywords: New Product Development; Technology push; radical innovation; ICT; thematisation; key factors. Reference to this paper should be made as follows: Biographical notes:
1. Introduction Developing new and successful products to market is necessary for most companies (e.g., Balachandra and Friar, 1997; Cooper, 1994; Ernst, 2002). Because development processes are very risky and failure rates are high, it is obvious that the management of development-intensive firms must be interested in those factors that lead to successful innovations. Previous literature on New Product Development (NPD) has presented conflicting findings regarding two key concepts: technology push (TP) and market pull (MP) (e.g., Herstatt and Lettl, 2004; Samli and Weber, 2000). The TP school maintains that innovation is driven by science, whereas the MP school argues that the users’ needs are the key drivers of innovation (Chau and Tam, 2000). Most literature stresses that emphasis should be on MP (e.g. by Langrish et al., 1972; Myers and Marquis, 1969; Rothwell et al., 1974; Utterback, 1974). However, numerous successful TP products have been launched. Probably the most reputed TP innovator – or at least one of them – is the Apple company.
Copyright © 200x Inderscience Enterprises Ltd.
J. Sarja
“. . . But it was hard to explain what an iPad was . . . The first set of ads showed we didn’t know what we were doing.” “Some people say, ‘Give the customers what they want.’ but that’s not my approach. Our job is to figure out what they’re going to want before they do. I think Henry Ford once said, ‘If I’d asked customers what they wanted, they would have told me, ‘A faster horse!’’ People don’t know what they want until you show it to them. That’s why I never rely on market research. Our task is to read things that are not yet on the page.” Steve Jobs by Walter Isaacson (2011, pp. 529, 598) There are many similar kinds of examples. “We don't even know what it is yet. We don't know what it is. We don't know what it can be, we don't know what it will be, we know that it is cool.” Mark Zuckerberg’s character in the movie “The Social Network”. “As a software development company, you have to act as a filter. Not everything everyone suggests is the right answer. We consider all requests but the customer is not always right.” Jason Fried and David Heinemeier Hansson, 37signals. The discussions regarding whether TP or MP is more important are futile. There are plenty of success stories and even more failures related to both driving forces (e.g., Balachandra and Friar, 1997). The current literature does not judge either concept. Instead, the concepts are linked strongly to particular innovation types: TP to radical and MP to incremental innovations (e.g., Bishop and Magleby, 2004; Brem and Voigt, 2009; Herstatt and Lettl, 2004; Samli and Weber, 2000). There have been many studies clarifying the success factors of NPD. Many of the key studies have not attempted to distinguish between radical and incremental innovation. By not distinguishing these two innovation types, the success factors of TP products are not explicitly known (Samli and Weber, 2000). For instance, the meta-analysis by Ernst (2002) encompassing dozens of widely cited NPD studies, including Cooper and
Key factors of successful technology push projects in the ICT context: A review of the literature
Kleinschmidt’s almost 30 papers, handles different types of innovation as one broad category. General NPD research, which does not take innovation type into account, is mostly too universal for studies of the key factors of TP. Because of the quantity of NPD and innovation management research that exists, representing different levels, different scopes and some with conflicting findings, we need to define a manageable set of key factors for further research. As Siggelkow (2007) states: “Theories and models are always simplifications. If they were as complex as reality, they would not be useful”. Cusumano (2010) follows the same philosophy to some degree when speaking about his six principles of creating competitive advantage: “In reflecting on what I have learned, I concluded that a handful of principles – I have chosen six – appear to have been essential to the effective management . . . I have focused on principles supported by considerable theoretical and empirical research undertaken by a variety of scholars . . .”. The prime objective of this study is to present a compact set of the success factors of TP projects in an information and communication technology (ICT) context. The success factors of ICT companies’ TP projects are led by studying the research on success factors in three levels. There are only a few research works on success factors specific to TP. Samli and Weber (2000) have generated and tested eight hypotheses of factors leading to breakthroughs. Bishop and Magleby (2004) have categorised eight themes of TP development success factors in their literature review. It seems that there are only a small number of studies on TP key factors in an ICT context 1. Isaacs and Tang (1996) and Spivey et al. (1997) had the desired context in their technology transfer studies but those are too case-oriented for deriving universal key factors.
1 Definition of ICT context ICT (information and communications technology (or technologies)) is an umbrella term that covers all communication devices and applications, including computers and network hardware and software, mobile phones, various services and applications associated with them (e.g., videoconferencing) but also more mature applications, such as radio and television (Asabere, 2012). We have used a narrower definition of ICT in this study by limiting it to computers, mobile phones and network application industries, including both hardware devices and software systems.
J. Sarja
The TP concept is considered an important competitive advantage for R&D-intensive companies trying to create breakthrough products (Herstatt and Lettl, 2004; Samli and Weber, 2000). This paper introduces a theorybased conceptual framework which could be used in studies to clarify the success factors of separate TP projects or products in an ICT context. This has been done by reviewing research on success factors in three levels: NPD, TP and TP in an ICT context. The weight is in TP success factor research because we concluded that the success factors of TP products are industry independent. The first level is general NPD research. By the epithet general, we mean NPD studies without any limitations of innovation drivers, innovation types, or industry. There are countless works in the literature about success factors in this level and it has been a significant research target during the past four decades (e.g., Balachandra and Friar, 1997; Ernst, 2002). The second level is the success factor research limited to TP products. When we discuss technology push, or the TP concept, we are not limiting it to any specific industry. The quantity of the literature at this level is more manageable (e.g., Bishop and Magleby, 2004). It is notable that the focus of NPD research has changed during the decades and it is clear that the MP models have had more attention from researchers and practitioners. However, MP projects are not within the scope of this study and therefore they are ignored. The third level is the literature on success factor research for TP projects limited to an ICT context. Even though the ICT industry is defined as one of the General Purpose Technology (GPT) industries (e.g., David and Wright, 1999), there are only a few ICT-focused works on success factor research. For example, only two out of ten TP studies in meta-analysis by Bishop and Magleby (2004) are solely in an ICT context. The extent of the NPD success factor research is presented in Table 1. MP research is not within scope of this study and it is marked with a grey background.
Key factors of successful technology push projects in the ICT context: A review of the literature Table 1 Level 1. NPD
Extent Countless
(2. MP products)
Multitude
2. TP products
Several
3. TP products in ICT context
Few
Model expressions “The literature discussing success in product innovation is vast” (Balachandra and Friar, 1997). “NPD research has retained a high level of popularity over the last 30 years” (Ernst, 2002). “Because of the numerous works available on this topic, a fact expressed in the many publications of review articles and meta-analyses” (Ernst, 2002). “Much of these new product research efforts have made no attempt to distinguish between simple product line extensions and breakthroughs” (Samli and Weber, 2000). “Both MP and TP models have formally existed since the 1960s though MP models have clearly had greater attention from researchers and practitioners” (Bishop and Magleby, 2004). “A large and rapidly growing literature on new product development [answers these questions] for the more incremental forms of innovation. But discontinuous innovation is very different in character,…” (Lynn et al., 1996). “Several researchers and practitioners have identified factors that are associated or correlated with TP product development resulting in successful products” (Bishop and Magleby, 2004). Only two out of ten TP studies analysed by Bishop and Magleby (2004) are solely in an ICT context (The author’s design).
Table 1. Extent of NPD key factor research at different levels
Because numerous research works exist on this topic, we focused on metaanalyses. Meta-analyses give broader outcomes of the topic. Chidamber and Kon (1994) state that a meta-analysis is a critical overview of several different studies and that the results of these studies are integrated and the generalisability of the findings is investigated. Meta-analyses give more information because of the greater availability of empirical source material. We were able to examine meta-analysis-type papers on both NPD (Balachandra and Friar, 1997; Ernst, 2002) and TP (Samli and Weber, 2002; Bishop and Magleby, 2004) levels. Currently in the third level, TP research in an ICT context, there are no meta-analyses available. In order to obtain a clearer understanding of the success factors, we started with identical categorisation methods to Balachandra and Friar (1997). The first named mode is a variant of the method used in marketing strategy studies to structure information (Aaker, 1992). The defined categories are market, technology, environment and organisation [related to]. The key factors in the NPD level are classified into these categories.
J. Sarja
However, after screening the most significant key factors, Balachandra and Friar (1997) realised that there were no factors related to technology and only one related to environment. Also Cooper (1979) found environmental factors to be unimportant. Therefore, we needed to revise the categorisation in order to derive factor sets that were more consistent. At the TP level, we studied the key factor set and found the natural common themes for the revised categories: market, product, management and organisation. The prime objective of this study is to present a compact set of the success factors of TP projects in an ICT context. With this in mind, we have first introduced the TP and MP concepts, innovation types and their connections with each other. Next, we introduce how we derived the compact set of TP key factors in an ICT context. Finally, the TP key factor set is discussed. 2. Innovation drivers, innovation types and key factors The core task for most NPD-intensive organisations is to generate and commercialise new products and services; however, this is a complex and difficult task. Most new products fail, that is, they do not meet their commercial targets (e.g., Balachandra and Friar, 1997). A turbulent environment with ever-shortening development-cycle times and a rapidly changing and increasingly competitive market cause these challenges (Herstatt and Lettl, 2004). Because NPD is the backbone of many industries, it is obvious that it is of significant interest to multidisciplinary research. The quantity of NPD research during recent decades has been tremendous (e.g., Balachandra and Friar, 1997; Ernst, 2002). The objective of these research works has been, almost without exception, to identify the success factors of new products. The impulse for the development of a new product comes either from customer needs (MP), or internal or external research (TP). 2.1 Technology push and market pull innovation drivers TP (Schumpeter, 1939) and MP (Schmookler, 1962) are the basic concepts for the driving forces behind innovations. There are a few synonyms in the literature for the concepts of technology push (e.g., science push, discovery push), and market pull (e.g., demand pull, need pull). The concept of MP suggests that market demand is the primary driver of innovation. In the concept of TP, the driving force for innovation is
Key factors of successful technology push projects in the ICT context: A review of the literature
internal or external research and the goal is to develop new technology for commercial use. Two schools of thought have debated which the most advisable approach is. Traditionally, empirical research has been concerned with the question of how these approaches influence the success of innovation (Herstatt and Lettl, 2004). Chidamber and Kon (1994) suggest that confrontation between the two approaches is due to different research objectives, definitions and models. Differences in problem statement and research constructs may also cause incongruity in research findings. Chidamber and Kon (1994) found that innovation research could be done at different levels – firm project, single innovation, industry, or even at a national level. A result found at a certain level is often inconsistent with results discovered at other levels. The four significant key studies of each school, most often cited in the literature, are (Chidamber and Kon, 1994): Technology push: Mowery and Rosenberg (1979) Freeman (1982) Casey (1977) Pavitt (1971) Market Pull: Project SAPPHO (1974) by Rothwell et al. Myers and Marquis (1969) Langrish et al. (1972) Utterback (1974) A comparison between the characteristics of innovation drivers is presented in Table 2. Table 2 Attribute Technology uncertainty R&D expense R&D duration Time to market Innovation process Market-related uncertainty R&D customer integration
Technology push High High Long Unknown “Probe and learn” type High Difficult
Market pull Low Low Short Known “Stage-gate” type Low Easy
J. Sarja Customer experience Customer education Market research type Need for changing customer behaviour
None present Usually necessary Qualitative “exploratory” research Extensive
Present Not necessary Quantitative conventional market research Minimal
Table 2. Innovation driver comparison (Gerpott, 2005; Herstatt and Lettl,
2004) Herstatt and Lettl (2004) explain that the degree, or newness, of innovation influences the development investments of both time and money, to the certainty level of technology and market. Lynn et al. (1996) state that the certainty level of technology and market causes different development processes: experimental probe-and-learn-type in TP cases and confirming stage-gate-type in MP cases. The knowledge of the needs of the market is different for both drivers. The TP strategy represents future markets that are difficult to predict and the MP strategy represents the current market situation. Therefore, the market research methods employed are also different: exploratory qualitative for TP and conventional quantitative (e.g., surveys) for MP (e.g., Herstatt and Lettl, 2004). The TP concept is traditionally linked with radical innovation, whereas MP is linked with incremental innovation (e.g., Brem and Voigt, 2009; Gerpott, 2005; Herstatt and Lettl, 2004). Therefore, it can be said that the more radical the innovation, the more the customer behaviour must change in order to adopt the innovation (Schiffman and Kanuk, 1997). Integrated models Even though some firms may be on the right track by focusing only on TP or MP, some researchers (e.g. Brem and Voigt, 2009) suggest that firms should not focus on a one-sided innovation strategy in the long term. The strategy decisions should be made case by case, or, preferably, using a combination of both strategies (e.g., Freeman, 1982; Munro and Noori, 1988; Ulrich and Eppinger, 2008; Zmud, 1984). Many researchers (e.g., Herstatt and Lettl, 2009; Souder, 1989) emphasise that innovation usually consists of hybrids of both concepts. Freeman (1982) found that the ability to connect technical and market opportunities is a success factor of innovation. The weight has been in the marketrelated activities in TP projects (e.g., Herstatt and Lettl, 2009). Ulrich and Eppinger (2008) have defined the known generic product development
Key factors of successful technology push projects in the ICT context: A review of the literature
process, which follows somewhat the MP process concept. They simplify the TP thought by adding technology-market matching to the first (out of six) phase (planning) of the [market pull] process. Even recent NPD literature does not present a black and white case in the TP-MP debate, leaving some space for interpretation in the case level (Herstatt and Lettl, 2004) and giving a change for combining both strategies. As mentioned before, many successful firms in the market adhere to the TP approach, either intentionally or accidentally. Two great examples in different scales are Apple (Isaacson, 2011), who did not do market research, and 37signals (Sarja, 2012), who defend their stance of not listening to customers in the development phase. As stated before, the TP strategy dominates radical innovation and MP dominates incremental innovation. 2.2 Radical and incremental innovations Innovation is generally defined as a new technology or combination of technologies that offer valuable benefits to the user. The difference between radical and incremental innovation is the degree of novelty. Radical innovation involves the development of significantly new technologies or market ideas previously unknown, or that require remarkable changes to what currently exists in the market. Incremental innovation is an extension of current products or existing processes (e.g., McDermott and O’Connor, 2002). Even though the definition of radical innovation varies in the literature (e.g., Green et al., 1995; McDermott and O’Connor, 2002), one valid and measurable definition by Green et al. (1995) incorporates four dimensions: technological uncertainty, technical inexperience, business inexperience and technology cost. Many researchers also add the change dimensions: the change of customer behaviour (e.g., Samli and Weber, 2000) and the change of the existing market (e.g., McDermott and O’Connor, 2002). As radical innovation is a consequence of TP development strategy and incremental innovation is a consequence of MP strategy, the characteristics of both types are identical with development strategies (see Table 2). By collating and summarising the characteristics, it is clear that the development of radical projects has higher risks but also higher profit expectations (e.g., Christensen, 1997; Samli and Weber, 2000). The radicalness of innovation projects is a fundamental aspect, which has been referred to and examined under many different labels (Green et al.,
J. Sarja
1995). The most well-known synonyms of the concepts are presented in Table 3.
Key factors of successful technology push projects in the ICT context: A review of the literature
Table 3 Radical types Discontinuous Breakthrough Revolutionary Pioneering New-to-the-world Discovery push Original
Incremental types Continuous Line extension Evolutionary Routine Extension Modifying Adapted
Table 3. Synonyms of innovation types
Successful radical innovations are exceptional compared with incremental innovations, but two aspects make it an interesting research topic. If it succeeds, it is a competitive advantage for the firm (e.g., Lynn et al. 1996; Lynn and Reilly, 2002) and incremental innovation would not exist without radical innovation, because the former always follows the latter (Abernathy and Utterback, 1978). 2.3 NPD key factor research New product development and commercialisation of innovation has been an important research topic for decades, because it is a core task for development-intensive organisations (e.g., Balachandra and Friar, 1997; Ernst, 2002). Because of rapidly developing technologies, stiff competition and shifting markets, it is also a very complex and difficult process (Cooper, 1994). What we mean here by NPD key factor research is a literature of general level development activities without distinguishing the innovation drivers and innovation types. The framework of general NPD key factor research is illustrated in Figure 1.
J. Sarja
Figure 1. The framework of NPD key factor research
2.3.1 NPD key factors by landmarks We have chosen two NPD-related landmark papers for closer examination: Ernst (2002) and Balachandra and Friar (1997). These NPDrelated papers are clearly focused on research of the success factors. Both papers are meta-analyses in nature, giving broader outcomes of the topic. They are acknowledged and widely cited within a large range of source material, including elementary studies of NPD. Ernst Ernst has reviewed dozens of NPD-related papers, including Cooper and Kleinschmidt’s 28 papers. The key factor in the categorisation mode used by Ernst is that originally used by Cooper and Kleinschmidt (1995). The defined categories are NPD process, organisation, culture, [senior] management commitment and strategy. The NPD process category is universal by nature and is also slightly misleading. It does not take a stand for a development process itself. Most factors sorted into this category are marketing related: the continuous commercial assessment during all phases of the NPD process, the NPD process orienting to market needs, the distinguishing between market orientation and customer integration into NPD, and the quality of planning
Key factors of successful technology push projects in the ICT context: A review of the literature
before the development phase. The individual aspects of the organisation category are explicit: cross-functional project team members; strong, responsible and committed team leaders; responsible and committed project team members; intensive internal communication during the project, and, finally, the correct form of project organisation. The culture category refers to the atmosphere of innovation within the company. The objective is to create systematically an innovation-friendly and entrepreneurial climate within the firm. Enabling work with their own and other unofficial projects and enabling the realisation of creative ideas can be a way to achieve that objective. The role and commitment of senior management mostly addresses the question of adequate resource allocation for the project. According to Ernst, new product strategy has been barely examined and it requires further research. The project must be defined and the project goals must be clearly communicated. The project must have a strategic focus, which gives overall direction to the individual NPD projects and it must be a part of a long-term NP portfolio. Balachandra and Friar Balachandra and Friar reviewed more than 60 papers in the fields of R&D projects and product innovation. The authors categorised the found factors according to the method used in marketing strategy studies (Aaker, 1992). The categories are market, technology, environment and organisation. The original key factor list identified by the examined material was long, totalling 72 factors. The final 14 factors chosen were those cited by four or more studies. This selection method omitted single and case-related factors. The noteworthy result is that the selected categorisation mode was not perfectly suitable after screening the factors, because there was no factor related to technology and only one related to the environment. Summary The findings of landmark meta-analyses (MA) by Ernst 2002 (E) and Balachandra and Friar 1997 (BF) are submitted in Table 4. Most of the key factors found by the authors are organisation related and few of them are market related. It can be seen that the aspect of these meta-analyses is somewhat different. Ernst (2002) settled on finding success factors at the organisational level, whereas Balachandra and Friar also took account of external factors. The same principle goes for the original categories by Aaker (1992) and by Cooper and Kleinschmidt (1995). It can be said that organisational-level factors are influenced by the organisation’s own
J. Sarja
management but that the external factors are partly given. Therefore, all factor categories used by Ernst (2002) can be included in Balachandra and Friar’s organisation category .
Market related Probability of tech. success
MA¹
Technology related
BF²
MA
Environment related Availability of raw materials
MA BF
Organisation related High level mgmt. support
MA BF,E³
Resource allocation Market existence
BF
Emphasise marketing
BF
Need to lower cost
BF
R&D process wellplanned
BF,E
Competitive environment
BF
Marketing & tech. are strengths/cross functional team
BF, E
Timing
BF
Commercial assessment, create market interphase, customer integration, process orienteering to market needs Training & experience of staff
BF, E
Project staff commitment
BF,E
Team leader capability and commitment
E
Tech. strategy tied to business strategy
BF,E
Project definition, strategic focus, NP portfolio
E
Internal communication
E
Innovation-friendly climate
E
Entrepreneurial climate
E
Form of the project organisation
E
¹ meta-analyses ² Author: Balachandra and Friar (1997)
BF
Key factors of successful technology push projects in the ICT context: A review of the literature ³ Author: Ernst (2002)
Table 4 Table 4. NPD key factors
It can be concluded that the findings of the NPD literature, without distinguishing the innovation driver types, are in most cases organisationand process-related and do not observe the key factors related to project outcome, e.g. technology or product. The impetus for all NPD processes comes from TP or MP innovation drivers (Brem and Voigt, 2009; Herstatt and Lettl, 2004). The focus of this study is on technology push research.
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3. The key factors of technology push projects In the NPD literature, for example, the widely cited works of Cooper (1979–1994), Cooper and Kleinschmidt (1986–1996) and the landmark papers of Balachandra and Friar (1997) and Ernst (2002), no attempt has been made to distinguish between radical and incremental products, or to acknowledge that the emphasis has been on MP projects. The number of studies on success factors related to TP projects is limited. We have chosen two meta-analyses landmark papers for closer examination: Bishop and Magleby (2004) and Samli and Weber (2000). Figure 2 illustrates the framework limited to key factor research of TP products.
Figure 2. The framework of TP products key factor research
These two landmark papers were chosen for several reasons. First, they are focused solely on TP projects. Secondly, the perspective of both papers is clearly to trawl success factors. Thus, the focus of the selected papers is very similar to ours. The only difference is that the selected papers are not limited to a certain industry, whereas we consider the ICT
Key factors of successful technology push projects in the ICT context: A review of the literature
context only. Both papers are wide-ranging and cover several research targets. Samli and Weber researched 30 separate long life cycle radical product cases and Bishop and Magleby reviewed 10 different level papers concerning the success factors of TP products. Finally, both papers are relatively new in this topic area. The authors of both papers have ranked their findings according to relative importance by using justified metrics. These findings are based on specific cases and in different contexts; thus it is clear that their findings are comparable only within the meta-analysis but not between the different meta-analyses. Bishop and Magleby researched the evolution of TP models for further research. They also studied the success factors of TP-developed products and thematised them into eight categories for further TP model research purposes. They studied 10 separate sources of differing natures, representing different levels of studies. The sources are from the period 1987 (Paul) to 2003 (Himmelfarb). The meta-analysis consists of:
Five journal articles. One out of five articles is poor according to today’s standards. Its length is only two pages, has no quotes and does not reveal how the results and conclusions are achieved.
One article published only on the Internet, which no longer exists.
One panel discussion note (linked with a journal article by the same authors).
Three business books.
The varying level of sources over a long period confirms the understanding that the quantity of TP-focused key factor research is limited. From our perspective, it is notable that only two studies in this meta-analysis were wholly within the ICT context. Samli and Weber researched 29 separate long life cycle radical product cases. They make a clear distinction between incremental and radical innovation research and they criticised other NPD research for not distinguishing the innovation types but keeping them as one broad new product category. The authors chose 30 long life cycle (over 10 years) products from the breakthrough innovation list identified by the Business Week magazine (one company did not take part in the study). They tested their hypotheses by interviewing the marketing division staff of the organisations behind the chosen products. Six out of eight hypotheses were supported regarding the success factors of radical innovation. From our perspective, it is notable that none of researched cases was within our narrower, limited ICT context (see our definition of ICT context).
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The environments of the landmark studies are presented in Figure 3.
Figure 3. The landmark TP meta-analyses
3.1 TP key factors by landmarks Bishop and Magleby Bishop and Magleby state that each of the papers they studied was written by authors of different backgrounds and was aimed for different audiences. The backgrounds of the authors varied from engineering, marketing, consulting and R&D management. The background of the audience ranged from practitioners to researchers. The same principle works between both landmark papers. Bishop and Magleby divided the success factors they found into eight categories. According to the authors, the success factors are as follows, arranged in order of significance: 1. There is a focus on customer/end user needs Customer or end user needs were considered during the development of the product. 2. Internal/external networks were used Networks internal and/or external to the company were used during product development, which were beyond interacting with customers and end users.
Key factors of successful technology push projects in the ICT context: A review of the literature
3. There is management support There existed support from the management either directly or through methods, such that management generally have control over aspects such as the organisation model. 4.
The development team is dynamic, motivated and/or talented
There was a high level of expertise, motivation and/or ability within the product development team. 5. A combination of MP and TP is used Both MP and TP methods were used in the same product development process beyond simply including customer and end user needs with TP elements. 6. The market is developed during or directly after product development The market was developed, instructed or prepared simultaneously with development of the product. 7. The technology offers clear advantages The product offers a clear advantage over other, similar products, directly because that technology was the basis for the development. 8. Alternatives were examined carefully Alternative technologies, products and markets were examined carefully by the product developers during development. The authors state that because of the diverse audiences and researchers, the success factors are written using terminology that is inconsistent. Perhaps because of this, the developed factors are intangible by nature and somewhat difficult to measure, define and even distinguish from each other (e.g. factors 1, 5 and 6). For instance, roughly speaking, if we are using a combination of TP and MP, we are focusing on customers and we are developing for the market. Samli and Weber
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Samli and Weber constructed a series of eight hypotheses for testing the relevance of their universal model of breakthrough development. Six out of eight hypotheses were supported. The hypotheses are introduced in order of significance (the pair H2 & H3 is equivalent). 1. Technological push results in new products that are not readily adopted. The development of technology push products is a long-term action. From the firm’s point of view, it means a commitment to technology push projects in the long run. 2. The degree to which a new product is a breakthrough will increase the length of time before the product is adopted by the market, i.e. technophobia. The novelty of technology push products affect the adoption time by the market. In reference to the target of our study, we see this factor as very close to the previous one, technophobia, such that we discuss them as one factor. 3. The greater the percentage expenditures on new product development and related research, the greater the number of new successful products introduced. More than 62% of the respondents to the landmark papers spent over 20% of their total budget developing new products. 4. The level of a breakthrough has a direct correlation with the longevity of the product. Even though technology push products are not accepted quickly by the market, they display longer life cycles than minor product developments or line extensions. 5. Technophobia This factor is combined with the degree of novelty factor (no. 2). 6. Products that fill an unrecognised need will have greater longevity than those that do not. If the firm has no knowledge of the market and it is proceeding completely with an internal technology push, it is not likely to be successful.
Key factors of successful technology push projects in the ICT context: A review of the literature
The order of significance is calculated in a different way in each metaanalysis. Therefore, the order is valid only inside the same meta-analysis and it is not comparable between the meta-analyses. In order to simplify the factors of both papers and to enable links between them, we have thematised all the findings according to common factors. This was done by thematising the found key factors. Thematisation enables a comparison of the occurrence of certain themes (Eskola and Suoranta, 1998). We compiled four different categories: market, product, management and organisation [related] factors. The different aspects of management- and organisation-related key factors existed so clearly that we distinguished them as separate categories. We also shortened the findings for simpler representation. The summary of TP key factors is illustrated in Table 5. Table 5 Market related
MA¹
Product related
MA
Management related
MA
Focus on customer needs
BM²
TP for difficult adopted
SW
Management support
BM
MP methods used
BM
Life cycle
SW
Degree of funding
SW
Market development
BM
Fill an unrecognised need
SW
Alternative study
BM
Technological advantages
SW
Adoption time/ SW³ technophobia ¹ meta-analyses ² Author: Bishop and Magleby (2004) ³ Author: Samli and Weber (2000)
Organisation related Networking
MA
Project team skills
BM
BM
Table 5. TP key factors
3.2 TP research in ICT context The ICT context in our study is limited to hardware and software products in computer, mobile phone and network applications industries only. Only two studies out of the ten in the meta-analysis by Bishop and Magleby were solely within the ICT context (Isaacs and Tang, 1996 and Spivey et al., 1997); moreover, one study had one ICT case study out of four within the desired context (Lynn et al., 1996). The other landmark paper by Samli and Weber had no cases within an ICT context. They categorised four researched radical products as “Telecomm.” Applications, but those
BM
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products do not fit our definition for ICT (fibre optic phones, a book-size video camera and two different hi-fi TVs). The position of the ICT-related TP products within the entire NPD field is illustrated in Figure 4.
Figure 4. The framework of ICT-related TP products key factor research
We have gathered the success factors within an ICT context categorised by Bishop and Magleby. The aforementioned two ICT-related sources of the study give the following factors: 1.
Internal/external networks are used
2. There is management support 3. There is a focus on customers/end users 4. The development team is dynamic, motivated and/or talented 5. The market is developed during or directly after product development 6. The technology offers clear advantages Limiting the context from general TP projects to ICT projects causes a change in factor category ranking. Factors 1 and 2 are referenced by both
Key factors of successful technology push projects in the ICT context: A review of the literature
studies and factors 3–6 are referenced by one or the other. The order of the remaining factors is according to the original meta-analysis. Table 6 represents the factors according to the familiar categories. Some conflicting issues led us to constitute a premise. First, the quantity of source material is too slight in terms of our target – a concrete set of the success factors. The discovered factors are intangible by nature for deriving concrete factors. Paradoxically, the findings of these two studies within an ICT context have already covered six out of the eight factor categories, which were defined without the industry limitation when all ten studies in the meta-analysis were investigated. Comparing general TP research and TP research limited to an ICT context, we can conclude a premise: The success factors of TP products are industry independent. Cusumano (2010) made same kind of assumption with his Six Principles [of effective management of strategy and innovation]: “What I offer is a selective list, mainly from the automobile, computer software, telecommunications, consumer electronics, and Internet service industries. But, because of their generality, I am convinced that these principles provide essential lessons for managers in nearly any industry.” In practice, the premise means that we can constitute the list of the success factors of ICT-related TP products with TP research in any industry. The industry independent key factor set of TP products was discussed in chapter 3.1. Table 6 Market related Focus on customer needs Market development
Product related Technological advantages
Management related Management support
Organisation related Networking Development team skills
Table 6. TP key factors limited to ICT industry by landmark study
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4. Discussion and conclusion As background information, we studied two meta-analyses. We found relatively long lists of NPD key factors. However, there are a few complications with those findings. Firstly, they are too universal by nature. They do not distinguish innovation drivers and/or innovation types; therefore, they are basically only good for general level hints on how to manage project-oriented organisations. On the other hand, the universality concerns the forms of factor expression. Most of the factors are ambiguous, more like categories (as Bishop and Magleby termed them). This, however, should not be confused with the upper categories (e.g., Market, Technology, Environment and Organisation by Aaker). In order to obtain the exact key factors, the found factors should be transcribed to exact pieces. For example, the factor named “emphasise marketing” can really mean many specific things in practice. Secondly, almost all found key factors belong to market- or organisation-related categories. Certainly, no one in a development-intensive business challenges the importance of market needs and the skills and enthusiasm of the organisations. However, we think there must be some technological- or product-related factors that are important when trying to find out why some products are successful. Taking account of the universality of the found NPD key factors and missing product-related factors, we conclude that before starting to develop a research pushed product, a firm should ensure that the basics – the NPD level key factors – are taken into account. After limiting key factor studies initially to TP projects only and then later to TP projects within the ICT industry, we realised that in today’s literature, the key factors of TP projects are industry independent. There might be some industry-related factors but the current research does not provide answers to that assumption. After ICT industry limitations, we needed to turn back to the general TP level. We found that only one of the studied meta-analyses, which was that of Bishop and Magleby, had two ICT-related examples. Paradoxically, even though the data source was clearly too small, the findings were almost the same as those without the industry limitation. We also noticed that there was no reason to omit the remaining findings of the mentioned landmark study and that the same applies to the other studied landmark study by Samli and Weber. All found key factors could also apply to ICT projects. We also obtained some
Key factors of successful technology push projects in the ICT context: A review of the literature
support for our premise from other independent NPD literature, e.g. Cusumano (2010), that the key factors are industry independent. This research-feedback from TP projects in the ICT industry to industry independent TP key factor research is illustrated in Figure 5.
Figure 5. Findings after the premise
Therefore, regardless of the ICT context we wanted to study in this work, we examine the general TP key factors in closer detail (represented in Table 5). As practically all NPD-related literature, regardless of perspective, emphasises the market-related factors, so too does TP research. We categorised five relatively broad key factors found by landmark works under the theme of market. The factors named “market development” and “focus on customer needs” are also found by NPD-level literature, restated in slightly different wording. The factor “MP methods used” is more or less pointless; we think it covers roughly all market-related actions, issues and factors and it is difficult to see it as an individual success factor. The factors “alternative study” and “technophobia” are obviously key factors for research pushed new products. It is important to compare the alternatives, question individual output and to outline the real benefits of the innovation. The novelty of TP products is always at a higher level and the adoption time is longer, whereupon the usability must be studied carefully in order to avoid technophobia. As TP projects are run comprehensively around the developed product, the TP-level literature naturally takes into account the product-related key factors, unlike general NPD research. The factor “technological
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advantages”, together with the market-related factors above, obtains support from the NPD level (“marketing and technology are strengths”). The other product-related factors are strongly time-centred: the duration of adoption time and the length of the life cycle. Longer adoption times, from the firm’s perspective, mean long-term commitment, especially regarding resources. However, in the case of product success, the expected life cycle is longer. A contextually different product-related key factor suggests the product must “fill an unrecognised need”. It is a matter of opinion as to which category to position it in (market or product). Because it is somewhat unpredictable, we see it more as a consequence of development work than as a clear key factor. The management- and organisation-related factors are approximately the same as in the general NPD literature. The main points are resource ensuring, networking and a multi-talented development team. In conclusion, the key factors of TP projects emphasise keeping marketing activities as a part of the development process. Thematisation is not a black and white process and the divisions between the themes are very thin lines. The current literature does not provide exact key factors, but instead, rather descriptive, vague topics. In order to obtain exact factors, all findings should divide smaller precise pieces and test them in case studies. This study may show the direction of key factors and, for instance, the survey instruments for testing TP project key factors (in ICT or other contexts) can be led from these elements. Acknowledgements References Aaker, D.A. (1992) Strategic market management, Wiley, New York, NY. Abernathy, W.J. and Utterback, J.M. (1978) ‘Patterns of industrial innovation’, Technology Review, Vol. 80 No. 7, pp.40–47. Asabere, N.Y. (2012) ‘Towards a perspective of information and communication technology (ICT) in education: migrating from electronic learning (E-learning) to mobile learning (M-learning)’, International Journal of Information and Communication Technology Research, Vol. 2 No. 8, pp.646–649. Balachandra, R. and Friar, J.H. (1997) ‘Factors for success in R&D projects and new product innovation: a contextual framework’, IEEE Transactions on Engineering Management, Vol. 44 No. 3, pp.276–287.
Key factors of successful technology push projects in the ICT context: A review of the literature
Bishop, G.L. and Magleby, S.P. (2004) ‘A review of technology push product development models and processes’, Proceedings of ASME DECT ’04, ASME, New York, NY, pp.383–392. Brem, A., Voigt, K.-I. (2009) ‘Integration of market pull and technology push in the corporate front end and innovation management—insights from the German software industry’, Technovation, Vol. 29 No. 5, pp.351–367. Casey, J.P. (1977) ‘High fructose corn syrup – a case history of innovation’. Starch, Vol. 29 No. 6, pp.27–33. Chau, P.Y.K. and Tam, K.Y. (2000) ‘Organizational adoption of open systems: a ‘technology-push, need-pull’ perspective’, Information & Management, Vol. 37 No. 5, pp.229–239. Chidamber, S. and Kon, H. (1994) ‘A research retrospective of innovation inception and success: the technology-push, demand-pull question’, International Journal of Technology Management, Vol. 9 No. 1, pp.94– 112. Christensen, C. (1997) The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, Harvard Business School Press, Boston, MA. Cooper, R.G. (1979) ‘Identifying industrial new product success: Project NewProd’, Industrial Marketing Management, Vol. 8 No. 2, pp.124– 135. Cooper, R.G. (1994) ‘New products: the factors that drive success’, International Marketing Review, Vol. 11 No. 1, pp.60–76. Cooper, R.G. and Kleinschmidt, E.J. (1995) ‘Benchmarking the firm’s critical success factors in new product development’, Journal of Product Innovation Management, Vol. 12 No. 5, pp.374–391. Cusumano, M.A. (2010) Staying Power: Six Enduring Principles for Managing Strategy and Innovation in an Uncertain World (Lessons from Microsoft, Apple, Intel, Google, Toyota and More), Oxford University Press, Oxford, UK. David, P.A. and Wright, G. (1999) ‘General purpose technologies and surges in productivity: historical reflections on the future of the ICT revolution’, Proceedings of the Symposium on Economic Challenges of the 21st Century in Historical Perspective, Oxford University Press, Oxford, UK. Ernst, H. (2002) ‘Success factors of new product development: a review of the empirical literature’, International Journal of Management Reviews, Vol. 4 No. 1, pp.1–40. Eskola, J. and Suoranta, J. (1998) Johdatus laadulliseen tutkimukseen, Tampere: Vastapaino (in Finnish).
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Freeman, C. (1982) ‘Schumpeter or Schmookler?’, in Freeman, C., Clark, J. and Soete, L. (Eds.), Unemployment and Technical Innovation. Pinter, London, UK. Gerpott, T.J. (2005) Strategisches technologie und innovationsmanagement, Schäffer-Poeschel, Stuttgart, Germany (in German). Green, S.G., Gavin, M.B. and Aiman-Smith, L. (1995) ‘Assessing a multidimensional measure of radical technological innovation’, IEEE Transactions on Engineering Management, Vol. 42 No. 3, pp.203–214. Herstatt, C. and Lettl, C. (2004) ‘Management of ‘technology push’ development projects’, International Journal of Technology Management, Vol. 27 No. 2/3, pp.155–175. Himmelfarb, P. (2003) ‘Market pull vs. tech push’. [online] www.bizbasics.com (Accessed 12 October 2012). Isaacs, E.A. and Tang, J.C. (1996) ‘Technology transfer: so much research, so few good products’, Communications of the ACM, Vol. 39 No. 9, pp.23–25. Isaacson, W. (2011) Steve Jobs. Otava: Keuruu, Finland. Langrish, J., Gibbons, M., Evans, W.G. and Jevons, F.R. (1972) ‘Wealth of Knowledge: A Study of Innovation in Industry’, John Wiley & Sons, New York, NY. Lynn, G., Morone, J. and Paulson, A. (1996) ‘Marketing and discontinuous innovation: the probe and learn process’, California Management Review, Vol. 38 No. 3, pp.8–37. Lynn, G.S. and Reilly, R.R. (2002) Blockbusters – The Five Keys to Developing GREAT New Products, HarperBusiness, New York, NY. McDermott, C.M. and O’Connor, G.C. (2002). ‘Managing radical innovation: an overview of emergent strategy issues’, The Journal of Product Innovation Management, Vol. 19 No. 6, pp.424–438. Mowery, D. and Rosenberg, N. (1979) ‘The influence of market demand upon innovation: a critical review of some recent empirical studies’, Research Policy, Vol. 8 No. 2, pp.102–153. Munro, H. and Noori, H. (1988) ‘Measuring commitment to new manufacturing technology: integrating technological push and marketing pull concepts’, IEEE Transactions on Engineering Management, Vol. 35 No. 2, pp.63–70. Myers, S. and Marquis, D.G. (1969) Successful industrial innovation, National Science Foundation, Washington, DC. Paul, R.N. (1987) ‘Improving the new product development process – making technology push work!’, Journal of Business & Industrial Marketing, Vol. 2 No. 4, pp.59–61.
Key factors of successful technology push projects in the ICT context: A review of the literature
Pavitt, K. (1971) The conditions for success in technological innovation, OECD, Paris, France. Rothwell, R., Freeman, C., Horsley, A., Jervis, V.T.P., Robertson, A.B. and Townsend, J. (1974) ‘SAPPHO updated – project SAPPHO phase II’, Research Policy, Vol. 3 No. 3, pp.258–291. Samli, A.C. and Weber, J.A.E. (2000) ‘A theory of successful product breakthrough management: learning from success’, Journal of Product & Brand Management, Vol. 9 No. 1, pp.35–55. Sarja, J. (2012) ‘A review of the Getting Real software development approach’, The International Journal of Agile and Extreme Software Development, Vol. 1 No. 1, pp.78–94. Schiffman, L.G. and Kanuk, L.L. (1997) Consumer Behaviour, PrenticeHall, Upper Saddle River, NJ. Schmookler, J. (1962), ‘Economic sources of inventive activity’, in Rosenberg, N. (Ed.), The economics of technological change, Penguin Books, Harmondsworth, UK. Schumpeter, J.A. (1939) Business Cycles: A Theoretical, Historical and Statistical Analysis of the Capitalist Process, vol. 2, McGraw-Hill, New York, NY. Siggelkow, N. (2007) ‘Persuasion with case studies’, Academy of Management Journal, Vol. 50 No. 1, pp.20–24. Souder, W. E. (1989) ‘Improving productivity through technology push’, Research Technology Management, Vol. 32 No. 2, pp.19–25. Spivey, W.A., Munson, J.M., Nelson, M.A. and Dietrich, G.B. (1997) ‘Coordinating the technology transfer and transition of information technology: a phenomenological perspective’, IEEE Transactions on Engineering Management, Vol. 44 No. 4, pp.359–366. Ulrich, K.T. and Eppinger, S.D. (2008) Product Design and Development, McGraw-Hill/Irwin, New York, NY. Utterback, J.M. (1974) ‘Innovation in industry and the diffusion of technology’, Science, Vol. 183 No. 4125, pp.620–626.. Zmud, R.W. (1984) ‘An examination of ‘push-pull’ theory applied to process innovation in knowledge work’, Management Science, Vol. 30 No. 6, pp.727–738.
Explanatory definitions of technology push success factors
Manuscript Jari Sarja 7.7.2014
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Abstract The main task for most development-intensive organisations is to create, develop and commercialize new products and services. Because development processes are risky and failure rates are high, especially in the case of technology pushed projects, unambiguous success factors are valuable knowledge for the management of development-intensive firms. New product development and innovation literature has presented many success factors for developed products, but, unfortunately, many of them are nebulous in nature. The aim of this paper is to clarify what elements comprise the exact factors. After an extensive review and screening of the technology push success factor related literature, a total of 13 success factors were rationalized and transcribed according the previous literature. As a result, three separate keynotes were recognized, and the survey instrument framework was proposed. The practical relevance of this study is to help firm management to recognize the real actions needed to reduce product development risks and also to help scholars to focus on key issues when studying the key factors of breakthrough development cases.
Key words: Technology push, Success factor, New product development, Survey instrument
3
1.
Introduction
The main task for most NPD1 intensive organisations is to create, develop and commercialize new products and services. However, this is a complex and difficult task. NPD being the backbone of many industries, it is obvious that it is of considerable interest to multidisciplinary research. The quantity of NPD research during recent decades has been tremendous (e.g., Balachandra & Friar, 1997; Ernst, 2002). This research has, almost without exception, been aimed to identify the success factors of new products. The impulse for the development of a new product comes either from customer needs (MP2) or from internal or external research (TP3). According to the concept of MP, market demand is the main driver of innovation. The concept of TP suggests instead that the driver for innovation is internal or external research and that the target is to develop new technology for commercial purposes. Even recent NPD literature does not set a clear arrangement in the TP-MP debate; it leaves some space for interpretation at the case level (Herstatt & Lettl, 2004) and leaves a possibility to combine both of these strategies. Still, few successful firms in the market prefer the TP approach, either intentionally or accidentally. To give an example of companies in different scales that adhere to the TP approach, one can name Apple (Isaacson, 2011) and 37signals (Sarja, 2012). Apple did not do market researched, and 37signals defends their way of not listening to customers in the development phase. The TP strategy dominates radical innovation and MP dominates incremental innovation. Innovation is generally defined as a new technology or combination of technologies that offer valuable benefits to the users. The difference between radical and incremental innovation is the state of novelty. Radical innovation involves the development of considerable new technologies or market ideas previously unknown or that require remarkable changes to what currently exists in the market. Incremental innovation is an extension of current products or existing processes (e.g., McDermott & O’Connor, 2002). Even though the definition of radical innovation varies in the literature (e.g., Green et al., 1995; McDermott & O’Connor, 2002), one valid and measurable definition by Green et al. (1995) incorporates four dimensions: technological uncertainty, technical inexperience, business inexperience and technology cost. Many researchers have also added change dimensions: the change of customer behaviour (e.g., Samli & Weber, 2000) and the change of the existing market (e.g., McDermott & O’Connor, 2002). If these characteristics are collated, it is obvious that the development of radical projects has higher risks but also higher profit expectations (e.g., Christensen, 1997; Samli & Weber, 2000).
1
New product development Market pull 3 Technology push 2
4 Because development processes are risky and failure rates are high, especially in the case of TP projects, unambiguous success factors are valuable knowledge for the management of development-intensive firms. Sarja (2014) studied two meta-analyses for finding the success factors of TP projects in an ICT context. However, the author concluded that the TP success factors – according to the current research – are industry independent. We found that the 13 success factors (table 1) are not very exact; rather, they are descriptive vague topics. We see this issue as somewhat problematic; the success factors are too wide, or they may have many different meanings. Balachandra and Friar (1997) concluded the same confusion of NPD research previously. The research problem of this paper is to clarify what elements comprise the exact factors. The research subject is 13 success factors collected from the meta-analyses by Samli and Weber (2000) and Bishop and Magleby (2004). For rationalizing and transcribing the success factors, we searched related concepts from previous literature, including research papers and established books. In this paper, we introduce the proposed reasoning of the success factors. In addition, the survey instrument framework for TP case studies is proposed. At first, the thematized success factors (Sarja, 2014) are presented and transcribed and the framework of the survey instrument for case testing is introduced. Then, the findings are discussed and summarized in the last chapter. Table 1 Market related
MA¹
Product related
MA
Management related
MA
Focus on customer needs
BM²
TP for difficult adopted
SW
Management support
BM
MP methods used
BM
Life cycle
SW
Degree of funding
SW
Market development
BM
Fill an unrecognised need
SW
Alternative study
BM
Technological advantages
SW
Adoption time/ SW³ technophobia ¹ meta-analyses ² Author: Bishop & Magleby (2004) ³ Author: Samli & Weber (2000)
BM
Table 1. TP success factors (Sarja, 2014)
Organisation related Networking
MA
Project team skills
BM
BM
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2.
Specification of the TP success factors
The NPD and innovation literature have presented many success factors for developed products. Parts of these factors are comprehensible, but, unfortunately, many of them have conspicuous characteristics; they are nebulous in nature. Many times, they can be explained many ways. Balachandra and Friar (1997) concluded this previously, and, as an example, they underlined that the terms “emphasize marketing” and “support of top management” may take many different forms. The authors explain the factors that are considered so self-evident in many cases that no clear definitions are given, even though they may have different meanings. The same phenomenon applies to the previous study of Sarja (2014). As the author concludes, “The current literature does not provide exact key factors but instead, rather descriptive vague topics.” For rationalizing the success factors, we have divided them into smaller, precise pieces and proposed a reasoning of the factors.
2.1 Market related success factors MP methods used We see that MP thought is not a method but rather is an innovation driver approach (e.g., Herstatt & Lettl, 2004; Sarja 2014), and this key factor covers somewhat the next three market related success factors: a focus on customer needs, market development and alternative study. In addition, following the MP based generic development process introduced by Ulrich and Eppinger (2008), the MP approach will be taken into consideration. The general level description of the generic development process is illustrated in figure 1.
Figure 1. Generic development process (source: Ulrich & Eppinger, 2008) The generic development process describes the market-pull situation. The authors separate the TP and MP situations, explaining that, in the TP case, a firm begins with a new technology and tries to find an appropriate market; whereas, in the MP case, a firm begins development with a market opportunity and tries to satisfy market needs using whatever technologies are available. This separation is done by adding technologymarket matching to the first phase (planning) of the (market pull) process. In summary, it can be concluded that the development process itself should be the same regardless of the innovation driver (TP or MP). This premise is supported by numerous studies with different NPD perspectives, for example, marketing-R&D co-operations or TP-MP integrated models (e.g., Freeman, 1982; Zmud, 1984; Munro & Noori, 1988; Souder, 1989; Herstatt & Lettl, 2009). The framework of this thought is presented in figure 2.
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Figure 2. The framework of NPD success factor research (Sarja, 2014) Focus on customer needs Customer needs means basically that the customer solves some problem by purchasing a product (a good or service). Most literature about NPD, also TP-focused, stresses that customer needs must be identified at the beginning of the development process. For example, Ulrich and Eppinger (2008) examine preparatory customer related studies, including customer needs collection for the two first phases (0=planning, 1=concept development), in their generic development process. After articulating market opportunities and defining market segments in the planning phase, the needs of segmented customers (e.g., Kotler & Armstrong, 1987, pp. 203–224) in a target market should be identified in the concept development phase. The output of identifying customer needs is a constructed list of customer need statements, organized in hierarchical order with importance weightings. The five-step process for identifying customer needs is: 1. Gather raw data from customers 2. Interpret the raw data in terms of customer needs 3. Organize the needs into a hierarchy of primary, secondary and (if necessary) tertiary needs 4. Establish the relative importance of the needs 5. Reflect on the results and the process Market development The term market development has many statements. Thinking about the found success factor of a TP product, it is reasonable to adopt the commonly used Ansoff model (Figure 3). The Ansoff model describes firm growth strategy opportunities. It contains four growth options that are used based on product and market maturities.
Figure 3. The Ansoff model (Ansoff, 1957)
7 In the model, market development means a firm’s attempt to identify and develop new markets for current products. However, it does not apply to the new product context. Therefore, when we use the concept of market development in this paper, we actually mean the concepts of product development (new products for existing markets) and diversification (new products for new markets). Bishop and Magleby (2004) state that the market must be developed, instructed or prepared simultaneously with the development of a product (see Sarja, 2014). We agree with this view in terms of the definition of a target market by a development firm. Alternative study Alternative study regards a kind of sub-process in the concept development phase of the development process that is similar to customer needs identification. Time-wise these two processes will be actualized simultaneously. Ulrich and Eppinger (2008) state that the alternative product concept must be generated and evaluated in the concept development phase. There are numerous studies of competitor analysis in marketing literature (e.g., Chen, 1996; Peteraf & Bergen, 2002; 2003). We would like to note a slight difference between the concepts of alternative analysis and competitor analysis. Competitor analysis is a marketing related term concerning products, whereas alternative study (or analysis) concerns only new products, processes and methods (in the market). Because there is not a significant number of studies about alternative analysis, we make an assumption that alternative studies can be done with the same method as competitor analyses. A significant argument was found by Lewitt (1960). He stated that business should not be defined in terms of product types but in terms of customer needs to be served. This thought encourages management to study business and growth opportunities more broadly (Peteraf & Bergen, 2003). An example of this aspect is the electric car. The other brands are not the only competitors; other economical vehicles and even public transportation are also competitors. With a similar thought, Chen (1996) defined the framework for competitor analyses. It was based on two dimensions: market commonality and resource similarity. The framework maps three kinds of competitors, indirect (substitutes), direct and potential, depending on the degree of dimensions. The framework of competitor analysis is illustrated in figure 4.
Figure 4. The framework of competitor analysis (based on Chen, 1996; Bergen & Peteraf, 2002)
8 Adoption time, technophobia Adoption time is the space of time when the consumer adopts new products or ideas. The more dramatic a new product is, the longer the adoption time (e.g. Samli & Weber, 2000). There are many models to explain adoption (e.g., Mahajan & Wind, 1986; Mahajan et al., 1990; Sultan et al., 1990, Narayanan, 1992). Most models are based on the Bass (1969) model (Narayanan, 1992). There are many definitions for the noun technophobia, and the early definitions are from the PC era. Brosnan (1998) uses the most commonly cited definition of Jay (1981) in his landmark book about technophobia. Jay (1981) defines technophobia as the following: 1. A resistance to talking about computers or even thinking about computers 2. Fear or anxiety towards computers 3. Hostile or aggressive thoughts about computers Briefly, Brosnan (1998, p. 33) states that the overall concept of technophobia is a combination of computer anxiety and a negative attitude. In this study, we deal with the given definitions, but we expand the cause of technophobia from computers to any technology based new product. We see that these two concepts, adoption time and technophobia, have a clear linkage in the field of NPD research, particularly when speaking about technology pushed products. Many scholars and research communities are in step with us, for example when explaining that user acceptance has been a long-term issue in highly esteemed MIS4 research (Davis, 1989). Brosnan (1998, p. 171) and the HCI5 community (Davis, 1989) emphasize a commercial motivation for continued user-friendliness in hardware and software due to an attempt to appeal to technophobes. Different technology acceptance models support this thought; users must feel that an application is useful (perceived usefulness) and easy to use (perceived ease of use). The roots of acceptance models are multidisciplinary, from sociology and psychology to information system research (IS) (see e.g., Venkatesh et al., 2003). In NPD research, the most known and highly cited technology acceptance model is TAM (Davis, 1989) and its extensions, TAM 2 (Venkatesh & Davis, 2000), TAM 3 (Venkatesh & Bala, 2008) and the unified theory of acceptance and use of technology (UTAUT) (Venkatesh et al., 2003). Technology acceptance models explain why users adopt or do not adopt new applications and give tools to promote positive adoption. The weakness of the models is that they do not take into account the time of adoption.
2.2 Product related success factors TP for difficult adopted TP driven products typically take longer to be adopted by the majority of customers (see the categories of adopters by Rogers, 1962). The adoption time from the customer’s point of view and the natural resistance of users to new solutions is discussed above. This factor is the adoption time domain from the developers’ perspective. The longer
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Management Information Systems [Quarterly]
5
Human-computer interaction
9 the adoption time from a firm’s point of view, the longer the run commitment to a project, especially in terms of resources. This is one reason, which makes TP projects risky. If risk is controlled and a product succeeds, the expected life cycle is also longer. Life cycle Firms develop new products to get long-term profits (Griffin & Hauser, 1996). A good example of the expected longer life cycle of successful technology push (also called as breakthrough) products is a study of Samli and Weber (2000), where they examined successful breakthrough developers, in total, 130 firms with 143 products, which had been in the market for over a decade. Product life cycle means total product existence from raw material sourcing to manufacturing steps, usage and, finally, to discarding or recycling (e.g., Tseng & Chen, 2004). For the firm’s perspective, we widen this concept by including also the development phase. The basic idea behind the life cycle factor, from an idea until the end of a product’s life, is economic planning. Samli and Weber (2000) see life cycle reasoning as a financial and human resource issue. Fill an unrecognized need The importance of focusing on customer needs in the development phase is discussed above. In the ideal world, a radical or breakthrough product fills a need customers did not consider. However, proceeding totally with an internal technology push is a lottery game. Samli and Weber (2000) emphasize that a new product must fulfil at least a somewhat recognized need. Calantone and Li (1998) are in step, stating that if a company has no knowledge of the market, it is not likely to be successful. Technological advantages Technological advantage is a multilevel concept. Depending on the study, the aspect can vary from country level to firm or project level. At firm level, technological advantage represents a firm’s ability to develop technology pushed breakthrough products instead of just satisfying existing demand (Samli & Weber, 2000). At project (or product) level, technological advantage means the overall benefits of a product (compared to other similar products), which has been developed on the basis of technology. Cooper and Kleinschmidt (1995) found that the success factors may be different at firm level and project level. There are many reasons for this, but, generalizing, there can be many different projects with different degrees of investment within the same firm. This principle applies to any success factor, including technological advantage. In this context we are primarily interested in technological advantages at project level and, secondarily, at firm level.
2.3 Management related success factors Management support Since management is too large a complex of issues to divide in this context, we share Ernst’s (2002) view that the most important support from management is to ensure needed resources. Ernst also emphasizes that non-material support may be nothing more
10 than lip-service. Samli and Weber (2000) explain that management must have adequate financial and human resources for generating breakthrough products. Degree of funding The degree of funding is an important part of a firm’s NPD strategy. In a study of Samli and Weber (2000), a generous majority of researched firms spent more than 20 per cent of their total budgets on developing new products, and this fact was the most important consideration. In general, adequate funding (and personnel) must be available, and it must be maintained during the development process for carrying out the research and development process (Samli & Weber, 2000). Ulrich and Eppinger (2008) suggest that aggregate planning for firms in terms of efficient use of their resources is pursuing only projects which can reasonably completed with budgeted resources. In a planning phase, management must prioritize the most important projects in terms of the success of the firm, those projects that are realizable with adequate resources. Other projects can be stopped or postponed.
2.4 Organization related success factors Project team skills Sarja (2014) found a few characteristics of development personnel: training, experience, commitment, expertise, motivation and ability. The author summarized these characteristics as team skills. In this study, we do not consider skills at the individual level; we focus on the thought that team skills are the consequence of cross-functional teams. Actually, this was the original idea of teams (e.g. Marquis & Straight, 1965). In general, many cross-functional team related studies emphasize the relationships between marketing and R&D (e.g., Griffin & Hauser, 1996). Cross-functionality has been found, without exception, to be a success factor of NPD (e.g., Cooper & Kleinschmidt, 1995). We share our focus with Ulrich and Eppinger (2008); a product development team should have expertise at least in marketing, design and manufacturing functions. Networking The way to consolidate in-house know how and resources is networking. The first phase of the networking concept includes lead users or customers in the development process (e.g., von Hippel, 1988; Kristensson et al., 2004). Bishop and Magleby (2004 in Sarja, 2014) required (but not described) more; networking must be beyond interacting with customers and end users. The next logical step is supplier involvement (e.g., Ragatz et al., 2002). Freel (2003) explored the relationship between networking with three horizontal actors: competitors, universities and the public sector. Aside from consolidating in-house know how, the benefits of networking are also risk and cost sharing, access to new technologies and markets and attempts to shorten development time (Ledwith & Coughlan, 2005). While networking was recognized as one of the key factors of technology pushed products, Ledwith and Coughlan (2005) found that there are conflicting findings in several studies between networking on a new product development and increased success. Their own study of 60 electronics firms found the same results. Therefore, the authors suggested a framework for managing networking in NPD projects for reaching successful collaboration. The framework is based on three variables:
11 1) The type of organization with which to collaborate Who? Which organizations should firms involve in their NPD projects? 2) The skills or absorptive capacity of the firm Skills? Do the firms have the necessary skills to benefit from the collaboration? 3) A firm’s new product strategy 4) Why? Are the reasons for collaboration consistent with the firms NPD strategy?
2.5 The survey instrument framework The research push case study survey instrument framework is based on the introduced success factors. The framework is illustrated in figure 5. The proposed framework is relatively broad and it is possible to use only part of it depending on the focus of the case study. The framework is meant to be used in various types of data collection in case studies, for example interviews, surveys, document and literature analyses and so on. The framework does not offer detailed questions, but the researchers can lead the questionnaires or make interview questions accordingly, depending on the method used. The framework leads to a focus to marketing related activities, organizational abilities and resource and time aspects, and these determinants are discussed below.
Figure 5. The survey instrument framework
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3.
Discussion
The aim of the transcription of TP success factors is to help a firm’s management to recognize the real actions needed to reduce product development risks and to help scholars to focus on the right issues when studying the key factors of breakthrough cases. For example, different survey instruments (e.g., questionnaires, surveys) can be built accordingly. After defining the content of TP success factors, we found three keynotes, which combine the definitions. The first keynote in the study is market observation activities in parallel with product development, or, rather, embedding them as a part of the development process. This can be seen from different angles in terms of several success factors. MP methods used guides the start of market observation immediately when planning a new product idea. This success factor also emphasizes another important issue; the development process, including marketing activities, should be the same regardless of the innovation driver (TP or MP). Consequently, customer needs must be identified systematically (focus on customer needs, fill an unrecognized need), and alternative solutions in the market must be studied in terms of customer needs instead of in terms of just itemizing competitors (alternative study). The outgrowth of these studies is the target market (existing or new) definition (market development). Technological ability contributes to developing valuable new products for customers, filling recognized – and in the ideal case – also unrecognized needs (technological advantages). The second keynote relates to organizational ability. The core task of a firm’s management from the product development perspective is to ensure needed resources for development work (management support). Because resources are always limited, they must be allocated in terms of the results of aggregate planning and project prioritizing (degree of funding). Generally, resources consist of human and financial domains (Samli & Weber, 2000). A capable development team is cross functional (project team skills), and the way to consolidate in-house know how and resources is networking (networking). Because of previous conflicting findings between NPD and increased success, networking activities must be planned strategically (Ledwith & Coughlan, 2005). The third keynote associates financial resources and different time aspects. As discussed, a long adoption time of TP products lies ahead. From a customer perspective, this means the acceptance time of new technology. At least partly, the acceptance time can be shortened by user-friendly design (adoption time, technophobia). From a firm’s perspective, a long run commitment to a project is required, in the other words, adequate financing (TP for difficult adopted). Finally, if the project is well planned and it pulls through the development phase, the end of the life (and payback) time is expected to be longer (life cycle). It is notable that an important factor in terms of product attributes is user-friendliness. There might be some other technological- or product-related attributes as well, but it seems that the current literature does not recognize them. Another notable thing is that, depending on research angle, a single success factor can be thematized differently.
13 The suggested success factors are based on the findings of two broad meta-analyses by Samli and Weber (2000) and Bishop and Magleby (2004) and are pre-analysed by Sarja (2014). The novelty of this study is the explanatory definitions of the discussed key factors, and, in that sense, it confirms and refines previous studies. For further research, we propose to test suggested key factors in breakthrough case studies. Naturally, there is some space when applying the results of this study. If some success factors are in closer examination in a case study, it is possible to go deeper. For example, Peteraf and Bergen (2002; 2003) broadened the competitor analysis framework in comparison to Chen (1996).
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Conclusion
The current literature does not introduce many firm success factors clearly. The factors may be presented too widely. In many cases, the factors were found to be self-evident, but, on closer examination, they may have different meanings. This can be a problem when researching the success factors of any business. It is important to be aware of what the success factors exactly mean. It is valuable for a firm’s management to recognize the real actions needed to reduce product development risks, and also helps scholars to focus on the right issues when studying the key factors of breakthrough cases. Based on two TP specific meta-analyses, this paper presents proposed reasonings and definitions of success factors in the NPD domain. The survey instrument framework for TP research cases is also introduced. Implications are drawn for future research on testing TP success factors in TP project cases using the survey instruments from the introduced framework.
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References Balachandra, R. & Friar, J. (1997). Factors for success in R&D projects and new product innovation: A contextual framework. IEEE Transactions on Engineering Management, 44(3), 276-287. Bass, F.M. (1969). A new product growth model for consumer durables. Management Science, 15 (January), 215-227. Bergen, M. & Peteraf, M. (2002). Competitor identification and competitor analysis: A broad-based managerial approach. Managerial and Decision Economics, 23, 157-169. Bishop, G.L. & Magleby, S.P. (2004). A review of technology push product development models and processes. Proceedings of DECT ’04, 383-392. Brosnan, M. (1998). Technophobia: The psychological impact of information technology. Routledge, NY. Calantone, R. & Li, T. (1998). The impact of market knowledge competence on new product advantage: conceptualization and empirical examination. Journal of Marketing, 62 (4), 13-29. Chen, M. (1996). Competitor analysis and interfirm rivalry: toward a theoretical integration. Academy of Management Review, 21, 100-134. Christensen, C. (1997). The innovator’s dilemma: when new technologies cause great firms to fail. Boston: Harvard Business School Press. Cooper, R. & Kleinschmidt, E. (1995). Benchmarking the firm’s critical success factors in new product development. The Journal of Product Innovation Management, 12 (5), 374-391. Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. Ernst, H. (2002). Success factors of new product development: a review of the empirical literature. International Journal of Management Reviews, 4(1), 1-40. Freel, M. (2003). Sectoral patterns of small firm innovation, networking and proximity. Research Policy, 32, 751-770. Freeman, C. (1982). Schumpeter or Schmookler?. In C. Freeman, J. Clark & L. Soete (Eds.), Unemployment and Technical Innovation. London: Pinter. Green, S., Gavin, M. & Aiman-Smith L. (1995) Assessing a multidimensional measure of radical technological innovation. IEEE Transactions on Engineering Management, 42(3), 203-214. Griffin, A. & Hauser, J. (1996). Integrating R&D and Marketing: A review and analysis of the literature. Journal of Product Innovation Management, 13 (3), 191-215.
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17 Samli, A.C. & Weber, J.A.E. (2000). A theory of successful product breakthrough management: Learning from success. Journal of Product & Brand Management, 9(1), 35-55. Sarja, J. (2012). A review of the Getting Real software development approach. Int. J. Agile and Extreme Software Development, 1(1), 78-94. Sarja, J. (2014). The key factors of successful technology push projects in ICT context: A review of the literature. Manuscript. Souder, W. E. (1989). Improving productivity through technology push. Research Technology Management, 32(2), 19-31. Sultan, F., Farley, J. & Lehmann, D. (1990). A meta-analysis of diffusion models. Journal of Marketing Research, 22 (February), 70-77. Tseng, H. & Chen, W. (2004). A replacement consideration for the end-of-life product in the green life cycle environment. Int. J. of Advanced Manufacturing Technology, 24(11-12), 925-931. Ulrich, K.T. & Eppinger, S.D. (2008). Product Design and Development. Irwin/McGraw-Hill. Venkatesh, V. & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315. Venkatesh, V. & Davis, F. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186-204. Venkatesh, V., Morris, M., Davis, G. & Davis, F. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478. von Hippel, E. (1988). The Sources of Innovation. Oxford University Press: Oxford Zmud, R.W. (1984). An Examination of “Push-Pull” Theory Applied to Process Innovation in Knowledge Work. Management Science, 30(6), 727-738.
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Int. J. Agile and Extreme Software Development, Vol. 1, No. 1, 2012
A review of the Getting Real software development approach Jari Sarja Raahe Unit, University of Oulu, Oulu, FI-92100, Finland Fax: +358-8-221-406 E-mail:
[email protected] Abstract: The small US software developing company called 37signals is a significant phenomenon in many ways. The company has launched successful commercial web applications. The company has its own unique way of business thinking, and the people of the company do not have any growth target. The people of the company also have their own way of thinking about the software developing process. They have named it Getting Real. Getting Real is not described as a developing method; rather, it is a philosophy or approach behind the development activities. It has confluence with agile methods, but unlike agile methods, in Getting Real the nature of the final product is also strongly emphasised. The success of the company has proven that there is some effectiveness in the Getting Real approach. Therefore, the aim of this study is to find out whether the Getting Real approach can be supported by previous professional literature and scientific research. Keywords: software development; agile methods; small business; the Getting Real approach. Reference to this paper should be made as follows: Sarja, J. (2012) ‘A review of the Getting Real software development approach’, Int. J. Agile and Extreme Software Development, Vol. 1, No. 1, pp.78–94. Biographical notes: Jari Sarja received his MSc degree (Information Processing Science) from the University of Oulu, Finland. Currently, he is a Project Researcher and a PhD student at the University of Oulu, in a side unit of Raahe. His research is mainly focused on the area of software development: agile methodologies, user experience and renewable energy. Before his research career, he has worked a long period in the electronics and component industry.
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Introduction
This study identifies the professional and scientific evidence for the software development philosophy or approach called Getting Real. The Getting Real approach was created by an US company called 37signals. The key persons1 of the 37signals have
Copyright © 2012 Inderscience Enterprises Ltd.
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created the Getting Real approach based on their own experience about developing software applications and commercialising them successfully. The key persons of the 37signals have written two books about their way of thinking about software development (Getting Real)2 and creating a profitable business in the internet environment (Rework). These two books, Getting Real (Fried and Heinemeier Hansson, 2006) and Rework (Fried and Heinemeier Hansson, 2010), are important empirical sources in this study. In Rework, the authors write the following about the book: “This book isn’t based on academic theories. It’s based on our experience. We’ve been in business for more than ten years. Along the way, we’ve seen two recessions, one burst bubble, business-model shifts, and doom-and-gloom predictions come and go – and we’ve remained profitable through it all” [Fried and Heinemeier Hansson, (2010), p.3]. The same principle applies to the Getting Real book. We call Getting Real an approach rather than a method, technique or procedure. Getting Real is not a described or documented software development method. It is a range of principles based on the good practices of the 37signals company. The Getting Real approach has confluence with agile methods. What is noteworthy is that 37signals is a small bootstrapped company without any expanding purpose. Regardless of that, they have gathered an active audience that follows the company. Widespread newspapers and magazines, such as The New York Times, Time, and The Wall Street Journal, have written stories about the key persons of the company, and they have been crowd-pleasing speakers in different events. It can be said that the outcome of the company is much wider than just the products they have developed; it consist of a different way of processing development and business thinking, and by-products. The company seems to enjoy a strong charisma of lonely riders, or even a little bit rebellious pioneers. Still two more issues exist, which make Getting Real an interesting research subject: according to databases, the key persons of the company and their books have been cited a few dozen times in academic researches and articles. Moreover, the Getting Real approach has not been the subject of a research before in a comprehensive way. From a practical point of view, this study may establish if the studied development and business models – or part of them – are useful benchmarking targets to other business owners. From a theoretical point of view, the purpose of this study is to find out if there exists any support from professional literature and previous research for the Getting Real software development approach. The main contribution is to connect the proven successful small business development and business ways to a professional and scientific context. The research question is: Can the Getting Real approach be supported by professional literature and previous scientific research? Since the Getting Real approach has not been researched before in a comprehensive way and it has confluence with agile methods, the studied previous research material mainly concerns agile methodologies. Abrahamsson et al. (2002, 2003) have observed that agile methodologies have evoked a substantial amount of literature. The Agile Manifesto (2011) is an important source in this research because it has been the starting point for agile definitions, rules, principles, and it is cited in most literature concerning agile methodologies. The influential persons behind the Agile Manifesto are also notable book and article writers. The research method in this study is conceptual analysis. Järvinen (2004) describes the nature of conceptual analysis by setting the question: “What is a part of reality according to a certain theory, model, or framework?” This study applies conceptual
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analysis in the contrary manner; it asks what is a part of theory according to certain practical activities? The data has been collected from many different sources: books, magazines, the internet, professional literature, scientific papers, and video clips. The collected data has been analysed using the systematic review and transcription methods. Systematic review can be undertaken to examine the extent to which empirical evidence supports theoretical hypotheses (Kitchenham, 2004). This is a very important aspect in this study, since the main research activity is to compare the empirical material to professional literature and previous researches. Transcription means converting the source text to another format, for instance from spoken language to a written form. The second section presents the previous studies on agile methodologies. An important part of this section is the description of the Agile Manifesto. Since there exists numerous agile methods, we have chosen four of them for general inspection: extreme programming, scrum, crystal methods, and feature-driven development. The company behind the Getting Real approach is also presented in the second section. Without knowing the company behind the approach, it would be difficult to gain an understanding of the approach. In the third section, we describe six separate Getting Real software development principles, and the conclusions of this study are summarised in the fourth section.
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Literature review
Software business is a much newer business line compared to manufacturing business lines. That is why traditional software development methods are based on the generic development process (or new product development process, NPD), which is widely used in various manufacturing business lines. Ulrich and Eppinger (2008, pp.13–15) describe the generic development process as a six-step process, which consists of the planning, concept development, system-level design, detail design, testing and refinement and production ramp-up phases. The traditional software development processes (e.g., Waterfall, Stage-Gate) are described from a quality-related point of view. For improving the quality of output from the process the focus has to be laid on the process itself by removing the variances of the process. There are a quality checkpoint between every working phase and the quality criteria must pass before moving to next working phase. The most important reason for criticism of traditional software development processes is the inflexibility for changes. Avison and Fitzgerald (1991), MacCormack et al. (2001), Nandhakumar and Avison (1999), and Parnas and Clements (1986) share the idea that traditional development methods are control-oriented, too mechanistic to use in detail, too ideal and hypothetical, and not working in dynamic environment. This provides a background for the emergence of agile software development methods. The major idea behind agile methods is to speed up the development time and to allow later changes to requirements. The number of different agile methods is existing and therefore it is difficult to find a common definition for an agile method. Strode (2006) has made a common definition for an agile method: “An agile method is a software development methodology designed for the management and support of iterative and incremental development of business systems in environments where change is constant. Agile methods use software development techniques that enhance teamwork in small empowered teams and support active customer involvement. An agile method is designed to produce
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working software early, using communication, feedback, learning and frequent meetings in preference to than modelling and documentation. Agile methods adapt existing software development techniques to achieve these goals”.
The Agile Manifesto includes general rules and principles for agile methods. It was signed by 17 persons influential in the agile field in 2001 [Agile Manifesto, 2011; Cockburn, (2002), p.213; Lindstrom and Jeffries, 2004]. The people behind the Agile Manifesto were individuals who had published separate software development methods with similar characteristics. All these methods are based on best practice experiences and evolutionary development practices focusing on early delivery and quality of software (Strode, 2006). The common rules in the Agile Manifesto are: “Individuals and interactions over processes and tools. Working software over comprehensive documentation. Customer collaboration over contract negotiation. Responding to change over following a plan.”
The Agile Manifesto further includes 12 explicit principles. These 12 principles of agile software are: •
“Our highest priority is to satisfy the customer through early and continuous delivery of valuable software.
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Welcome changing requirements, even late in development. Agile processes harness change for the customer’s competitive advantage.
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Deliver working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale.
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Business people and developers must work together daily throughout the project.
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Build projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done.
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The most efficient and effective method of conveying information to and within a development team is face-to-face conversation.
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Working software is the primary measure of progress.
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Agile processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely.
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Continuous attention to technical excellence and good design enhances agility.
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Simplicity – the art of maximizing the amount of work not done – is essential.
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The best architectures, requirements, and designs emerge from self-organizing teams.
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At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly.” (Agile Manifesto, 2011)
The Agile Manifesto is an important source in this study because it has been a starting point for agile definitions, and it is cited in most literature concerning agile
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methodologies. Because there exist numerous of different agile methods, we have selected four agile methods for closer inspection; extreme programming, scrum, crystal methods, and feature driven development, which belong to agile method family.
2.1 The company behind the Getting Real approach The background information of the company, 37signals, helps to deepen understanding of the Getting Real approach, which is the research target. Without knowing the company behind the approach, it would be difficult to gain an understanding of the approach. The presented issues are those that appear time and again when the company is spoken about. These issues are the big audience, the nature of the products and the unique business models of the company. 37signals is followed increasingly, and it has a loyal audience. The company has built the audience on purpose, as a kind of affordable marketing strategy. The company launched a weblog titled Signal vs. Noise in 1999. According to Fried and Heinemeier Hansson (2010, p.170) it had more than 100,000 daily readers in 2010. The fans and audience mean a lot to the company. Having an audience means an affordable way to reach a great number of people and potential customers, and to get direct feedback without any information barriers. The big group of followers of the small company, the audience, makes the company even more interesting from a research point of view. The common factor of 37signals’ products is that they have all been planned to be easy to use, opinionated, and relatively light and simple overall. Considering how successful these products have been, it can be said that at least a part of customers like simple products that do not require a lot of training before they can be used. After decades’ evolution with increasing features and complexity, simplicity and minimalism might be the forthcoming trend in the software business, perhaps in other business lines as well. The 37signals people summarise the idea of simplicity as the modus operandi of the company as follows: Our modus operandi: “We believe software is too complex. Too many features, too many buttons, too much to learn. Our products do less than the competition – intentionally. We build products that work smarter, feel better, allow you to do things your way, and are easier to use.” (Fried and Heinemeier Hansson, 2006)
37signals has a unique way of thinking about the running of a business. They have own ideas for example about company funding, product pricing, as well as about every day working methods.
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The Getting Real approach
Getting Real is a kind of way of lateral business thinking. It is a set of principles that lead the activities of a company. It is relatively difficult to define Getting Real, nor is it clearly defined by the company. It is not a software development method since the development process is not determined in it, and it also involves working and business methods. Getting Real is based on the company’s experience about developing software applications and commercialising them.
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After reviewing the source material, Getting Real is defined in this research as an approach that has an existence identical with the philosophies behind software development methods. It is presumable that the company people use ‘ultra-light agile methods’ without any formal documentation as their development method. There are six separate general principles in total: “1
Getting Real is about skipping all the stuff that represents real (charts, graphs, boxes, arrows, schematics, wireframes, etc.) and actually building the real thing.
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Getting Real is less. Less mass, less software, less features, less paperwork, less of everything that’s not essential (and most of what you think is essential actually isn’t).
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Getting Real is staying small and being agile.
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Getting Real starts with the interface, the real screens that people are going to use. It begins with what the customer actually experiences and builds backwards from there. This lets you get the interface right before you get the software wrong.
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Getting Real is about iterations and lowering the cost of change. Getting Real is all about launching, tweaking, and constantly improving which makes it a perfect approach for web-based software.
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Getting Real delivers just what customers need and eliminates anything they don’t.” (Fried and Heinemeier Hansson, 2006)
The key persons of the company define the benefits of the Getting Real approach as follows: “Getting Real delivers better results because it forces you to deal with the actual problems you’re trying to solve instead of your ideas about those problems. It forces you to deal with reality. Getting Real foregoes functional specs and other transitory documentation in favour of building real screens. A functional spec is make-believe, an illusion of agreement, while an actual web page is reality. That’s what your customers are going to see and use. That’s what matters. Getting Real gets you there faster. And that means you’re making software decisions based on the real thing instead of abstract notions.” (Fried and Heinemeier Hansson, 2006)
In order to clarify the analysis of the Getting Real theme, the principles are numbered (1–6). Each principle is introduced in detail below and compared with professional literature and scientific findings.
3.1 Getting Real – Principle 1 “Getting Real is about skipping all the stuff that represents real (charts, graphs, boxes, arrows, schematics, wireframes, etc.) and actually building the real thing.”
The first Getting Real principle is very similar to the common agile definitions regarding documentation. Already the set of common general rules for all agile methods – the Agile Manifesto – recommends focusing on well-functioning software instead of documentation: “Working software over comprehensive documentation”. The Agile Manifesto further includes 12 explicit principles. One of them is to focus on the
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development of process measurement: “Working software is the primary measure of progress”. In her research, Strode (2006) introduces common properties of agile methods and also mentions working software as the main product of development, together with minimising documentation. The key persons of the company criticise the need for comprehensive operational documentation – not only documentation related to software developing. Besides specifications, the key persons of the company call into question the need for roadmaps, projections (Fried, 2008), business plans, five-year plans (Heinemeier Hansson, 2009), financial plans, and strategies [Fried and Heinemeier Hansson, (2010), p.19]. Many professionals share the thinking about minimising documentation. Torvalds, the creator of Linux operating system, says about specifications: “A spec is close to useless. I have never seen a spec that was both big enough to be useful and accurate. And I have seen lots of total crap work that was based on specs. It’s the single worst way to write software, because it by definition means that the software was written to match theory, not reality” (Torvalds, 2005). Palmer and Felsing (2002, pp.100–101) state that it is a painful process to generate documents of source code and it increases the chances for updating. Cockburn (2002, p.177) suggests to dispense with design documentation beyond whiteboard sketches. This is in line with what the key persons argue; they recommend using paper sketches and real HTML screens in the planning phase instead of documents (Fried and Heinemeier Hansson, 2006).
Principle summary The first Getting real principle closely resembles one of the four common rules for agile methods, it is only defined in a somewhat more detailed and extensive way. We can conclude that the first Getting Real principle is supported by professional literature and previous scientific research.
3.2 Getting Real – Principle 2 “Getting real is less. Less mass, less software, less features, less paperwork, less of everything that’s not essential (and most of what you think is essential actually isn’t).”
Fried and Heinemeier Hansson (2006; 2010, pp.62–63) describe the second principle as follows: “If you keep your mass low, you can quickly change anything: your entire business model, product, feature set, and/or marketing message. You can make mistakes and fix them quickly. You can change your priorities, product mix, or focus”. One of the principles in the Agile Manifesto can be compared to this second principle: “Simplicity – the art of maximising the amount of work not done – is essential”. The key persons of the company emphasise to do less at every level; the code level, feature level, daily routine level as well as company strategy level. All characteristics of the agile methods, as well as those of the Getting Real approach, aim at flexible changes during the developing process. Appleton (2005) has summarised this idea as follows: “There is no code that is more flexible than no code!” He argues the good software design is not knowing what to put into code but it is knowing what to leave out.
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The key persons of the company see many different advantages in reducing codes. Less software is easier to manage, it reduces the code-base, which means less maintenance work, it lowers and speeds up the cost of change, and it causes fewer bugs and reduces the need of support. “For every feature that makes it into your app, ask yourself: Is there a way this can be added that won’t require as much software? Write just the code you need and no more. Your app will be leaner and healthier as a result” (Fried and Heinemeier Hansson, 2006). Wild (2008) recommends writing less code by justifying and prioritising every feature and minimising useful feature sets. It is a received principle that software design should be kept as simple as possible. For instance, Appleton (2005), Fernandez (2008), Lindstrom and Jeffries (2004), Müller and Tichy (2001), Nielsen and Mack (1994) and Wild (2008) share this principle with the 37signals people. According to the key persons, feature evaluation should always be done by thinking what is really needed, and leaving out the rest. The ‘less mass’ philosophy seems to present even a competitive edge to the company. “It’s all part of how we differentiate ourselves from competitors; instead of trying to build products that do more, we build products that do less” (Fried and Heinemeier Hansson, 2006). The key persons of the company highlight the minimalist character in every source when they speak about the products (e.g., Fried and Heinemeier Hansson, 2006, 2010; Fried, 2008; Heinemeier Hansson, 2009; Park, 2008, etc). It is difficult to prove scientifically whether there is any correlation between the number of features and the success of the product since there is not very much previous research available on this subject. There are also many variables, e.g., different researched customer segments [the customer segments according to Moore (1991): innovators, visionaries, pragmatists, conservatives, sceptics]. But it can be concluded that the fewer features a product contains, the simpler it is to use. Simple-to-use products always have loyal users. The company has proved it with more than three million users [Fried and Heinemeier Hansson, (2010), p.3]. As mentioned, minimalism might be a growing trend also in other business lines, such as consumer electronics or catering business. The key persons refer to Gordon Ramsey – a three-Michelin-star chef – who recommends to have only around ten dishes on a menu and to focus on them [Fried and Heinemeier Hansson, (2010), p.83].
Principle summary The second Getting Real principle is very general and extensive. It recommends doing things in a simple and light way at various levels. The phrase ‘less mass’ covers practically all functions of a software company, including the daily-level job, planning, documentation, and product design activities. The phrases ‘less paperwork’ are more descriptive and belong under the ‘less mass’ umbrella. The general less mass thinking – including all sub-thoughts – is in line with the Agile Manifesto principle: “Simplicity – the art of maximising the amount of work not done – is essential”. The idea of ‘less software’ and keeping the code as simple as possible is clearly in accordance with the agile approaches and is shared for instance by Appleton (2005), Fernandez (2008), Lindstrom and Jeffries (2004), Müller and Tichy (2001), Nielsen and Mack (1994) and Wild (2008). The ‘less feature’ thinking is very close to the ‘less software’ thinking since in most cases less software is the result of reducing the number of features. It is not possible to
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reach a conclusion concerning the correlation between the number of features and the success of the product because there are so many different kinds of customer segments. It is certain that innovators and visionaries want more features than mainstream customers. On the other hand, it can be seen that many customers want products that are easy to use, which in many cases means fewer features. The ‘less paperwork’ thinking is clearly in line with the agile methodologies and is defined in the Agile Manifesto as one of the four common rules: “Working software over comprehensive documentation”. We can conclude that the second Getting Real principle is supported by professional literature and scientific research.
3.3 Getting Real – Principle 3 “Getting Real is staying small and being agile.”
This is the first instance in which the key persons mention the concept of agility. However, they do not seem to refer directly to agile methodologies; rather, agility is a consequence of the small size of the company. “All the cash, all the marketing, all the people in the world can’t buy the agility you get from being small” (Fried and Heinemeier Hansson, 2006). This is also the first Getting Real principle which does not have a straightforward connection with the Agile Manifesto rules or principles; in the Agile Manifesto itself, agile methodologies are not linked only with small teams. However, some key persons behind the Agile Manifesto (e.g., Beck, 1999; Lindstrom and Jeffries, 2004) argue that particular agile methods are meant for small teams. Some researchers (e.g., Müller and Tichy, 2001; Rising and Janoff 2000; Strode, 2006) also share the idea of the small team size. The key persons of the company do not speak about the size of the developing team but the size of the whole company. They point out that a small business can be profitable and that growth itself should not be a main target of a company [Fried and Heinemeier Hansson, (2010), pp.22–23]. They emphasise four main reasons why it is favourable to keep a company small: •
the possibility of cheap and fast changes
•
resource limitations force one to do things faster and cheaper
•
fewer formalities, less bureaucracy, and more freedom
•
nimbler organisation.
Power and Reid (2005) have researched the flexibility and performance of small firms, and they have identified the main factors that influence the performance of long-lived small businesses positively. Two out of the four factors support this principle. A small firm must be aware of the drivers of change, and it must be ready for quick changes.
Principle summary The Agile Manifesto does not commit itself to the size of a company, but one of its main ideas is to react fast to requirement changes even in a late phase of the developing process. The fourth common rule of the Agile Manifesto is “Responding to change over following a plan”, and one of the 12 explicit principles is: “Welcome changing
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requirements, even late in development. Agile processes harness change for the customer’s competitive advantage”. Agile behaviour and the possibility of reacting fast are a consequence of the small size of a team or company. It is an established fact that small companies are more agile and faster than bigger ones (e.g., Power and Reid, 2005). We can conclude that the third Getting Real principle is supported by previous scientific research.
3.4 Getting Real – Principle 4 “Getting Real starts with the interface, the real screens that people are going to use. It begins with what the customer actually experiences and builds backwards from there. This lets you get the interface right before you get the software wrong.”
The order of building software is not addressed in the Agile Manifesto. One rule is loosely similar and closest to this principle; it is the one that was already introduced with the first principle – “Working software over comprehensive documentation”. The key persons of the company emphasise in many sources that it is important to start the building of software directly with real things without formal planning and documentation (e.g., Fried and Heinemeier Hansson, 2006; Fried, 2008), and the fourth principle states that the starting point should be the user interface. The key persons also equate the user interface to a product. They state the user interface is a product from user point of view (Fried and Heinemeier Hansson, 2006; Singer, 2008). The key persons of the company argue for starting the interface design first because it is relatively light and easy to change before the programming has started. They also argue that the user interface gives an impression of the application to the designers. Constantine and Lockwood (2002) note that the web page itself is a user interface. They also claim that the success of the user interface design determines the success of web applications. Nielsen and Mack (1994) have estimated that billions of dollars have been lost in internet sales because of usability problems. It is hard to find support for starting the design from the user interface, or for the opposite viewpoint. In all likelihood, the issue has not been researched extensively. However, Parnas (1969) notes in his paper that the user interface should be designed first, and thus share the viewpoint of the key persons. The 37signals people have focused strongly on user interface design, also at the more detailed level. They mention the same principles as with whole products; the user interface must be easy to use, opinionated and aesthetic. They emphasise the meaning of blank slate design, and the form of context and language, e.g., buttons, links, search functions, words and sentences, etc. [Fried and Heinemeier Hansson, 2006; Singer, 2008; see also Nielsen and Mack, (1994), pp.279–293]. The language of the user interface has also been studied before. De Souza (1993) presents the semiotic engineering approach for user interface designers, which has similarities with this Getting Real principle. User interfaces have been researched already before the internet became a common phenomenon. Grudin (1989) had already concluded that context is more important than consistency, against previous studies. He also states that knowing the users and their tasks can be a cutting edge for the designers. Grudin and Gentner (1990) also emphasise the difference between the engineer’s and user perspectives when designing the user interface.
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Principle summary The fourth Getting Real principle is ambiguous. The first point suggests to start the design of an application from the user interface and to design the real screens first. This seems to be based on the best practices of the company, and it is certainly a good observation. It is maybe stating the obvious for software designers, or it has not been researched a lot. In any case, it is hard to find support from professional literature and research for this point. The second point – the user experience – is loosely connected with this principle. However, the company has focused on and described user interface design from the user’s point of view, in other words the user’s experience, so deeply that it is valuable to summarise the point. All aspects the 37signals people present, the form of context and design including the language of user interface, are supported to some extent by previous research. A noteworthy matter is that most of the relevant studies are relatively old, from the time before the internet became common. The newer user interface research mostly focuses on more complicated user interfaces. However, it can be concluded that the same principles are valid with simple and minimalist web applications. We can conclude that the fourth Getting Real principle is partly supported by professional literature and scientific research.
3.5 Getting Real – Principle 5 “Getting Real is about iterations and lowering the cost of change. Getting Real is all about launching, tweaking, and constantly improving which makes it a perfect approach for web-based software.”
The fifth Getting Real principle is not directly supported by the Agile Manifesto rules or principles. The Agile Manifesto addresses the possibility of change, but from a different point of view. The Agile Manifesto rule and principle “Responding to change over following a plan” and “Welcome changing requirements, even late in development”, refer to one of the main characteristics of agile methods – flexibility for changes, but not for the cost point of view. However, it is self-evident that lowering the cost of change is one important motive behind the establishment of agile methodologies. The key persons of the company emphasise the change possibility from the cost point of view. The cost thinking is in line with their experience of limited development resources and the minimalist design principles. Kunz et al. (2008) summarise the relationship between the cost of change and agile methodologies saying agile software development methods try to decrease the cost of change and therewith reduce the overall development costs. The different cost of change in agile software development in comparison with traditional software development according to the project progress as suggested by Beck (1999) is shown in Figure 1. There is a strong connection between iterations and agile methodologies. Miller (2001) has defined nine characteristics which make a software development process agile. One of those characteristics is iteration; a short cycle which is repeated many times for refining the deliverables and completing activities. Kunz et al. (2008) emphasise the same aspect of extreme programming.
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The cost of change compared to the development method
Source: Beck (1999)
The key persons of the company have described the iterative process as follows: “Instead of banking on getting everything right up front, the iterative process lets you continue to make informed decisions as you go along. Plus, you’ll get an active app up and running quicker since you’re not striving for perfection right out the gate. The result is real feedback and real guidance on what requires your attention.” (Fried and Heinemeier Hansson, 2006)
They do not mention agile methodologies but speak about the exactly same iteration characteristic as the researchers and co-founders of agile methodologies.
Principle summary The Agile Manifesto strongly supports flexibility for changes. It does not mention the cost of change viewpoint. However, lowering the cost of change has been recognised as one important motive behind the establishment of agile methodologies, and it is an important characteristic of agile methodologies in general. In the fifth Getting Real principle, iteration is regarded as a method of implementing the lowering of the cost of change. It is totally in line with the characteristics of agile methodologies (see e.g., Miller, 2001; Strode, 2006). A noteworthy matter is that also the second Getting Real principle introduces many other methods of implementing the lowering of the cost of change. It can be said that to lower the cost of change is a consequence of iteration, but also of other methods of implementation introduced with the second principle. We can conclude that the fifth Getting Real principle is supported by professional literature and scientific research.
3.6 Getting Real – Principle 6 “Getting Real delivers just what customers need and eliminates anything they don’t.”
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The 37signals people have emphasised the importance of eliminating extra features in many sources, as has been discussed before. They have turned it into a competitive advantage, calling it ‘underdoing the competition’. The content of the sixth Getting Real principle resembles the previously introduced ‘less software-thinking’. Less software means less features, less code, and less waste. All these methods and mindsets have been introduced previously in this study. Therefore, we examine one small new viewpoint in this chapter, the waste eliminating. Wild (2008) has defined principles of lean thinking. One of the seven principles is eliminate waste. Wild defines waste as follows: •
anything that does not create value for the customer
•
the customer would be equally happy with the software without it.
He explains the prime directive of lean thinking: •
create value for the customer
•
improve the value stream by removing non-value-adding activities.
The cost of complexity as suggested by Wild is illustrated in Figure 2. The curve titled complexity simply means that more features cause more waste. According to Wild complexity is the biggest source of waste. Figure 2
The cost of complexity
Source: Wild (2008)
Wild has found that only 7% of features and functions are always used in typical systems. 13% of them are used often, 16% sometimes, 19% rarely, and 45% never. The percentages are illustrated in Figure 3. It means that only 20% of features and functions are used always or at least often. This means that, roughly speaking, 80% of features and functions are against lean thinking and are waste. Avoiding these 80% could make a lot
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of savings in the development and maintaining phases. This theory is totally in line with the sixth Getting Real principle and supports it. Figure 3
The features and functions used in a typical system
Source: Wild (2008)
Principle summary It can be concluded that the sixth Getting Real principle is relatively universal by nature. It is a higher-level principle compared to the other Getting Real principles, and it summarises many other principles and mindsets of the company. The sixth Getting Real principle is also in line with the Agile Manifesto principle: “Simplicity – the art of maximising the amount of work not done – is essential”. It is also supported by Nielsen and Mack’s (1994) usability heuristics (aesthetic and minimalist design), as well as by Wild’s (2008) principles of lean thinking (eliminate waste). We can conclude that the sixth Getting Real principle is supported by previous scientific research.
4
Conclusions and discussion
Considering the size of the researched company, the company and the Getting Real approach are relatively well known, especially in its home country and by special interest groups. The key persons of the company and their books have been cited a few dozen times in academic researches and articles. The Getting Real approach has not been a research subject before in a comprehensive way, so it has been interesting to connect the provenly successful small business (or small organisation) development and business ways to a scientific context. Following the investigation of the Getting Real principles, it can be concluded that many principles include a similar message. Perhaps, the authors have meant a somewhat different viewpoint between the principles. However, the main message of the principles could be summarised as follows: The application should have as few features as possible, and the whole development process should focus on building the real things directly instead of deep planning and documentation. That, and being small, make late changes
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possible, and also keep the cost of changes reasonable. For instance, the messages of the first and fourth principles are very similar to one another, as well as the messages of the second and sixth principles. The Getting Real principles resemble the Agile Manifesto rules and principles, but the viewpoint is somewhat different. The Getting Real principles deal with the nature of an application, which limits its use only to light products, such as web applications. The rules and principles of agile methodologies also address other viewpoints, such as individuals, teams, customers, collaboration, and reviews. However, the agile rules and principles do not commit to the nature of the final product. It would be interesting to know if the 37signals people have thought about the agile rules when defining the Getting Real principles. We tried to find that out with a short personal e-mail interview, but Fried’s answer was a polite refusal explained by the lack of time (personal e-mail, 24.5.2011). The support from previous research for the Getting Real principles is introduced in Table 1. It shows that the Getting Real principles, which reportedly are based on the best practices of the researched company, are mostly supported by Agile Manifesto, experts and specialists, professional literature, and previous scientific research. Table 1
Professional and scientific support for the Getting Real principles
Getting Real principle 1
Support from Agile manifesto/Agile methodologies
Professional literature and scientific papers
x
x
2
x
x
3
Partly
x
4
Partly
Partly
5
x
x
6
x
x
We can conclude that four out of the six Getting Real principles are supported by the Agile Manifesto. These four principles are clearly supported by other professional literature and researches as well. One out of the six Getting Real principles is not directly supported by the Agile Manifesto, but there are other professional literature and researches which support it. Finally, one out of the six Getting Real principles is only partly supported by the Agile Manifesto and other literature and researches. Consequently, we can conclude that there are not so many new aspects in the Getting Real approach. The ideas included in the principles have existed already before in some form. How is it possible that so much attention have given to the Getting Real approach? We think there are many reasons. The company has proved in practice the effectiveness of the Getting Real approach by developing and commercialising successful products. The success of the small company has provided the people of the company with a strong charisma. The charismatic entrepreneurs have been very open and shared their knowledge with their growing audience. The books written by the key persons of the company [Getting Real (Fried and Heinemeier Hansson, 2006) and Rework (Fried and Heinemeier Hansson, 2010)] resemble the company’s products; they are very light and easy to read and use ordinary language instead of jargon. We think the manner of representation has helped people to appreciate the thoughts of the 37signals people.
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Even though there are not so many new aspects in the Getting Real principles, it can be said that the small company has picked up the right principles from all possible business and development rules and tenets for strengthening their activities. From a practical point of view, we can conclude that the researched company might be a good benchmarking case for other small business owners as well. From a theoretical point of view, we can conclude that there are no conflicts between professional literature and previous research, and the Getting Real approach.
Acknowledgements Acknowledgements to Professor Samuli Saukkonen for the support and valuable discussions during the study.
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Notes 1
2
The definition ‘key person’ refers to Jason Fried and/or David Heinemeier Hansson, who are the partners of 37signals and co-writers of the books Getting Real and Rework. The definition is used when it is not known which partner/co-writer to cite, or when citing both. The internet version of the book Getting Real does not have page numbering. Citations to this book are in the form ‘(Fried and Heinemeier Hansson, 2006)’.
