Technological Forecasting & Social Change 76 (2009) 1055–1077
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Technological Forecasting & Social Change
Value Driven Technology Road Mapping (VTRM) process integrating decision making and marketing tools: Case of Internet security technologies David Fenwick a, Tugrul U. Daim a,⁎, Nathasit Gerdsri a,b a b
Department of Engineering and Technology Management, Portland State University, Portland OR, 97207, United States College of Management, Mahidol University, Bangkok, 10400, Thailand
a r t i c l e
i n f o
Article history: Received 13 February 2009 Received in revised form 16 April 2009 Accepted 17 April 2009 Keywords: Technology Roadmapping Hierarchical decision model Technology Development Envelope (TDE) Internet security technologies
a b s t r a c t This paper presents a new approach to Technology Roadmapping by integrating marketing and decision methodologies. While much of the research into technology roadmapping has been applied to products that represent a one-time ROI to the manufacturer, current Internet technologies are resulting in web services that use an entirely different financial and business model of licenses and subscriptions. This paper addresses the software services applicability and documents a start-to-finish application of cross-discipline models and tools to form a reallife roadmap from market drivers to project headcount. Pitfalls in the roadmapping process will be documented and suggestions for improvement will also be discussed. © 2009 Elsevier Inc. All rights reserved.
1. Introduction Technology roadmapping has been applied in many situations, ranging from electronics products and devices to hospital procedures, but little has been covered regarding actual cases and the tools required to meet the objective of roadmapping process. In addition, software, and particularly web services, has not been thoroughly analyzed even though it represents as the high growth technology arena. The multi-layer time-based chart is a popular and rewarding format for showing the alignment of functional strategies, but the development of this chart is often more an art than a science. Sometimes there is limited data available, which forces a great reliance on opinions. Other times there may be a dearth of training of the techniques that can be applied to each phase of the roadmapping process. This paper introduces and applies some of the tools available to business and marketing, as well as decision-making models, to complete the requirements matrix of each roadmap objective and arrive at a traditional multi-layer time-based roadmapping chart. In the paper, Google Checkout1 is introduced as an example of web-based Software as a Service (SAAS) example to further exemplify the roadmapping process to software services. Due to the magnitude of the technologies required to fully realize an online checkout service – from internationalization to shipping alternatives to billing to inventory to even social networking – the problem is much more complex than can be addressed here. So to demonstrate the applicability of the toolset, security solutions will be detailed and mapped as a representation of the larger process within Google Checkout. Other solutions can be appended using the same process outlines provided here. 2. Literature review Because this research features an entire service technology roadmapping project frominception to iteration, a diverse set of topics and tools were explored for applicability. The literature falls into three main categories: (1) Technology Roadmapping, (2) Marketing
⁎ Corresponding author. E-mail address:
[email protected] (T.U. Daim). 1 http://checkout.google.com/. 0040-1625/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.techfore.2009.04.005
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Tools, and (3) Decision-Making Models. The technology roadmapping literature provided goals and objectives and an overall strategy of the process. The marketing tools literature provided a toolset for the initial phases of the roadmapping process, such as Assessment, Market, and (Product or Service) Solutions. And the literature on Decision-Making Models provided a means to order and connect the pieces of the roadmap. 2.1. Technology roadmapping It is reported that technology roadmapping started to be used in the 70's [1,2] and started to be used as strategic planning tools [3–5]. Review of prior research shows that technology roadmapping was used for national [6–8], industry [9–11], international [12], public policy [13,14] purposes. Initial structure of technology roadmaps were introduced by Koen [15] and EIRMA [16] and were operationalized by Phall et al. through the T-Plan process [17–20]. It was important to limit to scope of the research and create boundaries [21] to keep the research manageable, such as the focus here on security technologies. The Value Road Map (VRM) [22] concept of assigning a value on products and services provides marketing tie-in to customer value drivers, and a quantifiable method to select emerging technologies for business benefit. To measure the difference in value, a baseline current assessment is needed [23]. Software, and especially web services, does not lend itself well to technology-driven roadmaps [24]. A customer value driver market approach could have more possibilities, and was chosen for that reason. Classifying the objectives into their “workshop” layers and customizing them to apply to other uses, such as software web services, reveals families of markets, products/services, and technologies that can be created by multiple objectives at lower levels [25]. Multiple roadmaps or parts of roadmaps can be combined to create new products and services, such as the 2-Factor security solutions presented in the case. These combinations can even create new “virtual innovations” that did not exist by themselves [26]. Regardless of the combinatorial potential, the forecast should be evaluated as an interconnected whole, and not as separate pieces [27]. All candidate technologies, whether existing, owned, or not, should be considered. Expectations for disruptive technologies should be incorporated into the roadmap [28], and a bottom-up approach is an effective way to discover a use for those disruptive technologies [29]. 2.2. Marketing tools The baseline Assessment and Market analysis comes from proven marketing tools consisting of a Five Forces analysis [30], SWOT diagrams [31–33] and Value Propositions [34] to determine the industry environment, the assets of the company, and what customers want and need. These marketing tools have been in use for decades and are well documented and understood. Unfortunately, many who are trained in technology management and the use of decision-making models and roadmapping tools are typically not familiar with these marketing representations, and vice versa. 2.3. Decision-making models A Comparative Features Matrix showing the offerings of similar services from competitors provides a baseline set of current and desired feature already available in the market [35]. Once the features and feature categories are identified, a perceptual map can be devised to cluster important expected features, [36]. The results from the Perceptual Mapping process can be used to nominate candidate technologies and compare in a Delphic Hierarchy Process (DHP) [37,38] using pairwise comparisons leading to a Hierarchical Decision Model which utilizes an Analytical Hierarchy Process (AHP). Plotting the Hierarchical Decision Model over time, while considering time-sensitive variables, forms a basis for a Technology Development Envelope [39,40]. The TDE provides a means for creating technology data points on the roadmap. 2.4. Literature gaps The research in establishing technology roadmaps has been going on for a while. So far most of it has been focused on justifying the methodology and demonstration of it through different cases. There has been some attempts discussing available tools, however few of them demonstrated application of them. This paper presents a step by step guideline for roadmapping technologies for decision makers in engineering and technology driven firms by integrating marketing and decision tools. The literature gaps and resulting research objectives are summarized below:
Technology Roadmapping Marketing Tools Decision Making Models
Literature Gaps
Research Objective
No set of integrated tools or cases where their use is demonstrated are available to develop a technology roadmap. Marketing tools are not used to their potential in technology roadmapping. Hierarchical decision models (HDM) present an opportunity to link markets to products to technologies and finally to R&D projects on the technology roadmaps.
Develop a set of guidelines for which tools to use at which stage and demonstrate the use of them. Integrate marketing tools into the technology roadmapping. Use HDM to operationalize technology roadmapping
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3. Roadmapping approach Many other studies have established a process for product planning, fundamentally based on the T-Plan process of Phaal et al. [17]. In this application of the process, however, performance of the Google Checkout Internet services and technologies will be forecasted. Various and appropriate evaluation tools are utilized to arrive at the objectives to define a Value-driven technology RoadMap (VRM) [22]. Value Drivers were determined to reflect the customer's current needs and future expected needs. These Drivers eventually lead to a technology roadmap, which defines technologies to purchase, lease or develop. The decision then suggest what projects should be developed and the number of headcounts needed to support the technology acquisitions. This VTRM approach provides a clear starting point, with step-by-step procedures in addition to well-defined tools to reach the roadmap goal. Fig. 1 shows the T-Plan process with the added marketing and roadmapping tools used to meet the objectives. There is much overlap of the tools used to arrive at an objective, which adds to the reliability of the results since no single tool is used to determine an objective. Through the Google case, we will test the applicability of the tools as suggested in Fig. 1, which really presents our propositions. Fig. 1 is developed for a service like Google Checkout, however it can be easily adopted for products as well. We focused on the generation of information through use of multiple methods. The final step of putting them and linking them on a roadmap has been discussed and explained in the literature [17–20]. This last stage includes further detailed in Section E under Roadmap links. Following the VTRM process steps, an (A) Assessment, (B) Market Analysis, (C) Services availability, and (D) necessary Technologies, are evaluated to arrive at an (E) Roadmap which is created to link technology to future market opportunities. Each of the process steps will be detailed in turn using the appropriate tools for each step. Terms that are underlined are the Objectives for each Process Step, and the Tools utilized are depicted in bold print. 3.1. Assessment 3.1.1. Create a SWOT diagram to provide both an internal (strengths and weaknesses) and external (opportunities and threats) analysis of the company The SWOT diagram provides a quick analysis of a company within a particular environment. Depending on the environment, different attributes may come into play, which might help or hinder operations within that industry. The SWOT diagram and the Five Forces analysis have some overlap, especially in the external attributes of opportunities and threats. The internal strengths and weaknesses can provide a clear snapshot of the present situation, or can take into account new developments that could come online within the company. The SWOT diagram is useful in determining the Operation Performance as well as the available Technology assets. 3.1.2. Investigate the five forces of competition, which gives an outside-in view of an industry A Porter's Five Forces analysis provides insight into the industry environment, or Market, within which the company is competing. Each of the forces has an effect on the competitors providing checkout services. For example, each player in the e-
Fig. 1. VTRM process and tools.
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payment industry must deal with a potential threat of new competitors entering the electronic checkout market. The customers, or buyers (merchants) may or may not have options to the services offered by each provider, which affect the merchants bargaining power. Brand loyalty or lock-in features can deter the switching of customers to competitors, which defines the threat of substitutes. Few suppliers to the checkout provider might offer limited choices, thereby increasing the bargaining power of suppliers. Lastly, the interplay of competing checkout providers themselves defines an internal market dynamic. A single dominant player might characterize this. Or there may be many providers each scrambling for their own market niche. 3.1.3. Utilize both the SWOT and five forces analysis to evaluate the current market Both SWOT and Five Forces contain analysis regarding the current Market situation, and each technique can crosscheck the other. Knowing the current market, including the competitive forces affecting the entire industry, can help temper later decisions on technology gaps or services with an appreciation of competitors and external factors. 3.2. Market analysis 3.2.1. Understand the value proposition for customers to determine the performance dimensions The Performance Dimensions help pinpoint how customers evaluate the offerings of each provider. The Value Proposition Template paints a scenario of what is important to the customer, including quantifiable attributes such as time periods and pricing. There is overlap with the SWOT analysis tool, which has an external parameter of Opportunity, and may have Performance Dimensions. Performance Dimensions are covered by the Five Forces analysis of buyers and substitutes, too, potentially providing a three-way verification of not only the Performance Dimensions, but the Value Drivers as well. 3.2.2. Use the value proposition to identify the market drivers for these customers In addition to the SWOT and Five Forces analysis, the Value Proposition Template outlines many of the Value Drivers important to the customer, and answers the question, “What can this provider do for the customer?” The Value Proposition can detail not only potential features of products and services, but also the quality and timeliness of the offerings. 3.2.3. Prioritize the Drivers based on value to the customer and the Internet e-payment Industry Environment Because the Five Forces analysis and the Value Proposition templates overlap each other, it becomes easier to Prioritize the derived Value Drivers based upon the competitive forces acting within the industry. For example, a driver found using the Template might be a lock-in feature under Substitutes in the Five Forces analysis that could prevent the customer from trying a substitute and switching to a competitor. 3.2.4. Identify gaps in the market of unfulfilled drivers The Five Forces evaluation, as well as the use of the Value Proposition Template, can help to identify Driver Gaps in the market. Sometimes these gaps can be pre-sales or post-sales features, such as improved support, or performance related features, such as set-up times or processor clock speed. The Gaps indicate new or revised offerings the company could provide to its customers, that are not being currently fulfilled. It may even reveal a wasted effort of marketing an existing product or service that is neither needed or appreciated in the market, and therefore could be withdrawn. The Competitive Features Matrix is an efficient way to compare product offerings and identify Gaps. The matrix could have all the features being offered by all companies within the industry, as well as features that are not being currently addressed. A gap may also consist of combinations of features that are needed by the customer but not offered by any provider. An example of this might be an ability to ship internationally plus an automatic international tax and shipping calculator. One provider may offer international shipping but there is no mechanism to easily calculate tax and shipping costs, while another provider has a tax and shipping calculator, but not the ability to ship internationally. Once the Value Drivers are derived, they can be included and compared with the categories determined in the Competitive Features list. There should be much overlap between the Drivers from the Value Proposition and the categories in the Feature list. If there is not, then the Value Proposition is not representative of the customer's situation, or the Features and/or competitors don't represent the correct industry addressing the needs of the Value Proposition. 3.3. Service or products (solutions) offered 3.3.1. Utilize the value proposition and the competitive features matrix to create a list of desirable features (also including identified driver gaps) The Competitive Features Matrix is a central part of creating an offering Strategy. Important Features currently offered by each provider (including the provider under analysis) are listed, as well as market Drivers that are not presently offered by any provider. If a provider is expected to release a new or updated feature in an upcoming release of a product or service, that information should be included as well. Price is another critical feature that should be listed, especially for comparison purposes. In that way a fair comparison can be made across potentially wildly disparate feature sets. For example, a provider may offer an inventory-tracking feature that no one else provides because of the extra cost, but the price of that feature might double the price to the customer.
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The Features are often needed to fulfill the Value Proposition requirements. If the Features in the list are not needed in any Value Proposition, then that feature is not important in the offering, but still might be justified because all the other competitors offer the same feature, and reviewers might expect it. It might also be that simply the sheer number of features determines which offering “wins” in the market, although consumers are becoming wiser and now expect usability over a plethora of features. 3.3.2. Group like features together to form categories of features Many of the features being offered can be grouped into categories having similar attributes. A web services feature that provides for secure communications between client and server, and a user login feature both share a similar aspect of security. The Groups will then be the initial definitions of the Product or Service being offered. 3.3.3. Rank the features and benefits of the products or services in order of importance To identify an Importance to Performance Gap, Perceptual Map Rank Valuation (I to P Valuation) can help compare and Rank the value of the features. If a feature offered by a provider is outstanding in performance, it may show up as a strength of the offering. But if the customer deems it of little importance, the feature should be relegated a negative gap — that is, more performance than is necessary. If customers need a feature but no provider can supply it, then there is a positive gap. The size of the gap indicates the amount the feature is needed by the consumer, and the current inability of the market to provide it. The I to P Valuation Perceptual Map is an efficient way to pictorially represent those items requiring attention. The map is a 2dimensional chart showing attribute Importance (or expected Performance) along its Y-axis, and the difference between the feature's Importance and its Performance is shown along the X-axis, with positive X-axis numbers showing a higher importance (or expectation) than is currently being satisfied. Features that show up in the upper right quadrant are high importance features that have performance gaps, while those attributes in the lower left quadrant are those of low importance but exceeding expectations. So the items showing up in the upper right quadrant are those features that should be addressed first, and the lower right quadrant shows those features that are lower priority opportunities. The features in the lower left might be good candidates for removal from the product or service, if only to simplify the user interface. 3.3.4. Paint a strategy for which services to offer and when to offer them This is the step in the process where matches are made between solutions and appropriate technologies. Pairwise Comparison Method (PCM) is a tool that provides a means of allowing experts to comparatively rank items in their relationship to each other. Even more importantly, PCM provides a means to verify the consistency of the expert's opinions. Creating a Strategy begins with the Competitive Features Matrix, and utilizes the Perceptual Map to prioritize solutions (Products or Services). The PCM of expert opinions, and Hierarchical Decision Models (HDM) using an Analytic Hierarchy Process (AHP) can evaluate the appropriateness of various underlying technologies inside each solution and help decide which services to offer and when to offer them. 3.3.5. Identify service gaps where additional services or combinations of services are needed to meet driver expectations Finally, Service or Product Solution Gaps can be identified that take into account not only the market needs, but also the viability of the solution, the timeliness of the offering, and the importance of the service in relation to others. This process of identifying the solution Gaps will be repeated at the lower process step of Technology, where technology gaps will be identified. 3.4. Technology needed for solution 3.4.1. Identify appropriate technologies that will fulfill the service requirements Just as in the Process Step C above, for each Products or Services targeted, the technologies appropriate to these Solutions need to be identified and listed. The Perceptual Map and the PCM tools are good at being able to prioritize the solutions and then determine the appropriateness of various technologies to fulfill the solution. Completing this step will create the connections between the technologies and the related solutions on the roadmap. 3.4.2. Compare technologies and cluster similar ones together The technologies themselves will have related attributes and can be combined into like groups. For example, in the e-payment industry there is a requirement for client confidence and also for banking services prerequisites. These solutions have an underlying need for Internet security technologies, and can be envisioned as a technology Group. 3.4.3. Compare the value of the technologies and rank their potential impact over time The AHP can give a snapshot in time of the relative value, or appropriateness, of technologies to a particular solution. Applying the model at regular time periods can provide data for a Technology Development Envelope (TDE), especially if information regarding the availability and readiness of the technology is included. The TDE can Rank the impact of technologies over a time interval, and the graphic presentation encourages a comparison of competing technologies for various solutions or groups of solutions. Each time period in the TDE re-ranks technologies based upon changing internal and external factors, which can vary the appropriateness of the available technologies from one time period to the next.
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3.4.4. Identify technology gaps The technology section of the roadmap can be created using the results of the TDE, and Technology Gaps can be readily identified by their affect in delaying or even delisting solutions. Sometimes adjusting the internal or external factors affecting the TDE could have an effect on the technology readiness. An example of this might be a current internal level of R&D within a company that, if increased, might be able to accelerate availability of a needed technology. The TDE could model the R&D expenditures in an underlying AHP model, where changes in the spending speeds up the technology development. 3.5. Roadmap links 3.5.1. Link and cross-index all technologies, solutions, and drivers The TDE provides a direct means to Link All the technologies to the Products or Services. The Competitive Features Matrix provides a means to connect the Drivers, which are addressed by the individual Features, to the Solutions, which are suggested by the grouped features. The TDE provides a clear time scale for the Roadmap, and while even though the technologies were determined using a topdown process starting with Value Drivers, the time scale index of Solution availability is determined bottom-up. That is, Solutions can only become available to address Value Drivers when the underlying Technologies are available. 3.5.2. Define the projects needed to build the appropriate technologies, or identify where the technology can be acquired or licensed The Roadmap can also be extended downward to determine the origins of the technologies, where a make vs. buy decision can be made. Project definition or technology acquisition can be identified. 3.5.3. Assign a headcount of human resources to fill the projects and accomplish the tasks Finally, the staffing requirements can be determined given the size of the project. It is also possible to determine overlaps where development can be applied to more than one Technology, just as one Technology can be applied to more than one Solution and a Solution can be applied to more than one Value Driver. The costs associated with the development team, license costs, or technology purchase can and should also be illustrated and made part of the Roadmap. The costs can also be implied given a cost per resource, and a price determined for each technology license or acquisition. 4. Case analysis Google Checkout provides an example of the use of the VTRM process to help predict where the e-payment service will or should be in the next few years. In this case, Market Drivers, Solutions (Services), Technologies, R&D Projects, and Resources can be mapped to help plan three years into the future. The presentation of this case is organized by tool used, from the drivers at the “top” of the roadmap to the resources at the “bottom”, and follows the progression shown across the top of Fig. 1. Experts in this field provided subjective data used in the analyses. 4.1. SWOT analysis A SWOT analysis can help provide a base assessment of a company in relation to an industry or market. The SWOT analysis for Google Checkout, shown in Fig. 2 shows quite a few Strengths that support Checkout as a logical extension of Google services. The advertising and search engine technology can lead a merchant's potential customers to their online stores, where checkout can conclude the shopping experience. The combination of search and buy is very compelling. Google is financially strong, so the funds needed to ensure a successful launch is readily available. Checkout's customers (merchants) are often already customers of the Google advertising program, so payments for services can be leveraged across services. Unfortunately, banks, as suppliers to Google Checkout, control the transaction fees and rates used in each purchase. This Weakness, as well as many others, can be alleviated over time by utilizing the Strengths and Opportunities available to Google. Other weaknesses include the lack of exclusivity — any merchant can use any checkout process, except for eBay, who is now banning the use of Google checkout with eBay transactions. Even though eBay is considered Google's largest advertising customer, they are now encroaching on eBay's, and subsidiary PayPal's, turf. Other opportunities available to Google Checkout include future growth paths, such as person-to-person payments, and a potential to establish accounts where funds can be held. This would enable Google to earn interest on money that belongs to merchants and customers. eBay is collecting much bad press over this practice, and this might be an area where Google could excel by offering interest-bearing accounts, subject to banking regulations. The Strengths and Weaknesses are attributes pertaining to the inner operations of the company, and something Google could potentially control. The Opportunities and Threats are attributes that are external to the company, and correspond to industry forces mostly outside the control of Google. These external attributes can be inspected in more detail using a Five Forces of Competition analysis.
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Fig. 2. SWOT analysis of Google Checkout.
4.2. Five forces of competition The Five Forces of Competition analysis of the e-payment industry shows relatively few players dominated by industry giant PayPal, which is owned by eBay. The five forces include (1) Potential Entrants, (2) Buyers (or customers), (3) Substitutes, (4) Suppliers, and (5) Competitors. The first four forces act upon the companies participating in the industry, and each force is evaluated separately to determine how much influence it has on the participating companies. Fig. 3 shows the Five Forces within the e-payment industry.
4.2.1. Potential entrants The e-payment industry has nominal entry barriers, mostly consisting of brand awareness and setting up long-term agreements with suppliers, who are the credit card companies, telco companies, and banks who handle the actual transfer of funds. In addition, a potential new entrant must be able to meet the buyer's and supplier's security expectations, which is an ever-rising bar. It is possible to enter the market with minimal “banking level” security capabilities, but competitor companies are offering and providing increasing levels of security. Bottom line evaluation of the threat of potential entrants: Moderate.
Fig. 3. Forces within the e-payment industry.
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4.2.2. Buyers The on-line merchants, who are the customers or buyers, have little choice of payment processors. There are only a few online payment processing companies, and those all funnel through VISA, MasterCard, American Express, and Discover. PayPal is a little different in that they also have the ability to hold funds until needed, or tap directly into a checking account for payments and withdrawals. The banking regulations have not caught up to the “virtual” bank, yet, and PayPal has come under fire for some questionable practices. The new Google Checkout solutions appear to provide a minimal way to handle the merchant's customer's credit card payments, and payouts go directly to the merchant's checking account, like other competitors. The bargaining value of buyers: Low. 4.2.3. Substitutes The e-payment industry tries to lock-in Buyers to something proprietary in their offerings, but due to the common platform of the web, there is little to no proprietary functionality. Each company tries to make it easy to add their shopping cart feature into a merchant's web site, so it is relatively easy to switch. Merchants can therefore jump to a slightly advantageous competitor offering on a whim, even through the merchant's can't negotiate price and features. In many cases, merchants offer their customers a choice of e-payment companies. The threat of substitutes: High. 4.2.4. Suppliers The banks and the few competing credit card companies have very little variety in their products and services, partly due to customer expectations, and partly to government regulations. Because the e-payment companies are relatively immature and still represent only a fraction of the overall credit card payment industry, they have little control over the rates. The bargaining power of suppliers: High. 4.2.5. Industry competitors Each competitor in the e-payment industry is battling for the fraction of market share left from industry leader PayPal. The general strategy is to enter market niches, attempt to dominate that niche, and move on to the next. Google has the corporate might to go head-to-head against PayPal, albeit with fewer features initially. Other than Google, each competitor is trying to stay under the radar of PayPal, and steadily adding technological features to their offerings. A definite Google advantage is the ease of shopping cart integration into existing websites, which is slightly better than competitors. Because e-payment systems require trust on the part of the merchant's and merchant's customers, a transparency of services is required, and a pristine reputation is critical. Branding is important as recognition for integrity. The competitor climate: Technological features and branding are vital for success. 4.3. Value proposition Value Propositions help paint a scenario of needs from the customer's (in this case, the merchant's) viewpoint. It is a condensed version of a vignette involving the customer actions regarding a product or service. The vignette here, like in a scene from a movie, would be of an on-line merchant whose customer is on their site and wanting to buy something. The customer needs to pay using a credit card, and the merchant is trying to keep payment transaction costs low. The vignette would expand to include set-up and security issues, and even reasons compelling the merchant to continue using Google Checkout. Fig. 4 shows a typical Value Proposition that answers the merchant's question, “What can Google Checkout do for me?” From this Value Proposition, Value Drivers such as Payment Service, Nominal Costs, Secure and Convenient Payments, and Short Set-up process are just a few of the many Drivers determined using the Value Proposition Template. Often, more than one Value Proposition can be created from other vignettes, and a list of Value Drivers can be determined from each. Another scenario that's possible in this context is one from the merchant's customer's perspective, and answers the question, “How can Google Checkout help my customers?” These Value Drivers will be compared to the categories from the Competitive Features List.
Fig. 4. Example Google Checkout customer value proposition.
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Fig. 5. E-payment industry competitive features list.
4.4. Competitive features matrix Fig. 5 shows the list of Competitive Features from the services offered by companies in the e-payment industry. Some of the companies have a list of features for the service they offer, and some had to be purchased or demoed to determine the feature set. The features are then grouped into related categories. In this case, Customer Service, Payment Processing, Shipping and Handling, Store Integration, Fraud Protection and Security, Advertising, and Pricing are apparently the important features to both the companies and their customers. If a feature is announced but not yet available, it might be included with a caveat. Having an idea of the relative market share also helps to apply a weighting on the features offered. The features offered by industry leader PayPal, for example, would be the standard set of features necessary to compete head-to-head with PayPal, at least when comparing functionality. Service, support, warranties, branding, etc., might be another consideration, and could be included in the features list, too. 4.5. Perceptual map As stated in the Introduction, because of the sheer number of Market Drivers that have been derived, and the desire to make this case a comprehendible example of the roadmapping process, only the drivers and services connected to Fraud Detection and Security will be presented here. Some drivers and services that aren't directly related to security are mentioned because they are needed as a prerequisite for other security drivers and services. Other non-security related drivers connected with their respective categories could be analyzed using the same process as Fraud Detection and Security. The Perceptual Map is used here to prioritize each of the security drivers taken from the Value Proposition and the Competitive Features Matrix. Other sources from the literature have also been used to correlate findings and project future expectations, such as “Staff Study 175 of the Federal Reserve System” regarding electronic payments done in 2002 [41], the Federal Reserve Bank of
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Fig. 6. Fraud detection and security perceptual map data.
Kansas City “2006 Payments System Briefing” [42], and an extensive analysis done by the Australian Government on “Future Electronic Payments Markets” [43]. The Market Drivers related to Fraud Detection and Security are listed in Fig. 6. From the Value Proposition, Features list, and the literature, these Drivers have been given an Importance number relative to each other, and reviews and analysis of the e-payment competitors were done to determine how well the industry performs in meeting the importance expectations. Fig. 7 graphs the Importance versus the Performance Gap (I to P Gap) of expected performance. Normalized Importance minus Normalized Performance determines the I to P Gap. In the upper-right quadrant of the graph are drivers that are of high importance and also where expected performance is inadequate. These drivers are where a competitor could concentrate their efforts to maximize their impact on the e-payment market. The left half of the graph shows drivers that are performing better than expected (and needed). Competitors should investigate to determine if there is wasted effort. The lower half of the graph shows drivers of lesser or secondary importance. But even features of lesser importance indicate a market opportunity if their gaps are positive. The next step in the process is matching the existing or potential feature categories, which are the services offered, to the drivers. New services may need to be created for some not-yet fulfilled drivers. Often, some services apply to more than one driver. The service-driver match up worked out as shown in Fig. 8 and the top two levels of the Fig. 15 roadmap. The order of the services was initially organized with current offerings on the left of the diagram, and future services or enhancements to the right. The final order of service offerings will be determined later as a combination of driver priorities, applicable services, technology availability, and project or acquisition development time.
Fig. 7. Importance to performance perceptual map of security drivers.
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Fig. 8. Service-driver match.
4.6. Delphi pairwise comparison A Delphi Pairwise Comparison model (PCM) is applied to potential security technology candidates that were suggested in the literature [41–43]. The goal at this step was to provide weightings that are to be used when comparing technologies against customer criteria and External Environmental Variables. Eventually, a “winner” will be determined from the evaluation at each time period and applied to the development of services. The candidate security technologies are: • • • • • • •
Secure Sockets Layer (SSL) Two factor security Passmark protection Biometrics PK encryption Encrypted databases PC fingerprinting
Again, grouping is necessary to compare each technology's merits and applicability. Four common factors used in evaluating security technologies were found and used in the PCM: (1) Reliability, (2) Customer Involvement, (3) Data Exposure, and (4) Decryption Difficulty. Pairwise comparisons were made using the same common factors, but each comparison was done in relation to three different criteria, important to the customer: (1) Capability, (2) Convenience, and (3) Confidentiality. This was done to provide weightings to the evaluation of technologies against customer criteria. Fig. 9 shows the expert opinions given to the Delphi Pairwise Comparisons of the four technology factors related to the three external customer criteria. The PCM is only used to determine the relative weightings to be applied to evaluating a technology in each time period. Because each time period has different external criteria, the weightings will be different in each time period. The factor weightings are combined with the variable criteria weightings and applied to the candidate technologies. Fig. 10 shows the entire combined TDE Microsoft Excel model, with the PCM in the lower half and right side of the model, the Hierarchical Decision Model in the upper center, and the TDE graph in the upper left. The Excel model is universal, and can be used to compare any technologies in any categories. The PCM also incorporates scale correction so that each factor is distributed using the same scale across all criteria, so the combinations of factors and criteria can be compared. 4.7. Analytic hierarchy process A Hierarchical Decision Model (HDM) using an Analytic Hierarchy Process (AHP) is used to pick the best technology for each time period based on the external criteria. Each factor is evaluated using the weightings from the PCM against the external criteria. Fig. 11 shows the Excel cells where the results are displayed, and Fig. 12 shows the calculations at each time period and the results based upon the expert scores given to each technology for every common factor.
Fig. 9. Pairwise comparison of security factors.
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Each time period for this Google Checkout model is six months, starting in the first half of 2008. The choice of a particular time interval is entirely arbitrary, and could be different in each case. Because the online services industries have rapid technology development, one year time periods was deemed to be too long, and the six-month intervals matched the development cycle better. Every candidate technology is given a relative score for each common factor, then normalized, and multiplied by the factor weighting for the time period. The scores are added and the technology with the greatest score is judged the best for the time period. For the time period three shown in Fig. 11, the weighted results are shown in Fig. 12 where Encrypted Databases are the best choice given the criteria for time period three. An important attribute of each technology is the time period when it is expected to be available, either coming out of development or acquired through other means. No ranking score is given for those technologies that won't be available until a later time period. 4.8. Technology development envelope Fig. 13 shows the External Customer Criteria used at each time period. More time periods can be added, if needed. The three criteria chosen for security technology are Capability, which is an indication of the importance of security performance is to the customer; Convenience, which is in indication as to how important security ease-of-use is to the customer; and Confidentiality, which covers the customer's perceived value of the protection of user data and identity. Also shown in Fig. 13 are the results from successive time runs of the AHP. The rankings from Fig. 12 are tabulated for each time period, and used to create the Technology Development Envelope (TDE) graph shown in Fig. 14. The graph shown in Fig. 14 shows the results of the AHP process applied at successive half-year time intervals starting in January 2008. The technology at the top in each time period is the most applicable to the solutions, or services in that time period. As previously mentioned, some of the technologies are not yet available for a given time period, and therefore has a relative value of zero. Also, because the value of each technology is relative, often the second or third best technology can still be very applicable for use in a solution. 4.9. Technology roadmap The goal of the technology roadmapping process is the production of a technology roadmap. Although there are many ancillary advantages to the roadmapping process, such as gaining knowledge regarding the industry, most of the literature defines the end goal as some sort of technology deployment plan. Fig. 15 shows a technology roadmap of the security technologies needed to satisfy related market drivers in Google Checkout. After the placement of technologies in the Technology layer of the roadmap, R&D projects were planned to satisfy either the development or acquisition of the related technologies. The placing of items and linkages were done after all the prior steps were completed — the R&D Projects layer of the roadmap includes specific projects to develop 2-factor, PC Fingerprinting, Passmark, and Biometric technologies. Technology integration projects are specified to install both the developed and acquired technologies into existing and new services. More mature technologies available off-the-shelf from third party vendors include SSL, PK Encryption, and Encrypted Database. These technologies might be better acquired than developed possibly because of pre-existing relationships with vendors, or intellectual property protection, or simply that it wouldn't be cost-effective to develop in-house. These acquisitions, as well as R&D project development headcount, are shown in the Resources layer of the roadmap. In this Google Checkout security technology case, the Resources layer includes financial resources and human resources. The duration of the roadmap is arbitrary, but was cut off at three years because of the potential for unreliability of projections beyond that. In other roadmaps involving technologies of dynamics different from web technologies, the duration might be longer or shorter depending on the confidence in the projections. In the case of Google Checkout, it might make sense to extend the duration another six months bi-annually, so that a three-year projection window is always maintained. 5. Discussion Much of the literature used regarding technology roadmapping contained very little on services, as opposed to products, and even less on web services. In addition, even through some cases were discussed, it was either only a small piece of the overall roadmapping process, or the case didn't show tools that would enable a roadmapping recipe to be created. The three main areas of literature reviewed – roadmapping, marketing, and decision-making – had very little overlap. That is, few articles on roadmapping have marketing discussions; few articles on decision-making had roadmapping discussions, etc. But the articles were mostly complete within their own areas, and it was a straightforward task to tie them together. The literature was tied together through the methodology discussion. There could have been even more tools introduced to further enable the roadmapping process, especially within the marketing realm. But there appears to be sufficient overlap that can be used to crosscheck the reliability of the results from each tool. Another tool that might prove useful is the Quality Function Deployment (QFD) correlation matrix, which is useful to connect customer requirements to engineering specifications. The impact of one element on another is also evaluated, so that each is not analyzed in isolation. The QFD could be applied between the Importance to Performance Gap driver perceptual map and the Delphi Pairwise Comparison technology analysis.
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Fig. 10. Complete security TDE, AHP, and PCM Excel implementation.
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Fig. 11. Security technology HDM.
The case presented just one way to produce a service technology roadmap; that wasn't quite top-down, but not quite bottomup, either. In application, none of the levels of the roadmap could be completed in isolation. For example, the time ordering and connections of the solutions in the Products/Services layer of the roadmap could not be accomplished until the technologies were evaluated. But the potential technologies could not have been nominated without target solutions. The case demonstrates that this is not an impasse, and that the tools work when applied to the process one step at a time. Even when a level is incomplete, such as in the example of the ordering and connections of the Solutions above, following the process and continuing to the next step allows for further refinement and eventual completion of previous steps. The three external Criteria are very malleable, and are expected to be continuously adjusted depending on changes in the environment. If, for example, there was a breech in customer data, such as credit card or medical information released on the web with a lot of accompanied bad press, customer concerns over confidentiality may increase at an accelerated rate. These values should be revisited often and updated as new information becomes available. In that way the TDE can be kept current and relevant. This case reveals many areas for potential improvement of the roadmapping process and where further study might be warranted. The Delphi expert opinion process has recently been under attack from a number of sources, such as in Ian Ayres book, Super Crunchers: “So humans are not only prone to make biased predictions, we're also damnably overconfident about our predictions and slow to change them in the face of new evidence.” A possible improvement to the reliability and overall confidence of the AHP model might be realized by using a data-driven decision-making approach in place of expert opinions. Another possible expansion to the process to improve confidence in the completeness of the process might be to include user scenarios, or vignettes, prior to the work on value propositions. Doing user scenarios could prove to be an important tool to ensure the inclusion of all possible relevant user needs, so that the derived solutions are more complete. The AHP model might be improved by adding another level of abstraction to the hierarchy to include external industry influences above technology factors and user criteria. Perhaps a level detailing the amount of competition from one time period to the next, to take into account company acquisitions and purchases. Or the amount of R&D funding could influence the rate of technology development. This new level might also track the external impact of changes in hardware technology or other external influences. Employing a Quality Function Deployment (QFD) correlation matrix, as mentioned above, might also provide a more reliable and complete picture. Even through the case represents only a fraction of the offering of the Google Checkout technology roadmap – namely fraud detection and security – roadmapping the entire offering may not require an identical amount of effort for each part. There could
Fig. 12. Security technology weighted value results.
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Fig. 13. Criteria and results for each time period.
be considerable leveraging of research and data acquisition from one part that can be applied in subsequent parts. A follow-on study might be to detail the process of combining roadmaps for different parts of the offering to paint a complete picture of Google Checkout technologies. Further effort will be needed on the practical implementation of the approach presented in this paper. Such approaches have been proposed in the prior research [44–47]. 6. Conclusions This paper had multiple objectives. The main objective was to develop an integrated process of technology roadmapping introduced as value roadmapping resulting in a Value-Driven Technology Roadmap. The paper accomplishes that goal by integrating decision making and marketing tools. Secondary objective of the paper was to demonstrate the applicability of the process. This was accomplished by using the process to predict the technologies, and, in particular, software security technologies, in the deployment of a web-based shopping cart service called Google Checkout. Many other studies have established a process for product planning, fundamentally based on the T-Plan process. In this application of the process, however, Google Internet services and technologies are forecast instead of products. The process of creating a Value-Driven Technology Roadmap (VTRM) begins with a current assessment of company's internal capabilities, as well as the external industry environment. The goal is a complete Technology Roadmap, hopefully with processes in place to update the roadmap when a significant change in the company or environment is quantified. Starting with the current assessment, the purpose of doing a SWOT analysis and Five Forces analysis is to create a foundation for a Value Proposition. The Value Proposition leads to the Value (Market) Drivers used to build the first (top) level of the Roadmap. The Features Matrix completes the Market Drivers level of the Roadmap. The Perceptual Map connects and compares the Drivers with the Solutions, and depicts the Gaps prevalent in the Solutions, which are added as the second level of the Roadmap. These Gaps identify new or improved Features needed in the Services. The Delphi Pairwise Comparison utilizes expert opinion regarding the suitability of potential Technologies in addressing the needed Features, and scores are awarded to each potential Technology in addressing the Factors needed for the Service features. An Analytic Hierarchy Process (AHP) is employed to evaluate performance of each prospective Technology when tested against external customer Criteria. The External attributes can change at each time period, which will affect the Object scoring of Technologies. In addition, emerging technologies may not be available until a later time period and must be scheduled to build or acquire to coincide with when the Technology is needed. The Technology Development Envelope (TDE) plots the scores from the AHP at each time period, and the highest scoring Technology is the best fit for the variables available at that time period to satisfy the Solutions (or Services) needed. Each Technology requires Resources to either build or acquire, and that information is added to the bottom level of the Roadmap. The Roadmap process must be iterative, so that when new data is available that might affect the roadmap, the TDE should be revisited to create a potentially new roadmap which incorporates the latest findings.
Fig. 14. Security technology TDE (vertical axis — relative value).
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Fig. 15. Technology roadmap.
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The practical application of the roadmapping process is eased considerably by a selection of appropriate tools, and the applicability overlap has a large impact on the confidence and reliability of the results. But while the case of roadmapping Google Checkout security technologies appears successful, there is considerable room for improvement and extensions. Only time will prove the accuracy of roadmapping predictions. But the TDE should be updated and continuously rerun as more current data becomes available, and, just as weather map projections are continuously updated, a technology roadmap should never be regarded as definitive and complete. Prior research documents advantages of several technology evaluation methods [48–51]. A similar review would help identify strengths and weaknesses of our approach. The case provided has not been implemented. Future research can focus on a case implemented in an industry setting capturing the advantages and disadvantages of the proposed approach.
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