Building Blocks of IT-enriched “Digitized” Products
IT-enriched “Digitized” Products: Building Blocks and Challenges Full paper
Ainara Novales Reutlingen University
[email protected]
Martin Mocker Reutlingen University and MIT Sloan School of Management
[email protected] Daniel Simonovich Reutlingen University
[email protected]
Abstract The use of digital, IT-based components in physical products is becoming increasingly relevant in practice. Surprisingly, the strategic impact of these “digitized products” has not received a lot of attention in IS research so far. Extant papers on the topic rely on ambiguous terminology (e.g., “smart products”, “cyberphysical systems”, “digital product-service systems”) and underlying concepts differ widely. Based on an extensive literature review, this article provides an overview of the different terms and identifies five conceptual elements that form the building blocks of digitized products in research: “hybridity” (i.e., the combination of digital and physical components), connectivity, smartness, digitized product-service bundles (servitization of digitized products), and digitized product ecosystems. The implication for practitioners is that each element comes with different managerial challenges that companies need to address when incorporating the respective element in their products. The research implication is that each conceptual element is supported by different theoretical streams.
Keywords Product digitization, smart products, cyber-physical systems, Internet of Things, servitization, ecosystems
Introduction The role of information technology (IT) in achieving strategic impacts, especially competitive advantage, has been the subject of information systems (IS) research for some time (Chen et al. 2010). So far, a lot of research has focused on the impact of IT on processes while “digital technology’s transformative impact on industrial age products has remained surprisingly unnoticed in the IS literature.” (Yoo et al. 2010). At the same time the use of digital, IT-based components in physical products is gaining increasing relevance in practice. Porter and Heppelmann (2014) state that IT is “revolutionizing products [as …] IT is becoming an integral part of the product itself.” Senior business executives like GE’s CEO Jeff Immelt (2015) are even proposing that “every industrial company must become a digital industrial company.” We call IT-enriched physical products, “digitized” products to differentiate them from purely intangible “digital” products, such as digital music, e-books and software. Examples of digitized products include the Philips Hue smartphonecontrollable lightbulb, Audi Connect internet-connected cars, or Rolls-Royce’s sensor-enabled pay per use jet engines. Several authors suggest that digitized products offer various benefits for both providers and users of these products such as richer, longer-term and closer customer relationships (Allmendinger and Lombreglia 2005), simpler and enhanced user experience (Allmendinger and Lombreglia 2005; Mühlhäuser 2008; Sabou et al. 2009), increased reliability (Porter and Heppelmann 2014), “evergreen”, i.e., constantly updateable, design (Porter and Heppelmann 2015; Yoo et al. 2010), and customization and configuration at lower cost, (Porter and Heppelmann 2014; Porter and Heppelmann 2015) among many others. While the demand for reliable insights on product digitization is increasing, the limited number of available IS research articles paint a diffuse picture for researchers aiming to add to the body of knowledge in this Twenty-second Americas Conference on Information Systems, San Diego, 2016
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area. First, there is quite a variety in terminology, ranging from “cyber-physical systems” to “smart, connected products” or “digital product-service systems”. Second, even authors using the same term refer to different conceptual elements, including mere IT-physical hybrids, network-connected products, ITenabled product-service bundles and full-blown ecosystems based on IT-enriched products. But there is a significant difference when considering the implications of these different concepts: different types of digitized products will be associated with different managerial challenges that companies need to address. E.g., moving from a standalone digitized product to a digitized product operating within an ecosystem creates a need for coordination among different actors of the ecosystem (Porter and Heppelmann 2014). Instead of arguing for the one valid concept of IT-enriched products, we set out to identify the “building blocks” or conceptual elements of digitized products, delineate them from each other and show the differences in challenges that come with each element. Hence this article aims to answer two research questions: (RQ1) “What elements constitute a digitized product?” and (RQ2) “What are managerial challenges that companies need to address for each element?” Using this article as a basis, future research can be much more explicit on what conceptual elements they include when looking at product digitization. By mapping the management challenges to the different elements, our work also helps companies choose conceptual elements to incorporate in their products. In the following sections, we first lay out the methodology we followed. We then present our findings, especially different terms, definitions, and conceptual elements of digitized products to then match conceptual elements to management challenges discussed in literature. We conclude with a discussion on our findings and their implications for future research and for practice.
Research methodology In order to answer our research questions, an extensive literature analysis was performed, starting with a preliminary journal-based search, followed by a more exhaustive database-driven keyword search. The journal-based search served as an exploratory search to identify the key terms used and to get a first grasp on the existing literature. According to Webster and Watson (2002) “the major contributions are likely to be in the leading journals, [therefore] it makes sense (…) to start with them”. For this search, all issues from 2004 on of the top two IS journals, MISQ and ISR (Association of Business Schools 2015), were considered. To also include the perspective of practice, we added the highest ranking practice-oriented management journals, Harvard Business Review, MIT Sloan Management Review and California Management Review (Association of Business Schools 2015). From this search, 64 papers were marked as potentially relevant, 37 of which were considered for examination after going through the abstracts. After a full reading, eight articles were found to be relevant for the field of product digitization. After identifying the key terms used for digitized products, a keyword search was conducted using the EBSCO Business Source Complete database and the following keywords: TITLE ((digit* OR smart OR connected) AND (product OR service)) OR ABSTRACT ((digit* OR smart OR connected) AND (product OR service)). To limit the number of papers, only publications in journals and magazines and in English language were considered. Also the timeframe was limited to articles published after 2004. The search resulted in 15,652 articles. In a first step, we filtered out most of 10,825 articles from magazines (e.g., MacWorld) that were clearly not academic magazines or not scholarly articles (e.g., product announcements, book reviews). Secondly, while going through remaining articles’ titles and abstracts, we filtered out articles that were purely technical articles (e.g., on how WiFi technology works). At the same time, we excluded all articles that did not address issues related to physical products with digital components. Thus, 27 articles were included for full reading, by considering all papers addressing product digitization regardless of their field of study. 15 were found to be relevant for the topic of product digitization and thus added to our article pool. We cross-checked those results with the results from the journal-based search to find that the eight papers selected from the journal-based search were also identified in the keyword research, confirming the reliability of the analysis and suitability of the keywords. The whole process took approximately 13 weeks. The results from the keyword search are available on request via email from the first author. Given the large number of results, we refrained from using further databases that did not allow defining as precise searches as EBSCO (e.g., Google Scholar). However, we did check the top 50 results from a similar Google Scholar search with our results and did not identify further relevant articles.
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During the evaluation of the papers, we also went “backward” by reviewing relevant papers referenced in previously identified articles (Webster and Watson 2002). This way five more articles were added to the article pool. Figure 1 below provides a graphic representation of the data collection process.
Figure 1: Search approach for the literature analysis on product digitization. For the data analysis, a concept-based review was conducted, summarizing and synthesizing relevant concepts and definitions into different conceptual matrixes (Webster and Watson 2002). This analysis and its results are presented in the following findings section.
Findings The findings are divided into two sections. The first one covers terminology and the second one introduces different conceptual elements of digitized products and their managerial implications.
Terminology
Ahram et al. (2011) and Ahram et al. (2012) Behaviour & Information Tech. / Work
Allmendinger and Lombreglia (2005) Harvard Bus Rev. HBR
Augmented product
Intelligent object
Smart object
Product Service Systems
CyberPhysical Systems
Digitization of physical product
Connected product
Smart product
Smart, connected product
In the literature review, we identified a number of different terms used for physical products with digital components, including “smart products”, “smart connected products”, “connected products”, “smart objects”, “augmented products”, “intelligent objects”, “cyber-physical systems” and “product service systems” (see Table 1). While this demonstrates a broad variety of terms and possible differences in the underlying concepts, the term “smart product” seems to be the most widely-used term in literature (Ahram et al. 2011; Ahram et al. 2012; Gutierrez et al. 2013; Lerch and Gotsch 2015; Maass and Varshney 2008; Mühlhäuser 2008; Rijsdijk and Hultink 2009; Sabou et al. 2009; Yoo et al. 2012; Yoo et al. 2010). Other authors use related terms, such as “smart, connected product” (Porter and Heppelmann 2014), smart object (Borgia 2014), and intelligent object (Wunderlich et al. 2015). Despite the widespread use of the term “smart product”, examples presented in the mentioned papers show that there are significant differences in the underlying concepts, i.e. differences in what the authors mean with the term. For instance, Rijsdijk and Hultink (2009) consider autonomous (but not necessarily network-connected) products like a washing machine or an autonomous vacuum cleaner that reacts to its environment via sensors as smart products, whereas Porter and Heppelmann (2014) also consider more sophisticated products such as the smartphonecontrollable Sonos speaker system that allows to connect the product to an ecosystem of third party digital services (e.g., Spotify, Pandora, Apple Music).
x x Twenty-second Americas Conference on Information Systems, San Diego, 2016
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Building Blocks of IT-enriched “Digitized” Products
Barrett et al. (2015) MIS
x
Quarterly MISQ
Borgia (2014)
x
Computer Communications
Cusumano (2008)
x
IEEE Computer Society Gutierrez et al. (2013) IEEE Conference
x x
Research-Technology Mgmt.
x
Lusch and Nambisan (2015)
x
MISQ
Maass and Varshney (2008)
x
Electronic Markets
Mühlhäuser (2008) Constructing Ambient
x
Intelligence Workshop
J. of Product Innovation Mgmt.
Sabou et al. (2009)
CEUR Workshop Proceedings
x
x
lansiti and Lakhani (2014) HBR Lerch and Gotsch (2015)
Parmar et al. (2014) HBR Porter and Heppelmann (2014, 2015) HBR Rijsdijk and Hultink (2009)
x
x x x x
Wunderlich et al. (2015)
x
J. of Services Marketing
Yoo et al. (2010) and Yoo et al. (2012) ISR, Org. Science
x
x
Table 1. Different terms used for digitized products. Because there is such a broad variety of what authors mean when they use even the same or similar terms, we dissected the different elements of the concepts underlying the used terms. To avoid confusion with existing terms, we refer to “digitized products,” meaning any combination of a physical product with a digital component that includes any combination of the following conceptual elements.
Conceptual elements of digitized products By collecting and classifying the definitions and examples of digitized products in our article pool, we identified the following five conceptual elements that represent the building blocks of digitized products in literature (see Figure 2): (1) “hybridity” (i.e., the mere combination of digital and physical components), (2) smartness, (3) connectivity, (4) servitization and (5) digitized product ecosystems.
Figure 2: Conceptual elements of digitized products in literature. The different definitions and examples provided by the authors in this literature review, differ by the combination of these conceptual elements, i.e. different types of digitized products combine different Twenty-second Americas Conference on Information Systems, San Diego, 2016
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building blocks (see Table 2). Likewise, we found that different conceptual elements also imply different challenges that firms need to address when they decide to incorporate the respective element into their digitized product (see Table 3). Ahram et al. (2011) and Ahram et al. (2012) Allmendinger and Lombreglia (2005) Barrett et al. (2015) Borgia (2014) Cusumano (2008) Gutierrez et al. (2013) lansiti and Lakhani (2014) Lerch and Gotsch (2015) Lusch and Nambisan (2015) Maass and Varshney (2008) Mühlhäuser (2008) Parmar et al. (2014) Porter and Heppelmann (2014) and Porter and Heppelmann (2015) Rijsdijk and Hultink (2009) Sabou et al. (2009) Wunderlich et al. (2015) Yoo et al. (2010) and Yoo et al. (2012)
Hybridity
Smartness
x
x
x x x x x x x x x x x
Connectivity
Servitization
x
x
x
x
x
x
x x
x
x
x x x
x x x
x
x x x
Ecosystem
x
x
x x x
x
x x
x
x
x
x
Table 2. Conceptual elements of digitized products used by different authors. Hybridity (combination of digital and physical components) IT components get embedded in physical products (Maass and Varshney 2008; Mühlhäuser 2008; Porter and Heppelmann 2014; Sabou et al. 2009; Wunderlich et al. 2015; Yoo et al. 2012; Yoo et al. 2010). In this regard, we refer to “hybridity” as the product’s quality of combining both digital and physical components. Examples of hybrid products include digitized lawnmowers, vacuum cleaners and washing machines (Rijsdijk and Hultink 2009) as well as wearable clothes with embedded sensors (Ahram et al. 2011; Maass and Varshney 2008; Mühlhäuser 2008; Porter and Heppelmann 2014). The physical components comprise mechanical elements of the product that enable its functioning, whereas digital components embody the logic. Digital components include a wide variety of elements ranging from sensors to software running on microprocessors (Ahram et al. 2011; Maass and Varshney 2008; Mühlhäuser 2008; Rijsdijk and Hultink 2009). Product hybridity represents the most basic building block of any digitized product, since digital components are the key enablers of product digitization. From the examined articles we identified several challenges that come from combining physical and digital components in products (see Table 3). Most of the challenges relate to product design and development: dealing with hardware limitations when developing new software capabilities (Sabou et al. 2009), mastering the “simplicity paradox”, i.e., more complex product design while simplifying the user experience (Mühlhäuser 2008), synchronizing different “clock speeds” in the development of e.g., software and physical products (Porter and Heppelmann 2014), and the need for re-usable product platforms for digitized products (Yoo et al. 2012). Given what we said before, these challenges are common to all digitized products, regardless of which other conceptual elements they incorporate. Smartness Different authors consider different dimensions when defining product smartness. According to Rijsdijk and Hultink (2009) product smartness comprises “seven characteristics, including autonomy, adaptability, reactivity, multifunctionality, ability to cooperate, humanlike interaction, and personality.” Similarly, Porter Twenty-second Americas Conference on Information Systems, San Diego, 2016
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and Heppelmann (2014) consider four different levels of functionality enabled by smart products: monitoring, optimization, control and autonomy. Borgia (2014) states that smartness allows products to “sense, compute, communicate, and integrate seamlessly with the surrounding environment.” There have been several attempts at comparing the characteristics that make products smart (Gutierrez et al. 2013; Sabou et al. 2009). Sabou et al. (2009) compare the characteristics defined by Maass and Varshney (2008), Mühlhäuser (2008) and the Smart Product Consortium, and conclude that “context awareness”, “pro-activity” and “self-organization” are common features. It is worth noting that not all hybrid digitalphysical products exhibit “smartness” factors. Mobile app-controlled physical objects are digitized products, but not necessarily context-aware. Examples of product smartness can be found in a car’s “rain-sensing windshields with automated wipers” (Porter and Heppelmann 2014) or in sensor-equipped autonomous vacuum cleaners (Rijsdijk and Hultink 2009). Just as with hybridity, the integration of smart components in products involves several challenges (see Table 3). To achieve context awareness and proactivity (or even autonomy), smart products need to collect data and be equipped with sophisticated algorithms that determine their behavior. Hence, management challenges relate to the management and continuous analysis of varied data of potentially suboptimal quality, e.g., derived from the device’s interaction with its environment (Sabou et al. 2009) and from dealing with complex reasoning algorithms (Lerch and Gotsch 2015; Sabou et al. 2009). Connectivity Connectivity refers to the product’s ability to communicate with other systems. Connected products are able to collect data from their environment and exchange data via a network (Borgia 2014). Porter and Heppelmann (2014) distinguish one-to one, one-to-many or many-to-many connectivity depending on the actors involved. Others differentiate by the technology used, which can range from radio frequency communication (RFID) to an IP-based internet of things (Maass and Varshney 2008; Mühlhäuser 2008). According to Porter and Heppelmann (2014), connectivity serves two purposes: “First, it allows information to be exchanged between the product and its operating environment, its maker, its users, and other products and systems. Second, [it] enables some functions […] to exist outside the […] device, in […] the product cloud.” This includes remote access to certain product features. Furthermore, connectivity is argued to enhance the value and capabilities of smart components (Porter and Heppelmann 2014) and even to provide the basis for IT-based smart products (Lerch and Gotsch 2015; Lusch and Nambisan 2015; Mühlhäuser 2008; Wunderlich et al. 2015). Thus, connectivity can be considered a key enabler 0f some smartness features. However, not all smart products are connected. E.g., an autonomous vacuum cleaner (e.g., the Dirt Devil M607 Spider) might sense when it hits a wall, react to this stimulus through an algorithm, without being connected to a network. Hence, we consider both elements as separate building blocks. Audi’s “Connect” cars are examples of connected products: using a private cloud, the car’s doors can be locked via a mobile app. Product connectivity involves again different challenges for companies deciding to add this building block to their digitized products (see Table 3). A key challenge is the support of the communication among the products while addressing privacy and security challenges arising from the communication (Borgia 2014; Maass and Varshney 2008; Porter and Heppelmann 2014; Porter and Heppelmann 2015). Users might want to limit access to data on the use of digitized products (Maass and Varshney 2008). Besides, challenges also result from the management of the device itself due to the need to establish communication protocols enabling software updates, switching on/off or monitoring among other connectivity functions (Borgia 2014) and from the need to build an entirely new technology backbone (often in a private or public cloud) that supports this connectivity (Porter and Heppelmann 2014). Servitization Servitization refers to service offerings integrated in manufacturers’ products (Baines et al. 2009), in our case, enabled by the digital components of the product (Barrett et al. 2015; Lerch and Gotsch 2015). These integrated product-service bundles are also known as product-service systems (Lerch and Gotsch 2015). In fact, the digitization-enabled servitization trend allows manufacturers to provide new business models based on product-service systems (Lerch and Gotsch 2015), generating revenue not by selling a product but through the continuous provision of a service. An example of this “product-as-a-service” model is RollsTwenty-second Americas Conference on Information Systems, San Diego, 2016
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Royce’s “power by the hour” (Barrett et al. 2015; Parmar et al. 2014; Porter and Heppelmann 2015). Instead of selling an engine, digitization (e.g., through the collection of usage data) allows selling engines as a service including predictive maintenance services (Barrett et al. 2015; Parmar et al. 2014). In this regard, Porter and Heppelmann (2014) state that these services “create a substitute for product ownership, reducing overall demand for a product (…) since they allow users to have full access to a product but pay only for the amount of product they use.” Again, as most product examples mentioned so far demonstrate, servitization is not a requirement for all hybrid, smart, or connected products. But companies adding servitization to their digitized products will need to address many managerial challenges (see Table 3). One challenge is the design of viable business models (Porter and Heppelmann 2014; Porter and Heppelmann 2015). The shift towards servitizing a digitized product implies changes in product design, as responsibility for maintenance and its associated costs remains with the manufacturer (Porter and Heppelmann 2015). At the same time, there is an incresead need to manage and capture data to charge appropriately for the use of the product (Porter and Heppelmann 2015). Besides, there is a need for increased coordination across different parts of the company (Porter and Heppelmann 2015), especially in situations of user-reported issues in the operation of the product, potentially involving customer service, IT, and R&D. Digitized product ecosystem The term ecosystem refers to a network of interacting actors (Lusch and Nambisan 2015) in which individuals and organizations connect with each other to combine often complementary products and services (Parmar et al. 2014) to enhance the overall value offering. A digitized product can operate as an isolated product or enable other companies to use the product as a “platform” and innovate on it (Yoo et al. 2010). Digitized products can hence act as connectors between product users and providers of complementary products and services (Porter and Heppelmann 2014). Digitized product ecosystems can even connect with other ecosystems forming what Porter and Heppelmann (2014) call “systems of systems”, such as “a smart building, a smart home, or a smart city.” An example of a digitized product ecosystem is Philips’ HealthSuite cloud-based platform, which supports connectivity among multiple devices (e.g., medical scanners) and apps that collect and analyze data, connecting users and healthcare providers such as hospitals or insurance companies (Philips 2016). Moving from providing standalone digitized products to digitized products that operate within an ecosystem creates several additional managerial challenges (see Table 3). One is the coordination among the different actors of the ecosystem (Porter and Heppelmann 2014). Companies need to define the level of openness of the ecosystem, the ecosystem governance, as well as their role within the ecosystem (provider or orchestrator) (Porter and Heppelmann 2014). This also creates further security and privacy issues, given that customer data might need to be shared among the actors of the ecosystem (Borgia 2014; Maass and Varshney 2008; Porter and Heppelmann 2014; Porter and Heppelmann 2015; Sabou et al. 2009). Thus, companies need to define ownership, rules and access rights to product data (Porter and Heppelmann 2014; Yoo et al. 2010). Other challenging issues include interoperability, requiring the establishment of some type of cross-company standards (Porter and Heppelmann 2015) and dealing with cognitive differences among the actors within the ecosystem (Lusch and Nambisan 2015). Element
Hybridity
Smartness
Challenge • • • • • • • • • • • •
Cross-functional coordination (Porter and Heppelmann 2015) Creating and dealing with generative platforms of knowledge and skills (Yoo et al. 2012) Security/privacy (Porter and Heppelmann 2014; Porter and Heppelmann 2015; Sabou et al. 2009) Dealing with hardware limitations (Sabou et al. 2009) Mastering the simplicity paradox between product design/user experience (Mühlhäuser 2008) Building an entirely new technology infrastructure (Porter and Heppelmann 2014) Synchronizing “clock speeds” of software and hardware development (Porter and Heppelmann 2014) New design principles (Porter and Heppelmann 2014; Porter and Heppelmann 2015) Change of the IT role to a more central role in the organization (Porter and Heppelmann 2015) Establishing the features that the product should include (Porter and Heppelmann 2014) Deciding on developing capabilities internally versus outsourcing (Porter and Heppelmann 2014) Dealing with suboptimal data quality (Sabou et al. 2009) Twenty-second Americas Conference on Information Systems, San Diego, 2016
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Connectivity
Servitization
Digitized Product Ecosystem
• • • • • • • • • • • • • • • • • • • • • • • • •
Representing much richer and varied information (Sabou et al. 2009) Continually supporting emergent knowledge (Sabou et al. 2009) Dealing with complex reasoning algorithms (Lerch and Gotsch 2015; Sabou et al. 2009) New management systems (Lerch and Gotsch 2015) Defining data required to maximize offering’s value (Porter and Heppelmann 2014) Communication among smart products (Maass and Varshney 2008) Mix of functionality embedded in product versus in the cloud (Porter and Heppelmann 2014) Security/privacy (Borgia 2014; Maass and Varshney 2008; Porter and Heppelmann 2014; Porter and Heppelmann 2015; Sabou et al. 2009) Remote device management (Borgia 2014) Building an entirely new technology infrastructure (Porter and Heppelmann 2014) Support for new business models (Porter and Heppelmann 2014; Porter and Heppelmann 2015) Cross-functional coordination (Porter and Heppelmann 2015) New management systems (Lerch and Gotsch 2015) “Fully or partially disintermidiating service networks” (Porter and Heppelmann 2014) Entering new businesses by selling product data to third parties (Porter and Heppelmann 2014) Multi-actor coordination (Porter and Heppelmann 2014) Technical interoperability among related products (Porter and Heppelmann 2015) Dealing with the cognitive distance among the actors in the ecosystem (Lusch and Nambisan 2015) Managing the ecosystem (Yoo et al. 2010) Attracting heterogeneous and expected firms (Yoo et al. 2010) Challenged conventional norms of ownership, roles and rules (Yoo et al. 2012) Security/privacy (Borgia 2014; Maass and Varshney 2008; Porter and Heppelmann 2014; Porter and Heppelmann 2015; Sabou et al. 2009) Value chain disruption (Porter and Heppelmann 2014) Pursing an open or a closed system (Porter and Heppelmann 2014) Managing ownership and access rights to product data (Porter and Heppelmann 2014)
Table 3. Managerial challenges resulting from each different element of digitized products.
Discussion The findings of our literature review show that current research in the area of digitized products relies on ambiguous terminology. We provided an overview of the different terms, and identified five conceptual elements referred to in literature: the hybridity of combined physical products with digital components, smartness, connectivity, servitization (digitized product-service bundles), and digitized product ecosystems. The elements differ conceptually, i.e., in the way digitization is applied to the physical products and in the value that digitization adds to the physical product. Most authors cover several conceptual elements, but none of them is explicit about that. It is implicitly assumed that all digitized products exhibit the characteristics covered in the respective articles. No article dives into any depth on the differences of the various conceptual elements and the implications of combining different elements. One might assume that the more elements a digitized product incorporates, the more value it can potentially add. However, we demonstrated that each conceptual element comes with a distinct set of challenges that companies have to address if they decide to add the conceptual element to their digitized products. Each element also seems to come with its own set of risks. For example, given that the success of ecosystems depends on network effects (the more users, the more value per users (McIntyre and Subramaniam 2009)), operating an ecosystem puts high demands on companies. Hence, the decision on which conceptual elements to incorporate is far from simple and clearly one of strategic relevance. Another question relates to dependencies among conceptual elements. We only found one article (Porter and Heppelmann 2014) that identified different categories of digitized products, which assumes (in an otherwise unexplained graphic) that there is a sequential build-up. This implies that connectivity requires smartness as a pre-condition, and that using digitized product-service bundles requires connectivity, etc. However, in actual products we do not always find this build-up. E.g., some connected digitized products are not smart (e.g., some app-controllable lightbulbs have no sense of their environment, and are not proactive or autonomous). Hence, dependencies between conceptual elements and the cost-value-risk trade-off of introducing certain combinations of conceptual elements should be subject to further research.
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Each conceptual element also comes with a set of theoretical foundations. E.g., hybridization of physical and digital product parts relies on the “coordinat[ion of] diverse production skills and integrati[ion of] multiple streams of technologies” (Prahalad and Hamel 1990) known as core competencies. In this case, the production skills and technology streams include digitization, mechanics and others. When software development skills are involved, research on success factors of software firms will be relevant (Cusumano 2004; Cusumano 2008; Hoch et al. 2000; Yoffie 1997). Research on digitized product service systems has to consider the theoretical foundations of “servitization”, i.e. the “process of creating value by adding services to products” (Baines et al. 2009) and continue to apply the insights of servitization to IS (e.g., Böhmann et al. 2014; Cusumano 2008), as well as identify the specifics of product-service-systems that are digitized. Research on ecosystems based on digitized products will rely on theories related to multi-sided platforms (MSPs) (e.g., Hagiu and Wright 2015). Challenges of MSPs should be researched in the light of the specific context provided by digitized products. This includes issues such as MSP pricing and design (e.g., how many sides to involve or how open or closed the MSP should be) (Hagiu 2014). Research on combinations of conceptual elements will have to combine these different research streams.
Conclusion, Limitations and Further Research Driven by the observation of inconsistency in the terminology used to refer to physical products with digital components, as well as by the lack of consensus on their conceptual composition in IS research, we posed two research questions: (RQ1) “What elements constitute a digitized product?” and (RQ2) “What are the managerial challenges for each element?” The five identified conceptual elements can help future researchers to be more specific about their conceptualization and perception of digitized products (or any related term). A next step for research can be to apply relevant insights from the different theoretical streams identified above to digitized products. In addition, our research can also help practitioners reflect on the kind of digitized product to offer and the challenges to be expected. Our study is based on a literature review of articles on digitized products – a still nascent area in IS research. We are aware that our research has several limitations. The analysis of a literature review can be subjective, even though we discussed included and excluded papers and those with doubts regarding inclusion. Besides, while the conceptual elements and challenges were stated in these articles, often they were not well defined, and were not the article’s main focus. Empirical research analyzing digitized product manufacturers can help further classify and categorize the challenges and to formulate propositions relating conceptual elements, expected benefits and management challenges. As a next step, we are studying manufacturers to test and complement the identified challenges, eliciting capabilities firms need to have to address these challenges.
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Building Blocks of IT-enriched “Digitized” Products
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Twenty-second Americas Conference on Information Systems, San Diego, 2016
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