6 The Deployment of Technology

6 The Deployment of Technology

The Basic Problem Now that w e have a feel for h o w technology is created—through a process of applied research and d e v e l o p m e n t — w e need to understand h o w technology moves f r o m being the property of its creators to the property of its users. T h e purpose of this chapter is to describe: 1.

how technology developers frame the problem of deployment

2. how they define and structure mechanisms for c o m m u n i c a t i n g their technological ideas to potential users 3.

how different k i n d s of i n f o r m a t i o n sharing are (or are not) compatible with the contexts in w h i c h they are used.

In this b o o k , the w o r d technology embodies not only physical artifacts but social a n d organizational behavior as w e l l ; in fact, the former is often the less important aspect. A s w e shall see, the key process of technology deployment is not only the placement of p h y s i c a l artifacts into users' hands but the communication of the knowledge needed to use the artifacts effectively. U n f o r t u n a t e l y , technology deployment is a field of study that suffers f r o m an unfortunate choice of w o r d s and descriptive metaphors ( E v e l a n d 1 9 8 6 ) . In fact, our relatively neutral term technology deployment may be s o m e w h a t foreign to readers w h o are more f a m i l i a r w i t h terms such as technology transfer, diffusion, or dissemination. I n o u r o p i n i o n , these latter terms are too e n c u m bered w i t h p r i o r a n a l y t i c a l and metaphorical baggage to be useful. F o r e x a m ple, diffusion has often been associated w i t h a passive, m a r k e t penetration approach to the issue. D i f f u s i o n studies have carefully monitored h o w adopters of technology can be categorized as early or late, w i t h limited regard to economic, o r g a n i z a t i o n a l , a n d h u m a n processes. T h e users of dissemination as a metaphor have too often ignored the m u t u a l interests of developers and users that w e w i l l try to describe in this and subsequent chapters. T h e dissemination approach implicitly assumes that a specific technology is needed, This chapter w a s written J . D . E v e l a n d and L o u i s G . T o r n a t z k y .

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and that the m a i n task is to persuade people to use it. Technology transfer, w h i l e a c o m m o n l y used t e r m , also has a host of nuances, not the least of w h i c h is the image that technology is something that is p h y s i c a l , comes in large crates or on pallets, and gets literally moved f r o m place to place. Despite the risk of coining yet another metaphor, w e propose to use the more inclusive and less encumbered notion of deployment.^ O n e problem w i t h the field of technology deployment, as w e have defined it, is that it has a l w a y s been a n area strongly afflicted w i t h w h a t w e earlier called the " p r o - i n n o v a t i o n b i a s " — t h e idea that more technology is better. W h i l e perhaps partially true at the societal level, this notion is demonstrably false at the level of the i n d i v i d u a l user and of the user o r g a n i z a t i o n . It also tends to induce an a n a l y t i c numbness, in w h i c h systems for deploying technologies take little account of ultimate users. T h u s , a m a j o r burden of this chapter w i l l be to develop an understanding of the m u t u a l i t y of the process, of the importance of developers' k n o w i n g w h a t customers w a n t and responding effectively. T h i s process of understanding users' w a n t s proceeds at several levels, at least in effective deployment systems. T h e s e range f r o m the one-to-one interaction between a d r u g salesperson and a p h y s i c i a n , to the more c o m p l e x and protracted relationship between a systems house and a factory installing a new m a n u f a c t u r i n g line. U l t i m a t e l y , these interactions get abstracted into demographic and need profiles that presumably characterize h u n d r e d s , thousands, or m i l l i o n s of s i m i l a r episodes. T h e s e abstractions are called m a r k e t s . G o o d technology deployment cannot exist apart f r o m good technology deployment m e c h a n i s m s , and it is an additional task o f this chapter to sketch the properties that m a k e such mechanisms " g o o d " in p a r t i c u l a r contexts. W h i l e deployment is essentially a c o m m u n i c a t i o n process, the understanding of deployment mechanisms extends far beyond a competitive analysis of face-to-face versus p r i n t , versus electronic media approaches to transmitting i n f o r m a t i o n . E a c h of these is likely embedded in a fairly c o m p l e x w e b of transactions—legal, f i n a n c i a l , and logistical. In this chapter w e first outline some of the properties of deployment as social interaction and discuss some of the vocabularies that have been developed to m a k e sense of the process. W e then suggest a simple model that interrelates technology, contexts, and mechanisms. After defining the different components of this m o d e l , w e w i l l conclude w i t h some c a u t i o n a r y notes about how the performance of technology deployment systems should be judged.

Models of Social Interaction in Technology Deployment A l l technology deployment involves the c o m m u n i c a t i o n of ideas, a n d all c o m m u n i c a t i o n s y s t e m s — i n c l u d i n g those specializing i n technological infor-

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mation—are sets of relationships between people. T h e s e relationships include not only the content of the i n f o r m a t i o n being s h a r e d , but the positions of the actors in their separate a n d shared social contexts. It is through these individual relationships that connections between organizations are structured. The roles taken by the participants in these relationships m a y be described in different w o r d s reflecting differing contexts. I n the technology deployment framework, salesperson/customer, e x p e r t / n o v i c e , consultant/client, and teacher/student are all w a y s of describing relationships between the people involved, as w e l l as suggesting v a r i o u s c o m m u n i c a t i o n channels along w h i c h technological i n f o r m a t i o n is m o v e d . A s M a n s f i e l d ( 1 9 8 5 ) has s h o w n , these channels can be relied upon to t r a n s m i t even highly sensitive i n f o r m a t i o n within relatively short periods of t i m e . T h e s e relationships may v a r y considerably in depth, intensity, length, and a number of other dimensions. W h a t are the implicit models embedded i n these v a r i o u s interactions? For many years the field of technology deployment has been dominated by so-called center-periphery models of c o m m u n i c a t i o n (Schon 1 9 7 1 ) . In such models it is assumed that the center is the source of i n f o r m a t i o n not available to outsiders, and the object is to set up channels for c o n v e y i n g that i n f o r m a tion as expeditiously as possible f r o m those that have it to those w h o do not.' For m a n y purposes, center-periphery systems are thoroughly appropriate and effective. W h e r e the technologies being deployed are discrete, relatively u n e q u i v o c a l , easily v a l u e d , and of obvious advantage, there is a lot of parsimony in this v o c a b u l a r y . F o r e x a m p l e , m a n y consumer products are of this type. It is relatively clear h o w to use ( a n d for w h a t purposes) a new action figure m i l i t a r y toy or a classical m u s i c compact d i s k . Intense interaction between developer a n d user is not needed. R a t h e r , depending upon the size and breadth of the potential user g r o u p , w e simply need to select the m i x of media that i n f o r m s the m a x i m u m number of users about the product. T h e field of m a r k e t i n g has made very profitable use of center-periphery models and has developed extensive refinements to them that can find an audience for anything f r o m a m a i n f r a m e computer to a c a n opener. O n the other h a n d , w h e n issues of advanced technology are i n v o l v e d , such center-periphery systems m a y be less than o p t i m a l . A s w e have noted, technological i n n o v a t i o n if often more a process of shaping the idea of the tool and the idea of its possible uses between developer and user, rather t h a n s i m ply an insertion of a tool into an appointed slot. T h e r e is a l w a y s a degree of " r e i n v e n t i o n " ( R i c e a n d Rogers 1 9 8 0 ) , o f users t i n k e r i n g w i t h even highly specified tools i n the process of m a k i n g them part of the user system. I f the deployment system is not attuned to sharing i n f o r m a t i o n in reciprocal w a y s , the process can become frustrated. Boyle's ( 1 9 8 6 ) study distinguished a v a r i ety of barriers between participants i n transfer activities ( p r o d u c t , institutional, and c o m m u n i c a t i o n s ) , any one of w h i c h is capable of seriously obstructing an interface between potential c o l l a b o r a t o r s . ' A s v o n H i p p e l (1988) has s h o w n , users often have i n f o r m a t i o n w i t h i n their systems that is

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critical to the ability of developers to m a k e better tools—not only information on sometimes ephemeral customer needs, but solid technical data that can enrich the tool development process. ( T h e term users needs to be understood as a catch-all t e r m , i n c o r p o r a t i n g not only end-consumers but all those in the m a r k e t i n g c h a i n as w e l l — e s s e n t i a l l y , those whose focus is o n w h e r e the product or process goes rather t h a n w h e r e it came from). In fact, m a n y companies that m a k e technologically sophisticated consumer goods k n o w that the earliest buyers of n e w products are people who love new gadgets, and w h o are themselves knowledgeable about technologies. A n explicit strategy is to get early a n d detailed feedback f r o m such users, and to modify the product accurately.

Thirty Below in the Boardman Valley

A few years ago one of the authors of this chapter was involved in a project that illustrates the strengths (and limitations) of early user involvement in technology refinement. He was part of a 3-person expedition that planned to skicamp a 120-mile trail in northern Michigan. A deal had been cut with a national backpacking equipment company to provide gear at "VIP discount," if expedition members did a written evaluation of each piece of equipment taken on the trip. This process definitely worked to spotlight strengths and weaknesses. For example, it became very clear to expedition members that the buckles and fastenings of a new pack were impossible to manage with mittens on (a distinct disadvantage in cold weather). A set of sunglasses fit so tightly that they immediately steamed up under the strenuous pace of cross-country skiing. Other equipment performed flawlessly, and the developer/manufacturer was so informed. The four-man dome tent, combined with winter sleeping bags, provided a home away from home. In addition, the four liters of 100-proof liqueur that were taken were portrayed to its manufacturer in the evaluation report as an exemplary "high calorie nutrient or field embalming fluid." However, there are limits to the utility of user's feedback, particularly when the user employs a technology in inappropriate applications. One member of the expedition was naive enough to bring a blow-up air mattress to sleep on. The third night out (at thirty degrees below zero) as the party was encamped in a narrow ravine, it was awakened by a pop, pop, pop. The air mattress had frozen into a hollow popsicle, and the weight of our friend was rapidly reducing it to a flat skeleton of its former self.

The has been measure (Rogers, channels

pattern o f users a n d developers sharing i n f o r m a t i o n reciprocally noted in agricultural research a n d is probably responsible i n large for the long-term effectiveness of the A g r i c u l t u r a l E x t e n s i o n System E v e l a n d a n d Bean 1 9 7 6 ) . It is clear that there is a need to set up of interaction between technology developers a n d technology users

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in the early stages of d e p l o y m e n t / channels that go beyond the limits of product data and product delivery. Since the late 1970s significant interest has arisen in models of developer/ user communication that deemphasize the center-periphery properties and emphasize instead the n e t w o r k of interconnections, of different types and on different levels, that tie the multiple members of both groups together ( H i l t z and T u r o f f 1 9 7 8 ) . N e t w o r k models clearly subsume center-periphery models as a special case but have the added advantage of emphasizing the interactivity and reciprocity of different k i n d s of i n f o r m a t i o n f l o w s over t i m e . ' T h e bulk of this chapter w i l l be based o n the concept of technology transfer as the exchange of i n f o r m a t i o n w i t h i n c o m p l e x organizational and social n e t w o r k s of relationships.

Center-Periphery versus Network Approaches to Deployment

A few years ago two of the authors were involved in an effort that can be understood as a set of experimental comparisons of the relative efficacy of centerperiphery versus network approaches to deployment. The innovation was a social technology, involving a program for the community treatment of chronic mental patients (described in chapter 2). It was a complex approach, which involved setting up a corporation, a patient-run business, a self-governance system, medication monitoring, and so on. As a result, this was not a turnkey social technology, and took many person-months to establish. Over an eight-year period several experiments were run on what amounted to the entire population of mental hospitals in the United States. These experiments compared different communication channels (written materials, workshops, participative demonstrations), different technical assistance approaches (do-it-yourself manuals versus consulting versus consulting with organization development built in), and various degrees of participative decision making among users. The findings were theoretically consistent: every approach that was more intensive, more interactive, and more reciprocal was more effective in fostering use. All of the results could be construed as supporting a networking approach (Fairweather, Sanders, and Tornatzky 1974; Tornatzky et al. 1980).

H o w e v e r , first w e w i l l describe h o w these n e t w o r k models have evolved f r o m earlier conceptions of the deployment process, p a r t i c u l a r l y those that rest on notions of diffusion and dissemination of technology.

An Innovation-Based Model: Diffusion Analysis The most basic a n a l y t i c a l model that has been applied to the processes o f technology deployment is w h a t has come to be called the classical d i f f u s i o n

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m o d e l . Rogers ( 1 9 8 3 ) has provided an extremely complete s u m m a r y of its history and development. It is sufficient to note that the model emerged out of pioneering research studies of the use of h y b r i d seed corn among farmers ( R y a n a n d G r o s s 1 9 4 3 ) and has subsequently found applications i n virtually every area of technology deployment and i n n o v a t i o n research. D i f f u s i o n is defined as "the process by w h i c h an i n n o v a t i o n is communicated through certain channels over time a m o n g the members of a social syst e m " (Rogers 1 9 8 3 , 5 ) . T h e k e y w o r d s here are innovation, communicated, channels, time, and members. E a c h of these poses certain problems that, given the ubiquity of the diffusion v o c a b u l a r y , it w o u l d be w e l l to examine. F o r one, the diffusion approach relies for its a n a l y t i c a l rigor o n the presence of a definable unit of i n n o v a t i o n that c a n be bounded and assumed to be more or less constant across the system under study. T h e i n n o v a t i o n itself is the focal point of the a n a l y s i s , a r o u n d w h i c h all else revolves. T h e approach also assumes a determinate number of c o m m u n i c a t i o n channels (less than the full b a n d w i d t h of those a v a i l a b l e ) , an act of adoption of the i n n o v a t i o n that is simple a n d u n e q u i v o c a l , a n d a population of potential adopters that is both definable and more or less equivalent. B l a c k m a n ' s ( 1 9 8 6 ) review of the uses of diffusion models noted the k i n d s of spatial and temporal assumptions that need to be made to take proper advantage of the algebraic properties of empirical analyses of d i f f u s i o n . B r o w n ( 1 9 8 1 ) presents a more complete review of the origins, l i m i t s , a n d advantages of d i f f u s i o n models, noting in particular their implicit geographical metaphors and their relationship to m a r k e t analysis and conceptual, as w e l l as e m p i r i c a l , territory. I f these assumptions can be made ( a n d in m a n y cases they c a n , p a r t i c u l a r l y for technologies intended for mass-markets) then some very a m a z i n g things can be done w i t h mathematics to predict the behavior of such systems and the spread of innovations through them ( H a m b l i n 1 9 7 3 ) . T h e ubiquity o f the logistic curve to describe adoptive behavior w i t h i n a population is one by-product of this line of a n a l y s i s . T h e diffusion model has contributed t w o m a i n sets of classifications to the understanding of technology deployment. F i r s t , there are the attributes of innovations (mentioned in chapter 2 ) that are ostensibly related to their adopt i o n : relative advantage, c o m p a t i b i l i t y , c o m p l e x i t y , t r i a l a b i l i t y , and observability. T h e rate of adoption presumably depends o n some interaction of these features of the i n n o v a t i o n w i t h relevant features of the user population in question ( E v e l a n d et a l . 1 9 7 7 ) . O n l y a few of these attributes—particularly c o m p l e x i t y and c o m p a t i b i l i t y — h a v e a relatively consistent relationship to adoption behavior ( T o r n a t z k y a n d K l e i n 1 9 8 2 ) . Second, there is the classification of adopters themselves into categories according to the point in time they adopted the i n n o v a t i o n relative to w h e n they might have: i n n o v a t o r s , early adopters, early m a j o r i t y , late m a j o r i t y , and laggards. I n the d i f f u s i o n f r a m e w o r k , each of the t w o categories—innovators

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or laggards—is presumed to have somewhat different characteristics and to respond to appeals differently. T h e r e is also a tendency to categorize i n d i v i d uals for life (once a laggard, a l w a y s a laggard) rather t h a n in relation to specific innovations, w h i c h w a s the original use of the t e r m . T h e s e categories have become deeply ingrained i n i n n o v a t i o n research and are frequently used without thought as to their relevance. In some cases labeling people in one or the other category ignores the fact that "false positives" can o c c u r , or that the presumed linear progression f r o m one category to another may not happen, and often for good reasons. Some adopters may never get to i m p l e m e n t a t i o n — the adopted equipment m a y sit forever in the warehouse or m a y be pulled out of a production line a n d tossed in the scrap y a r d .

The Sad Case of Machine Vision

In the late 1970s and early 1980s, what appeared to be a revolutionary process technology was introduced to manufacturing. Loosely described as machine vision, it was, technically speaking, a confluence of recent developments in optics, video, and computerized control systems. The machine vision techniques ostensibly permitted manufacturers to gain precise and automated control over the quality inspection of fabricated parts. Many major companies installed machine vision systems, which, not incidentally, were often produced by small R&D-based new companies. Then the trouble began. Venders expected their users to quickly adopt and implement the new technologies and make them an integral part of their production systems. Too often, it didn't happen. Users often did not provide the appropriate training, technical support, and new management practices necessitated by the systems. Vendors were forced to keep their technical staff at vendors' sites for months (or years) at a time, in order to make the systems work as planned. Many plants simply gave up. Some large, and expensive, machine vision systems were "de-installed." Automation consultants, in visits to plants, found unused machine vision systems sitting in boxes, relics of failed deployment.^

Problems arise w h e n the d i f f u s i o n model is applied in situations w h e r e its basic assumptions are not met—that is to s a y , v i r t u a l l y every case i n v o l v i n g complex, advanced technology. L i k e the elephant and the blind m e n , a c o m plex technology means different things to different participants in deployment activities. C o m m u n i c a t i o n channels in complex social systems are h a r d to define, as they function on m a n y different levels simultaneously. A s w e have discussed earlier, it is extremely difficult to determine just w h a t the act of adoption in the i n c o r p o r a t i o n of a complex new technology might be. Is it when a purchase order has been processed, or w h e n an important stakeholder makes a n integral psychological c o m m i t m e n t to the n e w technology.'

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Perhaps the most serious problem w i t h using the diffusion model in relation to advanced technology is that it tends to inappropriately focus analysis (and potential intervention) onto the i n d i v i d u a l . I f one assumes that a single and simple adoption decision is made about an easily defined thing, then it becomes more obvious h o w prone to error this system is. Decisions are often m a n y ( a n d reversed), and technologies are often too big and complex to be grasped by a single person's cognitive p o w e r — o r , u s u a l l y , to be acquired or deployed w i t h i n the discretionary authority of any single organizational participant. Attempts have been made to fit the basic diffusion model to situations in w h i c h adopters are i n d i v i d u a l s , private organizations ( U t t e r b a c k 1 9 7 4 ; Martino, C h e n , a n d L e n z 1 9 7 8 ) , and public agencies (Feller, M e n z e l , and Engel 1974; L a m b r i g h t 1 9 8 0 ) , w i t h limited d i s c r i m i n a t i o n between whether the i n d i v i d u a l or the organization is the real adoption-implementation unit. Too often, data are gathered on i n d i v i d u a l attributes such as the personalities and c o m m u n i c a t i o n patterns of key decision m a k e r s , w h i l e the real outcome of interest (adoption or implementation of technology) is a n organization property, at best only partly affected by the i n d i v i d u a l s in question. W i t h i n this a p p r o a c h , one is either forced to personalize the organizations being studied or to simply assume that populations of individuals a n d populations of organization behave in the same w a y , subject to the same forces ( W a l k e r 1969; G r a y 1 9 7 3 ) . Neither approach reflects reality.

A Context-Based Approach It is the contention of this b o o k that the process of technological innovation cannot be understood w i t h o u t careful attention to the concept of choices within contexts. I n n o v a t i o n is a c o m p l e x sequence of decisions made by many people in different situations, against largely situational c r i t e r i a . Technology deployment—the exchange of information between technology developers and technology users—also takes place w i t h i n constraints. D e t e r m i n a t i o n of the type of deployment mechanisms that most effectively facilitate this exchange m u s t , in t u r n , be grounded in these contexts. In effect, the choice of deployment mechanism is a k i n to balancing a fivefold set o f contingencies. T h e five elements of context that w e w i l l consider are as f o l l o w s : 1. The nature of the technology. A s w e discussed in chapter 2 , technology is a concept that refers to m a n y different kinds of things at m a n y different levels of specificity. Some of the things about the technology that we w i l l discuss as h a v i n g significant effects in relation to deployment processes include its range of potential applicability (that i s , h o w m u c h its use is con-

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Strained by its very n a t u r e ) , its degree of h a r d w a r e dependence, its potential for adaptability, and the level of its " p r o d u c t i z a t i o n . " 2. Characteristics of users. A s it is w i t h potato c h i p s , so it is w i t h technologies: nobody w a n t s to deploy just one. T h e result is that deployers need to take into account the aggregated characteristics of the user of their technology. T h i s c a n operate at several levels. I n the w o r l d of selling and b u y i n g technologies, it means understanding m a r k e t s and the industries to w h i c h one is deploying. A t the level of the i n d i v i d u a l a d o p t i o n , it may mean understanding special needs of users that indicate a prolonged period of postsale interaction (such as the machine vision e x a m p l e in this c h a p t e r ) . 3. Characteristics of deployers. J u s t because an organization develops a technology does not m e a n that there are structures, incentives, and capacities to perform its deployment. F o r e x a m p l e , some R & D organizations may make the appropriate decision to not deploy, p a r t i c u l a r l y as they contract the realities of large m a r k e t s and tough-to-service i n d i v i d u a l users. 4. Boundaries within and between deployers and users. T h i s issue is equally applicable whether the systems in question are entirely different organizations (such as a federal agency and an agency of local government) or parts of the same organization (such as R & D and m a n u f a c t u r i n g ) , or multiple organizations interconnected in some n e t w o r k of commerce ( s o f t w a r e development companies w h o sell a r t i f i c i a l intelligence products to large m a n u facturing equipment vendors w h o design/configure equipment for installation in individual p l a n t s ) . T h e point is that w i t h i n and between organizations there are historically stable relationships, w h i c h m a y or m a y not i n v o l v e technology per se. W e need to understand the degree to w h i c h systems interconnect, and where they do so. It is this operative boundary between the systems that must be crossed w i t h i n f o r m a t i o n . T h e nature and location of this boundary are critical to the choice of deployment m e c h a n i s m s . T h e s e boundaries may be simple interfaces between t w o clearly definable u n i t s , or c o m p l e x sets of interaction a m o n g multiple participants. T h e latter situation is more c o m mon; h o w e v e r , the a n a l y t i c a l problem remains to look at each interface in turn. 5 . Characteristics of communication and transaction mechanisms. There is a w i d e range of possible arrangements for deployment, each of w h i c h has certain inherent advantages and limitations in relation to the other factors. N o t all mechanisms m a y be equally accessible to the parties involved at any given point in time. T h e important point is to be able to relate the transaction arrangements to the other elements of the situation in order to achieve the desired outcomes. In the r e m a i n i n g sections of this chapter, w e w i l l explore each of the elements of this f r a m e w o r k in more depth, l o o k i n g at w h a t aspects matter most in terms of achieving an effective and satisfying (to both deployers and users)

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exchange of technology ideas a n d practices. It is i m p o r t a n t to remember that, w h i l e this is a n e m p i r i c a l l y based conceptual a p p r o a c h , the state of the underl y i n g data and theory is often relatively w e a k . W h i l e w e w o u l d like to have a comprehensive a n d validated " c h e c k l i s t " that w o u l d inevitably lead to correct choices of deployment approaches, w e w i l l fall far short of that (Mohr 1 9 8 7 ) . Nonetheless, w e w i l l provide the reader w i t h a m a p to help us see how the different elements of a deployment situation come together, and to suggest that w e almost a l w a y s have far more effective choices in any given situation than we t h i n k w e do (as w e w i l l discuss further later in the chapter). A s we discuss each of the five elements of the m o d e l , there are t w o concepts that simplify the tactical choices that need to be made a m o n g deployment approaches. 1. The dimension of certainty/uncertainty. A n y deployment campaign must deal w i t h the reduction of ambiguity about the technology being deployed, but it must accomplish this w i t h i n the constraints of resources available, w h i c h become exacerbated in large, ambitious efforts. F o r e x a m p l e , we have depicted deployment as inherently a c o m m u n i c a t i o n process, but what does that imply? C o m m u n i c a t i o n , interpersonal or o t h e r w i s e , is a w a y of resolving/reducing uncertainties (Festinger 1 9 5 4 ) . T h e s e m a y be uncertainties about operations, use, conceptual u n d e r p i n n i n g , expected effects, or whatever. A s w e w a l k through the five elements of our c o n t e x t u a l m o d e l , the reader w i l l be reminded that certain factors either increase or decrease the degree of uncertainty that needs to be resolved, a n d , correspondingly, the intensity or i n f o r m a t i o n richness of the c o m m u n i c a t i o n that needs to occur. 2. Scope. E a c h of the elements of context (users, technology, deployers, and boundaries) w i l l either e x p a n d or contract the scope or magnitude of the deployment task. Scope m a y be a function of the n u m b e r of user firms, the n u m b e r of i n d i v i d u a l stakeholders, or the sheer v o l u m e of information that must be t r a n s m i t t e d . It is easier to sell a b o x of dog biscuits than it is a seeing-eye dog.

Nature of the Technology A h a m m e r is a h a m m e r , but a telescope is a w i n d o w to the universe. W h i l e all technologies are knowledge-embedded tools to extend h u m a n capability, each has different characteristics that have i m p l i c a t i o n s for h o w one might attempt to deploy it. T h e s e characteristics include: 1. 2. 3.

the science involved fragility and efficacy lumpiness and t r i a l a b i l i t y

The Deployment of Technology 4. 5.

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adaptability packaging

The Science

Involved

As we noted in chapter 2 , all technology is rooted in science, in the systematic observation of the observable p h y s i c a l and/or social w o r l d . C e r t a i n k i n d s of science obviously lend themselves better than others to translation into technologies that w i l l have immediate effects on those other than the science's practitioners. M a t e r i a l s science m a y be expected to generate a relatively higher level of transferable technologies t h a n , s a y , radio a s t r o n o m y . O u r discussion in chapter 5 about technological opportunities reflects these differences. W h a t is it about p a r t i c u l a r fields of science that has implications for the deployment of technologies that derive f r o m those sciences? O n e critical area is simply the focus o f the science itself. T h o s e sciences ( a n d resultant technologies) focused a r o u n d phenomena at levels between the molecular and the planetary, and at phenomena that are physically observable, are more likely to be c o m m u n i c a t e d and deployed than those that are not. A s w e w i l l see in chapter 8, m a n y of the key decision m a k e r s in user organizations do not have technical b a c k g r o u n d s , or else their p r i m a r y job function does not involve staying abreast of the state-of-the-art in technology development. D e p l o y i n g a developed technology that is on the fringes of the m a i n s t r e a m demands a much more intense set of i n t e r a c t i o n s — m o r e t a l k i n g , more meetings, more briefings, more education of the potential user group. I n effect, " f a r o u t " technologies, w h i c h derive f r o m relatively obscure scientific specialties, may demand a significant effort at m a r k e t development. T h e position of the social/behavioral sciences w i t h i n this f r a m e w o r k is worth noting. C e r t a i n l y the failure of m u c h social science research (particularly evaluative and policy research) to find an effective audience in user communities ranging f r o m practitioners to p o l i c y m a k e r s has been the subject of considerable anguish over the years ( W e i s s 1 9 7 7 ; C a p l a n , M o r r i s o n , and Stambough 1 9 7 5 ; L a r s e n 1 9 8 2 ) . P a r t of the problem has to do w i t h the subject matter of these fields, w h i c h is largely unobservable and made up of constructs w i t h only l i m i t e d face relevance or is perceived as a fancy restatement of c o m m o n sense. O n e result is that use has tended to be conceptual rather than operational (Beyer and T r i c e 1 9 8 2 ) . T h e s e disciplines are also not part of the m a i n s t r e a m epistemology of decision m a k e r s . W h i l e sciences such as psychology have generated effective and transferable technologies in areas such as personality and intelligence testing (perhaps because the concepts of personality a n d intelligence have face validity to the average p e r s o n ) , the general c o n t r i b u t i o n of social science to technology deployment ( T o r n a t z k y et a l . 1982) has been more in terms of m a k i n g observations about the process itself than in the generation of technology itself ( R i c h 1 9 8 7 ) .

128

Fragility

• The

and

Processes

Efficacy

of Technological

of the

Innovation

Technology

T h e concept of the efficacy of technology w a s discussed in chapter 2. The basic questions here are: Does it w o r k (efficacy)? I f so, w i t h w h a t degree of consistency (fragility)? W h o says so? H o w and against w h a t criteria was this efficacy determined? A c r i t e r i o n for any technology w i t h aspirations for deployment is that it actually does w h a t it says it w i l l d o , w i t h reasonable predictability and few possibilities for catastrophic f a i l u r e . Y e t this criterion is not necessarily easily achieved. O n e problem has to do w i t h instability a n d lack of precision in the core elements of a technology. A n y c o m p l e x , multifaceted i n n o v a t i o n has a small number of core elements ( H a l l a n d L o u c k s 1 9 7 7 , 1 9 7 8 ) that must be replicated e x a c t l y , along w i t h others that are less c r u c i a l . H o w e v e r , in one study of the replication of research-based social technologies ( B l a k e l y et a l . 1983), the core elements were only rarely specified w i t h precision a n d c l a r i t y . Related to the issue of core elements is the question of fidelity to some model of the i n n o v a t i o n . T h a t i s , if a technology is developed i n the R & D setting a n d produces measurable and desirable effects, w h a t is the likelihood that it w i l l yield s i m i l a r results i n subsequent replications and routine use. M u c h of this research has focused o n adaptation/fidelity of social technologies, such as t r a i n i n g p r o g r a m s , treatment regimes, a n d the like ( B l a k e l y et a l . 1 9 8 4 ) , w h e r e fragility and replication are real problems. O n e of the more interesting conclusions is that the fidelity a n d success of use is related to the deployment and implementation approaches that are used. Some of the difficulty has to do w i t h the different environments experienced by the developers and the users. It is too often true that performance in the R & D laboratory is seldom a predictor of performance a n y w h e r e else except in another l a b o r a t o r y . A technology that performs reliably in one setting m a y or may not p e r f o r m equally in another setting. A good deal of the empirical analysis of technologies in terms of deployability has to do with determining performance l i m i t s — t h e conditions that b o u n d its effective performance.

Efficacy versus Appropriability: The Role of Standards

Appropriability of benefits (the ability to make money) is one driving force behind the creation of new technology, and most developers want to capture all or a large share of a market. At the same time, each individual unit or company in that market wants something more prosaic: routine and beneficial use of a technology, which will enable it to accomplish its goals. These motivations often work at cross purposes—a developer company may want to protect the secrets of efficacious use in a monopolistic fashion, at the same time that user organizations may want choices and options among alternate technological solutions to their problems.

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One intervening factor in this dilemma is the role of industrial and technical standards. Standards serve to set boundaries on the range of permissible technology development and follow-on deployment. A developer of technology can come up with any kind of innovation to perform a specific function, but it must also conform to certain generic standards. In an organizational sleight-ofhand, standards force rationality onto markets, with a result that often increases competition and innovation (Tassey 1986). For example, in the field of manufacturing technologies, individual machines and processes are increasingly being controlled by computers. At the same time, there are economic and other pressures to knit together these individual machines and processes into integrated manufacturing systems. The problem becomes how to ensure that the various computers can talk to one another. One standard solution has been MAP (Manufacturing Automation Protocol), which has predominately been a user-driven movement, although the standards-setting process involves a tortuous, lengthy set of technical discussions involving many stakeholders. Ultimately, equipment vendors will begin to have their products MAP-certified, in order to participate more effectively in the market. The vision from the user perspective is that true plugcompatibility will result, akin to putting together various components of a stereo system.

Some of the v a r i a b i l i t y in efficacy is s i m p l y a function of the underlying science and/or materials and e n v i r o n m e n t ; some technologies ( a n d the underlying science) are inherently more probabilistic in nature than others. I f a onepound h a m m e r strikes a one-foot square piece of . 0 1 - i n c h steel at a v e l o c i t y of 50 feet per second, the p r o b a b i l i t y is certain that the steel w i l l be bent; if a large batch of plastic " g o o p " is m i x e d in a n injection m o l d i n g p l a n t , the probability is quite v a r i a b l e w h e t h e r it w i l l result in a perfect batch of dashboards. T h e i m p l i c a t i o n of all this for deployment approaches is that depending upon the fragility a n d efficacy of the u n d e r l y i n g science, some technologies will demand more user h a n d - h o l d i n g d u r i n g deployment. I f core elements are poorly defined and/or difficult to replicate, and if positive impacts are not obvious, this w i l l create uncertainties for the user. Uncertainties can only be resolved—if at a l l — w i t h a lot of dialogue between developer and user. H a n d holding of this sort costs time a n d money.^

Lumpiness

and

Trialability

Lumpiness a n d trialability relate to h o w m u c h of the user's system the technology could potentially affect, over w h a t time f r a m e , and h o w one might go about finding out. Some technologies are " l u m p y " ; that i s , their scope is large; they affect large s w a t h s of the user organization over a long period of time and, consequently, are h a r d for users to absorb easily.

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T r i a l a b i l i t y i s , in a sense, the flip side of lumpiness. Some technologies can be assimilated in a more bite-size m a n n e r — o v e r t i m e , i n c h u n k s , and incrementally. It should be noted that a p r i o r i judgments about scope and trialability are subject to a very high m a r g i n of e r r o r . It is not hard to see w h y — o n e m a y be asked to look at a very complex existing system and to visualize something that is not n o w there. Differences in anticipated versus realized scope (or lumpiness) m a y operate in either direction. A technology that is expected to have major repercussions in a user organization may t u r n out to be useful only in a very limited context;** by the same t o k e n , one perceived by users to have limited effect may t u r n out to be ubiquitous in i m p a c t . F o r e x a m p l e , companies that purchase computerized m a n u f a c t u r i n g systems m a y t h i n k they are a c q u i r i n g a set of technologies that w i l l affect fabrication and assembly only on their shop floor, but soon they find widespread effects. F i r m s that implemented w o r d processing technology in the p r e - P C era frequently found themselves involved in m u c h more significant restructuring of w o r k f l o w s than they had ever anticipated (Johnson 1 9 8 5 ) . T h i s mismatch between anticipated versus realized scope has implications for deployment approaches. F o r e x a m p l e , if the developers/deployers are knowledgeable and honest about their l u m p y technology, they w i l l attempt to bundle a significant a m o u n t of technical assistance and h a n d - h o l d i n g w i t h the h a r d w a r e that they sell; the naive user m a y see only the h a r d w a r e a n d want a turnkey t r a n s a c t i o n . W h a t actually gets transacted w i l l likely be i n between; this w i l l be less than o p t i m a l for both parties. T o some degree, the unpredictability of scope can be dealt w i t h through trial and e x p e r i m e n t a t i o n . A g a i n , technologies differ in the degree to which they can be put to field trials p r i o r to full deployment. I f a f i r m c a n buy one new m a c h i n e , put it in a shop alongside conventional tools, and evaluate its performance against specified c r i t e r i a , then trialability is great. A s L i n k and T a s s e y ( 1 9 8 8 ) have s h o w n , the a v a i l a b i l i t y of clearly defined standards to provide decision criteria to evaluate tools enhances the likelihood of their deployment. It is m u c h harder to experiment w i t h , s a y , a pilot chemical processing p l a n t , and assume that a scaled-up version w i l l operate w i t h the same performance parameters. T h e r e are t w o aspects to t r i a l a b i l i t y : ( 1 ) being able to look at an entire technology over a limited time f r a m e ; a n d ( 2 ) being able to take a slice or c h u n k of a technology, try i t , and then take another c h u n k or slice. T r i a l a b i l i t y is designed i n , and inherent t o , the specific technology. In general, trialability of technologies is progressively harder to attain the larger the behavioral component (Johnson and R i c e 1 9 8 7 ) . B e h a v i o r is notoriously context-sensitive, and the context of a trial is inevitably very different f r o m that of the usual w o r k w o r l d . W h i l e there is m u c h to be said for careful experimentation w i t h advanced technologies p r i o r to full i m p l e m e n t a t i o n .

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many such experiments are misleading. M a r k u s ( 1 9 8 7 ) describes a number of the problems involved w i t h t r y i n g to generalize f r o m pilot deployments of information systems, noting in p a r t i c u l a r that the a v a i l a b i l i t y of a critical mass of users is c r u c i a l . W i t h o u t such a m a s s , the experiment m a y provide falsely pessimistic estimates. I f only a s m a l l number of advocates or a single champion understand the technology as a result of pilot testing a n d ultimate implementation demands use by a group o r team of i n d i v i d u a l s , then d o w n stream problems are l i k e l y .

Adaptability The ease w i t h w h i c h the i n n o v a t i o n can be tinkered w i t h by the user, to match it more closely w i t h its projected a p p l i c a t i o n , is an extremely critical feature. Any technology must eventually be mapped into the user's organization and its personnel a n d procedures. I m p l e m e n t a t i o n , as w e w i l l discuss in chapter 9, is inherently a process of m u t u a l adaptation of the technology to its environment. T o the degree that the burden of all changes and adaptations must be borne by the user organization rather than built into the flexibility of the technology, the process is likely to be m u c h more d i f f i c u l t and susceptible to abortion or ultimate f a i l u r e . Adaptability of use is almost inevitable; h o w easy ( i n personnel, time, and money) it is for the user to m a k e these adaptations i s , in effect, a designed-in feature of the technology. T h e basic ingredients of a personal computer are pretty m u c h the same w o r l d - w i d e . Y e t different computers w i l l v a r y widely on the degree to w h i c h there is a range of alternate functions a n d capacities available, either w i r e d - i n or in the f o r m o f s o f t w a r e . In fact, this inherent multifunctionality is one of the m a i n points in m a r k e t i n g such systems. It should also be noted that adaptability may have necessary constraints. That i s , h o w m u c h can one (or s h o u l d one be able to) adapt a technology before losing its efficacy. A s discussed earlier, the issue o f the importance of fidelity to the developers' concept of the technology versus the ability of the user to adapt and reinvent the i n n o v a t i o n has engaged lively debate, particularly in relation to process innovations in education ( B e r m a n and M c L a u g h l i n 1 9 7 4 ) , health ( K a l u z n y , G e n t r y , and V e n e y 1 9 7 4 ) , a n d evaluation research techniques ( C a l s y n , T o r n a t z k y , and D i t t m a r 1 9 7 7 ) , and to the use of information technology in a variety of contexts ( E v e l a n d , R o g e r s , and K l e p p e r 1977; J o h n s o n and R i c e 1 9 8 7 ) . W h a t is i m p o r t a n t to our analysis at this point is that adaptability of a technology i n terms of h o w it c a n be used, and under w h a t circumstances, simplifies the burden o n the technology deployment system. Users w i l l w a n t to adapt technologies. I f they can do it themselves, all to the good. I f not, and if they need to return c o n t i n u a l l y to the developer/deployer, this increases the costs of marketing/deployment a n d , ultimately, the number of users w h o

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can be served. M o r e o v e r , if the technology is too adaptable (or adaptable in malignant directions, as discussed a b o v e ) , then deployment activities will be preoccupied w i t h postsales maintenance or cleaning up messes.

Packaging T h i s final dimension of technology reflects the degree to w h i c h the subcomponents of the t e c h n o l o g y — a l l its different physical objects and associated b e h a v i o r s — f o r m tight or loose bundles, w h i c h c a n be aggregated or disaggregated in the deployment process, a n d w h i c h correspond (or do not correspond) to aggregated and disaggregated bundles of user needs and desires. F r o m the point of view of developers, w r a p p i n g up a complete package for turnkey deliverability ( w e call this productization) is obviously a desirable objective. It simplifies their deployment responsibilities, puts the major burden on the m a r k e t as a deployment m e c h a n i s m , and cuts d o w n on the degree of messy involvement w i t h the after-sale m a r k e t . F o r m a n y innovations— p r i m a r i l y those of limited scope, high r e l i a b i l i t y , l o w behavioral content, and low a d a p t a b i l i t y — t h i s w o r k s quite w e l l . Users can scan the marketplace and m a k e their decisions to go w i t h one package or another. T h e end point of this process i s , of course, a c o m m o d i t y p r o d u c t , a situation in w h i c h every deployer (seller) offers something that is pretty much the same as every other one being offered. T e c h n o l o g i c a l products can approach c o m m o d i t y status, at least until the next w a v e of development o c c u r s . A s of the late 1 9 8 0 s , consumer T V s have nearly reached this status; h o w e v e r , this quasi-commodity situation w i l l be d r a m a t i c a l l y upset w i t h the a r r i v a l of high definition television ( H D T V ) . Productization as a deployment strategy does not w o r k w e l l w i t h inherently c o m p l e x technologies and where significant a m o u n t s of organizational and social change are likely to characterize i m p l e m e n t a t i o n . T h e larger the bundle an organization is asked to b u y , the more d i f f i c u l t the process of m a k i n g that buy is likely to be. I n effect, inappropriate p r o d u c t i z a t i o n of too large a package reduces the trialability of a technology. T h e user cannot divide adoption/implementation into manageable episodes. A good i l l u s t r a t i o n of the p r o b l e m of t r y i n g to deal w i t h c o m p l e x technologies as single products is to be f o u n d in the experiences of large organizations trying to install advanced i n f o r m a t i o n systems. W h i l e such situations can have effective outcomes, the amounts of time a n d energy expended in trying to keep such complex innovations w i t h i n the bounds o f the package are frequently staggering. W h e n the U . S . Forest Service, first installed its electronic mail system, for e x a m p l e , it constrained all m a i l to f o l l o w explicit organizational hierarchy lines. It w a s not until the U . S . F . S . realized that more effort w a s being spent on t r y i n g to restrict message f l o w s t h a n on t a k i n g a d v a n tage of the potential for lateral c o m m u n i c a t i o n that these constraints were

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relaxed (Stasz, B i k s o n , and S h a p i r o 1 9 8 6 ) . I n effect, these are quasi-products masquerading as the real thing. Whether or not a technology is truly productizable has implications for possible deployment approaches. I f it i s , then it becomes feasible to reach large numbers of users, w i t h n o n - p e r s o n - i n t e n s i v e c o m m u n i c a t i o n m e d i a ; if a technology isn't p r o d u c t i z a b l e , then there is a corresponding need for laborintensive, interactive deployment approaches. In s u m , the attributes of the technology in question have a distinct effect on how it w i l l interact w i t h the contexts of both its developer and its users, and, in t u r n , h o w different deployment mechanisms might be used. Such attributes are neither f i x e d nor determinate; they are a l w a y s capable of redefinition of reinterpretation a n d , in fact, are subject to widely differing perceptions a m o n g the participants in the process. H o w e v e r , they are a useful starting point for l o o k i n g at w h a t is and is not manipulable in the deployment process.

Characteristics of Users There are t w o w a y s of l o o k i n g at user characteristics as they affect the choice of deployment approaches. F i r s t , there is the context of the i n d i v i d u a l u s e r — the set of related goals, roles, expectations, c r i t e r i a , assumptions, technical k n o w - h o w , a n d i n d i v i d u a l a n d o r g a n i z a t i o n a l characteristics that decisively affect the ability o f the person and/or the organization to absorb a n d use the innovation. Second, is the set of characteristics a n d capacities that represent logical aggregations of u s e r s — m a r k e t s , user groups, and so o n . T h e s e m a y represent summative statistics of the first set of variables but usually don't. Individual

Firm

Characteristics

It is evident that the structure and processes of the user organization w i l l affect how different types of technology deployment approaches w i l l be received. In chapter 7 w e discuss in detail h o w different k i n d s or organizational features appear to be related to the ability of organizations to use technology effectively. H e r e w e w i l l simply note that four factors appear to be p a r t i c u l a r l y important in shaping the k i n d of technological receptivity the organization w i l l assume, and w h i c h have implications for the deployment approach to be preferred by the developer o r g a n i z a t i o n . T h e s e include: 1.

size

2.

the resources a v a i l a b l e , w i t h p a r t i c u l a r emphasis both on resources already committed ( s u n k costs) and those u n c o m m i t t e d ( s l a c k )

134 3. 4.

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the conceptual rigidity of the organization the dependence on technology of the user organization

T h e size of the typical user o r g a n i z a t i o n clearly affects its ability to assimilate technology, although size in itself is often a p r o x y for other underlying factors ( K i m b e r l y 1 9 7 6 ) — s o m e of w h i c h , h o w e v e r , have implications for deployment approaches. F o r e x a m p l e , simple o b s e r v a t i o n , as w e l l as systematic evidence, suggests that smaller organizations are likely to be less bureauc r a t i c , more f l e x i b l e , more i n f o r m a l , and so o n . Since the implementation of some c o m p l e x technologies demands major dislocations i n organization functioning, then smaller users may have more capacity to assimilate complex new technologies. A recent study of the deployment of advanced manufacturing technologies provides some supportive evidence ( W i a r d a 1 9 8 7 ) . A m o n g a sample of 1,200 m a n u f a c t u r i n g p l a n t s , s m a l l organizations achieved a much greater depth of implementation (that i s , more machines per each hundred employees) once they had decided to purchase, although their adoption (purchase) rate w a s less. T h a t i s , all things being e q u a l , smaller plants were less likely than larger ones to have a given technology ( c o n f i r m e d by Rees, Briggs, a n d H i c k s [ 1 9 8 4 ] ) , but, if they d i d , they were more likely to deploy a greater number of machines a n d , p r e s u m a b l y , far more applications. W h y do w e find a reduced adoption rate in smaller firms.' T h e answer is probably because size is related to another important user c h a r a c t e r i s t i c resources. Smaller firms and plants are likely to have fewer slack resources, h u m a n or c a p i t a l . T h i s m a y disadvantage them as they search for technological solutions to problems (limited scanning c a p a c i t y ) , as w e l l as i n coming up w i t h the money to pay for t h e m . T h e y are also likely to consume more developer resources in after-sale support t h a n are larger organizations that can more easily develop their o w n internal " g u r u s . " T h e implications for the deployer f o l l o w logically. I f the average user organization is s m a l l , w i t h limited resources, the net cost-of-sales may be excessive. M o r e ( a n d indeed, too m u c h ) may be needed to educate small users and to bring them to the point where a deal is possible. In one study by Swanson ( 1 9 8 4 ) of the w a y s in w h i c h companies seek and use scientific and technical i n f o r m a t i o n , it w a s f o u n d that smaller f i r m s tended to have restricted levels and sources of i n f o r m a t i o n (that i s , a heavy reliance on technology vendors). In contrast, some f i r m s may simply be more dependent on technology for their competitive edge. T h e s e m a y be production technologies, managerial technologies, or others. Some fields are m u c h more dependent than others; this generally reflects the pace of change in the u n d e r l y i n g science, as w e l l as the d y n a m i s m a n d richness of the markets that they serve. T h e greater the dependence of the user f i r m on its technological p o s i t i o n , the more it must be open to technology developed elsewhere (Pelz and H a r t 1 9 8 6 ) , and the more likely it w i l l have in-house technical expertise to receive these new technologies. Since a major element of successful transfer is the ability of developer

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and user specialists to talk to each other w i t h o u t interpreters, the presence of specialists w i t h i n a user organization is a major factor in the ease w i t h w h i c h technologies m a y be developed, as K o z m a ' s ( 1 9 7 9 , 1 9 8 9 ) studies of the i n f l u ence of c o m m u n i c a t i o n n e t w o r k s o n the use of educational innovations have shown. The implication for crafting a deployment approach is that, if the m o d a l user firm has internal capacity to assimilate technology, it reduces the need for technology education as p a r t of the deployment effort. It also is more likely that the potential user w i l l have a " s c a n " capacity, that i s , the ability to have an o v e r v i e w of the available technology, thus reducing the need for information dissemination activities as part the overall deployment a p p r o a c h .

User Characteristics

Aggregated

Developers/deployers do not typically w a n t to sell just one. W h i l e sales/adoptions occur at an i n d i v i d u a l user level, the deployers attend to the important characteristics of groups of users. I n s h o r t , they look for the characteristics of their markets. One characteristic is the size, in terms of number of economic units that are potential users. A l l things being e q u a l , if a deployer organization must reach an audience of N users, it w i l l be less hard-pressed than if it must reach ( N ) ( M ) users. I n m a r k e t i n g terminology, w h a t is the size of the potential user population at a given " p r i c e p o i n t " ? L e t us consider t w o computer m a n u f a c turers. O n e has a product w h o s e features a n d price suggest a total potential market of one thousand users. T h e second manufacturer occupies a niche of product features a n d price that implies a potential m a r k e t of one m i l l i o n users. T h e s e alternative scenarios have o b v i o u s implications for media choice, intensity a n d d u r a t i o n of interaction w i t h the user, and the c o m p l e x i t y of the transaction between the t w o . T h e first c o m p a n y can perhaps afford personto-person deployment approaches and is likely to be dealing w i t h m u c h more sophisticated users. T h e latter is in a mass m a r k e t . A related characteristic is the c o n c e n t r a t i o n , or structure, of the user group (or i n d u s t r y ) , and the subgroups t h e r i n . F o r e x a m p l e , w h a t percentage of total economic activity of users is accounted for by ten organizations? B y twenty? B y one hundred? I f a significant v o l u m e of deployment (that i s , sales and profits) can be achieved by focusing on ten users in a concentrated industry (assuming m u l t i p l e , w i t h i n - f i r m , replications), then the best deployment strategy w i l l be to ignore everyone except those core ten. It becomes m u c h easier w i t h such a strategy to use person-intensive, resource-intensive deployment tactics. A third major issue w h e n considering aggregated user characteristics is whether the end-users (the organization that actually puts the tools into practical applications) are the same as the adopting organizations. I n other w o r d s , are w e t a l k i n g about a p r i m a r y or a secondary market? F o r e x a m p l e , m a n y

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companies develop and deploy technologies exclusively for organizations that, in t u r n , service the real users. C o m p a n i e s such as Sears don't manufacture m a n y products themselves, but they deploy (sell) m i l l i o n s of manufactured products. T h e i r huge sales and distribution system enables companies that are developing technology to have the best of both w o r l d s : in effect, deploying (albeit indirectly) to a huge number of users, a n d focusing and concentrating their actual deployment efforts to a h a n d f u l of secondary m a r k e t targets.

Characteristics of Deployers A s s u m i n g that the deploying organization has also been the developer, we w o u l d , of course, like it to have all the characteristics of a w o r l d - c l a s s applied research and development organization discussed in chapter 5 . H o w e v e r , the constraints and capacities that pertain to deployment are essentially twofold: organization resources and organization m i s s i o n . T h e former is fairly straightf o r w a r d . Different deployment strategies and tactics call for different degrees of resource c o m m i t m e n t s . F o r e x a m p l e , v i r t u a l l y any organization can buy a m a i l i n g list f r o m a list b r o k e r , w r i t e and p r i n t a small b r o c h u r e , and send it to thousands of potential users. It is on a different order of magnitude to be able to put hundreds of technical people in the field to w o r k w i t h users, to develop and implement a national media c a m p a i g n , a n d to have the finances to be able to w a i t out the agonizing, s l o w g r o w t h in revenues that is correlated w i t h m o v i n g along the d i f f u s i o n c u r v e . In large p a r t , resources are correlated w i t h the size of the deploying o r g a n i z a t i o n . T h a t i s , all things being e q u a l , larger deploying organizations are likely to have more m a r k e t i n g , d i s t r i b u t i o n , sales, legal, and financial resources. T h e r e is one exception to this general rule. I n some situations there may be a close match between an extremely focused a n d n a r r o w technology development o p p o r t u n i t y , and a correspondingly small population of highly specialized users. I n such a situation a s m a l l developer organization may assemble a sufficient critical mass of technical talent to become w o r l d class. It may also be able to deploy satisfactorily to the s m a l l number of equally sophisticated user organizations.

The Case of Cray Computers

An interesting example of this phenomenon is Cray, which has been so successful in the supercomputer market that it has until recently dominated that arena. This is a company that has a few thousand employees and is in an industry (computer hardware) that has some huge corporate players. However, I the supercomputer market is highly specialized; each installation involves a major capital investment; and the resultant numbers of units sold is relatively

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small. During the first decade of its existence, the company sold less than one hundred machines, which nonetheless was the lion's share of the world market. Cray has been able to serve this market because it has assembled a critical mass of computer engineers, who can speak to their peers in user organizations. However, recent expansions in the market, particularly from Japanese computer makers such as Fujitsu and domestic companies such as IBM, suggest that a single, small company may get beyond its ability to serve users adequately.

The issue of organizational m i s s i o n , or goals, is also w o r t h discussing. U n d e r standing users, serving t h e m , c o m m u n i c a t i n g to t h e m , and also assuming that they are right, forms an internally consistent cluster of values, beliefs, and incentives. T h i s cluster w i l l likely differ significantly from the set of values, beliefs, and perceptions that permeate, for e x a m p l e , the applied research and development function of an o r g a n i z a t i o n . The i m p l i c a t i o n is that often a f i r m cannot be both a developer and a deployer of technology, despite the obvious efficiencies of housing both funcrions in a single o r g a n i z a t i o n . I n p a r t i c u l a r , the small f i r m may not be large enough to encompass multiple m i s s i o n s . F o r e x a m p l e , m a n y small high-tech companies excel at development but fail miserably at deployment. Other organizations m a y not be able to master the delicacies of i n t e r n a l , interfunctional boundary-spanning. H o w can a company keep both a healthy development function a n d a healthy deployment function and orchestrate the necessary intersections? W e w i l l discuss this in the next section.

Boundaries Between Users and Deployers One important component of our a n a l y t i c f r a m e w o r k is the idea that the boundary between deployers a n d user) is in itself a feature w o r t h considering. Most of the analyses that have been done of organization-level innovation have used the deployer and user organizations involved in the process themselves as focal p o i n t s , rather t h a n separately conceptualizing the boundary between them as a feature w i t h its o w n characteristics and d y n a m i c s . By contrast, w e believe that if one k n o w s enough about the b o u n d a r y — a n d about w h a t is expected to cross the b o u n d a r y — o n e c a n pretty w e l l understand w h y particular deployment devices succeed (or f a i l ) . Boundaries are local p h e n o m e n a , that i s , they exist in a limited part of an organization and for v a r i o u s periods of time. Some are relatively permanent, such as those between a f i r m ' s purchasing department and its suppliers, or between its l a w y e r s and everybody else's l a w y e r s . H o w e v e r , other boundaries only open up for relatively short intervals w h e n there is no other alternative.

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B o u n d a r i e s develop w h e n some part of an organization needs a window to the outside in order to achieve a n objective and w i l l structure w a y s of doing so that put the least possible pressure on those inside the organization (March and S i m o n 1 9 5 8 ; T h o m p s o n 1 9 6 7 ) . I n fact, it is erroneous to t h i n k of a single organizational b o u n d a r y , a k i n to a city w a l l , permanently surrounding the o r g a n i z a t i o n . A more appropriate metaphor w o u l d be to t h i n k of a large c o c k t a i l party attended both by people in u n i f o r m (insiders) and those in civilian clothes (outsiders). T h e p a r t y goes on for years a n d is characterized by clumps of c o n v e r s a t i o n , w i t h v a r y i n g levels of p a r t i c i p a t i o n , that involves both insiders and outsiders, i n changing p r o p o r t i o n s . Boundaries are crossed by i n f o r m a t i o n . I n a technology deployment boundary s i t u a t i o n , the i n f o r m a t i o n i n v o l v e d is generally i n f o r m a t i o n about the technology, both its technical a n d nontechnical dimensions. T h i s informat i o n , once received, must be interpreted in terms of the receiving context. T o the degree that a b o u n d a r y is fraught w i t h m u t u a l understandings—both sides tend to hear w h a t they w a n t to hear about w h a t the technology i s , h o w it is to be used, and w h a t its limitations a r e — i t w i l l discourage the only thing that has a chance of o v e r c o m i n g this d y n a m i c , n a m e l y , frequent and intense contact between the parties. O n l y w i t h time and iterations is the ability of both parties to understand and interpret each other fully f o r m e d . Boundaries m a y evolve to the point w h e r e t w o organizational systems actually interpenetrate each other. T h e process m a y be by m u t u a l consent or it m a y be under duress. In technology deployment, the process is usually m u t u a l , although w h e n the federal government is i n v o l v e d w i t h t r y i n g to push p a r t i c u l a r i n n o v a t i o n s , the line m a y get a little b l u r r y at times. T h i s interpenetration m a y take a variety o f f o r m s ; usually one organization moves farther into the other t h a n the other moves into the first. A salesperson who expects to sell products to a p a r t i c u l a r customer must k n o w considerably more about that customer's context than the customer can be expected to k n o w about the salesperson's. O n the other h a n d , a customer w h o k n o w s reasonably w e l l w h a t is w a n t e d m a y w i n d up k n o w i n g considerably more about the potential products available and those w h o sell them than any of the potential suppliers k n o w about the client.

OEMs and Their Suppliers

Companies that sell complex manufactured products (original equipment manufacturers, or OEMs), typically do not fabricate all (or even the majority) of the parts and subassemblies that go into their automobiles, refrigerators, or computers. Rather, they have sourcing relationships with a network of parts and component supplier firms that may number into the thousands. These relationships (or boundaries) tend to be quite stable.

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These same supplier firms have a second set of boundary relationships with another set of companies—those who sell industrial equipment and machine tools that enable these supplier firms to conduct their manufacturing operations. Unfortunately, supplier firms, since they are both small in size and large in number, are disadvantaged in their relationships with both OEMs and machine tool vendors. Currently, OEMs are demanding that supplier firms modernize their shopfloor technologies. Since they exert power and influence through the ability to bestow or withhold sourcing contracts, they can force supplier firms to use certain technologies. For example, in recent years some automotive OEMs have given their supplier firms deadlines for the installation of certain technologies, such as computer-assisted-design. At the same time, supplier firms (particularly small ones) have not been well served by their equipment vendors. Quality, cost, and delivery are problems. That is, given the relatively unfavorable cost-per-sale reality, vendor firms have few incentives to spend much time with small plants. Since small firms have less capacity to maintain an ongoing technology scanning function, they are still reliant on vendors for staying abreast. This difficulty is a residue of historically stable boundary relationship (Swanson 1984).

If it is the need to achieve c o m m o n goals that brings organizations to interconnect w i t h each other, it is other factors that create barriers to the success of the i n f o r m a t i o n exchange. T h e s e barriers are of several types: • Structural. T h e s e are barriers posed by internal organizational arrangements a n d the need to achieve internal organizational maintenance criteria. I n t e r n a l structures may be at odds w i t h the processes needed for boundary s p a n n i n g . • Cultural. T h e s e are barriers posed by the basic frame of reference of the parties i n v o l v e d . T h e y m a y involve general cultures (for e x a m p l e , A m e r ican f i r m s t r y i n g to do business in J a p a n and encountering u n f a m i l i a r practices), or the professional and technical cultures either w i t h i n or across organizational lines (for e x a m p l e , m a n u f a c t u r i n g t r y i n g to talk to R & D ; an economist t a l k i n g to an engineer). • Geographical. T h e s e are barriers posed by separation in space or time. Despite the advances of i n f o r m a t i o n technology in helping achieve asynchronous c o m m u n i c a t i o n , the fact remains that it is still a lot easier to share i n f o r m a t i o n w i t h those close by t h a n w i t h those farther a w a y . • Procedural. T h e s e are barriers posed by different w a y s of defining and conducting operations. F r e q u e n t l y , w h a t this amounts to is a failure to appreciate that w o r d s have different meanings in different contexts; w h a t seems n o r m a l a n d logical to one organization in terms of procedures m a y not seem equally logical to everyone else.

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T h e key point here is that m a n y of these barriers are, in fact, not physical or even organizational but conceptual or epistemological. T h e y are a function of people operating w i t h i n their o w n contexts for reasons that make sense w i t h i n that context, and being asked to assimilate another context. There are, of course, real costs in transcending these b a r r i e r s — t i m e , t r a v e l , people. Nonetheless, the magnitude of the barriers is often more a function of cognitive structures and belief systems than of distance on a m a p . By the same t o k e n , these barriers can be modified o r removed by the same processes that brought them into being. T h e critical dimension is h o w people think and feel about the technology itself, about the estimated value of deployment, and about their corresponding party on the other side of the boundary (users about deployers, and vice v e r s a ) . A t b o t t o m , creating effective technology deployment systems that take full advantage of the capabilities of parties on both sides is as m u c h a process of reeducating people as it is of doing anything at the organizational level. T h e actual individuals w h o manage the f l o w of i n f o r m a t i o n between organizations are (for a n a l y t i c a l purposes) generally termed boundary spanners.This is a p a r t i c u l a r l y difficult role to play w e l l . O f the twelve distinct roles i n the i n n o v a t i o n process defined by S m i t h et a l . ( 1 9 8 4 ) , at least four are explicit boundary-spanning functions. O f t e n the characteristics that enable one to be an effective gatekeeper are distinctly different f r o m those that make one an effective manager or strategist. T o a significant degree, an effective boundary spanner must operate in both contexts s i m u l t a n e o u s l y — a position nearly guaranteed to m a k e a participant in each context believe that he or she has been co-opted, o r taken o v e r , by the other. W h i l e someone w h o works at the b o u n d a r y is legally and fiscally o w n e d by one or the other organization, in a personal or psychological sense he or she m a y belong to neither. I n chapter 7 w e discuss further the characteristics associated w i t h those individuals w h o seem to be able to span boundaries effectively. I n some cases, b o u n d a r y - s p a n n i n g structures and people get legitimated in a visible w a y . Increasingly, companies that either use or deploy complex technological systems recognize that effective implementation w i l l demand lengthy and intensive interaction between at least t w o organizations and maybe m o r e . T h e y m a y create a project team or a temporary system and give it the single task of achieving the transition f r o m developer-deployer to user. In s u m m a r y , w e have argued that relatively stable patterns of relations h i p s — c a l l e d b o u n d a r i e s — e x i s t between deployers and users, and that information (about technology) needs to move across that b o u n d a r y . M o r e o v e r , barriers to boundary spanning m a y become exacerbated w h e n there are disparities between the t w o (or more) parties in c u l t u r e , geography, procedures, structures, or p o w e r (political or e c o n o m i c ) . A s barriers get larger, there is more and more need for dedicating people and money to boundaryspanning functions. T h i s has implications for deployers selecting their deploy-

The

not p h y s i c a l e a function m a k e sense . There are, 'el, people. 3n o f c o g n i by the s a m e h o w people of deployboundary 'e t e c h n o l of p a r t i e s doing a n y n between dary spanve d i s t i n c t least f o u r that enable that m a k e effective a position he o r she ho w o r k s 5anization, r. I n c h a p dividuals :gitimated complex demand ions a n d and give to user, relationlat i n f o r oreover, here are , procelarger, undarydeploy-

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ment approach, or for f i r m s w h o are deciding whether or not they are capable of being a deployer.

Characteristics of Communication Transaction Mechanisms

and

In this section w e w i l l intentionally c o n f o u n d and intermingle t w o important issues: deployment c o m m u n i c a t i o n media and deployment transaction mechanisms. C o m m u n i c a t i o n media are, generically speaking, channels for m o v i n g information, technical or otherwise. P r i n t , interpersonal, and electronic are all communication media choices. I n contrast, deployment transaction mechanisms are w a y s of f o r m a l i z i n g the exchange relationship between deployer (or third party) and user. A sales contract is a type of transaction m e c h a n i s m ; so is a retail sale at a discount store checkout stand. For our purposes, both c o m m u n i c a t i o n media a n d transaction mechanisms can be categorized along a few dimensions that have relevance for crafting deployment approaches. Both differ on the uncertainty-reduction (that is, i n f o r m a t i o n conveying) p o w e r of different options. F o r e x a m p l e , communicating v i a the w r i t t e n w o r d is different f r o m a face-to-face encounter in the ability to convey nuances of m e a n i n g ; transacting the transfer of a technology v i a a licensing agreement has different potential for i n f o r m a t i o n exchange than giving it a w a y or selling i t . " S i m i l a r l y , both c o m m u n i c a t i o n media and transaction mechanisms differ on the scope and cost of options. F o r e x a m p l e , p r i n t c o m m u n i c a t i o n embodied in a technology product brochure c a n be mailed to thousands of potential users at a modest per contact cost; this is not true w i t h other, more intensive media. S i m i l a r l y , a transaction device such as a retail sale is something that is easily replicated; this is not true of complicated licensing agreements, which need to be crafted o n a case-by-case basis, and attended to by expensive lawyers. T h e s e observations should lead deployers to ask questions such as what is the number of transactions, or media contacts, that can be made, given cost-per-transaction/contact constraints? C o m m u n i c a t i o n media and transaction m e c h a n i s m s , in an operational sense, tend to be intertwined in the deployment process. H o w e v e r , in planning an overall a p p r o a c h , c o m m u n i c a t i o n media issues are more important early in the interaction w i t h the user, w h e n needs are being determined and decisions are being made (see chapter 8 ) . T r a n s a c t i o n mechanisms have more implications for the postadoption phase of user behavior, w h e n implementation is unfolding. C o m m u n i c a t i o n media that involve interpersonal interaction tend to be high in uncertainty-reduction p o w e r , l o w in scope, and high in cost. M e d i a

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that are noninteractive tend to be less capable of c o n v e y i n g information, although they have greater scope (for e x a m p l e , p r i n t , electronic media) and l o w e r cost per c o m m u n i c a t i o n contact. A classic study by C h a p p a n i s ( 1 9 7 1 ) is illustrative. A n experiment was set up to provide researchers w i t h different k i n d s of i n f o r m a t i o n services—phone c o n s u l t a t i o n , literature searches, or f o r m a l w r i t t e n c o m m u n i c a t i o n . They found m u c h greater satisfaction w i t h interpersonally mediated information retrieval when the problem was complex a n d essentially no difference among media w i t h simple and routine problems. T h i s experimental finding has correlations in everyday deployment practice. T h e transmission of any kind of technically dense intervention tends to be achieved better v i a "interpersonally r i c h " approaches (Beyer and T r i c e 1 9 8 2 ; C h a k r a b a r t i , F e i n m a n , and Fuentev i l l a 1 9 8 3 ; E r s h o f f , A a r o n s o n , and W i l n e r 1 9 8 3 ) . O n e can apply a s i m i l a r logic to transaction devices. F o r e x a m p l e , if one considers simple sales, licensing, cooperative agreements or joint ventures, and mergers as a l l being transaction mechanisms between technology deployers and users, then w h a t do they i m p l y for considerations of scope and uncertainty-reduction.' T h e brief, simple encounter such as a retail sale, is high in scope and l o w in i n f o r m a t i o n content. O n the other end of the spect r u m , if a developer/deployer organization a n d a user organization can only achieve the degree of necessary uncertainty-reduction by constant interaction, then they had better t h i n k about merging. O b v i o u s l y , this is a low-scope option. T h e s e issues of uncertainty and scope are not abstract w h e n they are tied to the specific aspects of context that were discussed earlier. W h a t are the characteristics of users, m a r k e t s , technology, deployers, and boundaries that matter? F o r e x a m p l e , w h a t is the choice of deployment option w h e n the technology is c o m p l e x , the user group is both unsophisticated and large numeri c a l l y , the deployer is limited in resources, a n d the established linkages or boundaries are negligible? G i v e n a complex technology and unsophisticated users, this w o u l d , at first, suggest t h r o w i n g lots of smart personnel into the field to interact w i t h potential users. H o w e v e r , w h a t if the number of users is in the thousands? C a n w e a i r d r o p consultants all over the landscape? What if the n o m i n a l deployer (the developer) is strapped for people and resources? If this hypothetical situation occurred in the private sector, there would be a strong temptation to pronounce that a structurally imbalanced market failure h a d developed and that the case for v a r i o u s types of government intervention w a s strong. Bean and Roessner's ( 1 9 7 9 ) analysis of circumstances w h e n government intervention into i n n o v a t i o n is justified suggests that such activity is appropriate w h e n clear n a t i o n a l needs are i n v o l v e d and individual incentives are insufficiently strong—for e x a m p l e , in the case of energyconserving technology. T h e s e might include v a r i o u s t a x incentives or subsidies to raise the interest or capacity of either deployer or user.

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Another a h e r n a t i v e is to create a technology of technology deployment, that is, media and other tools that are both high scope and high in uncertaintyreduction p o w e r . F o r e x a m p l e , recent developments in hypertext permit an interrogative, interactive electronic p r i n t m e d i u m . A n i n d i v i d u a l can v i e w a screen of print a n d then z o o m in on any sentence or w o r d in that display for more and more detail ( G r e i f and S u r i n 1 9 8 6 ) . T h e use of hypertextbased context-sensitive help in computer systems is an exciting new development. We are also developing electronic versions of the technical consultant. I n recent years, w e have seen the g r o w t h of expert systems in w h i c h the k n o w l edge and w i s d o m of p r a c t i c i n g experts is embedded into diagnostic and prescriptive computer p r o g r a m s . F o r e x a m p l e , one major computer c o m p a n y is using such a n expert system w i t h its field sales staff, to enable each of them to operate on the level of an engineering consultant, as each diagnoses the systems needs of customers. H o w e v e r , as the D r . F a c t o r y ' ^ insert suggests, the use of expert systems as consultants-in-a-box goes beyond computer systems.

A Visit to Dr. Factory

Technologically speaking, the small manufacturing plant in America is often a backward place. Little in the way of benefit from the new technologies— computerized machining systems, robots, CAD—has found its way into this setting. In fact, many equipment vendors don't know how to serve the hundreds of thousands of such companies, given the high cost of sales. This demonstrates a classic market failure. One solution to this deployment problem is for government to throw a large cadre of automation consultants into the field to diagnose the technological needs and opportunities of small companies; in effect, for government to subsidize a way of meeting a market failure. Unfortunately, government is as broke as the rest of us. A better, more economical solution, is to embody much of the wisdom of several such automation consultants into a tool—the consultant on a disc. Such a system exists and is known as Dr. Factory. It can be used to expand the capacities of field agents or consultants as they bring the twentieth century to the foundation firms of the country. Rather than a consultant relying solely on his or her expertise and ability to make insightful (if sometimes flawed) diagnoses of factory problems, an expert system computer program can assimilate the information collected by the consultant on the shop floor, suggest tentative conclusions (with rationale supplied), and nudge the consultant to ask this or that supplemental question. Moreover, Dr. Factory keeps getting smarter. It has magnetic, focused memory, rather than an organic fallible one and can recall other cases and other situations (perhaps faced by other consultants) that have potential applicability.

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Innovation

Choosing Deployment Tactics i n the spirit of t r y i n g to provide o u r readers some partial certainty where litde exists, w e present the f o l l o w i n g tool to help choose a m o n g communication a n d transaction options. C o n s i d e r this as a p l a n n i n g , tactic-selection device. W e have tried to capture in a highly simplified fashion some of the dimensions of deployment that w e have discussed i n this chapter. I f w e h a d built in all of the factors that w e have discussed ( a n d the levels and permutations t h e r e o f ) , this w o u l d have yielded a m a t r i x w i t h an almost impossibly large number of cells. W e have also not attempted to fill in every cell in the matrix that w e have created; rather, w e have p r o v i d e d some sample call entries, in w h i c h a technology/user c o m b i n a t i o n is paired w i t h a n appropriate c o m m u n i c a t i o n / t r a n s a c t i o n device. F o r e x a m p l e , suppose w e h a d a case in w h i c h a fairly small deployer company had a technology that w a s c o m p l e x , unstable, and c o s d y , but that had a potential for benefiting a large number of sophisticated users. T h e y would probably need to partner w i t h a m a r k e t i n g group capable of putting legions of individuals into the field to meet w i t h those users on a one-to-one basis. A n e w , highly effective, but d i f f i c u l t to use d r u g or medical device would be of this type. O n the other h a n d , if the potential user population were unsophisticated or resistant, this w o u l d create a n impossibly difficult deployment task. T h e m a t r i x that w e have created in figure 6 - 1 should be used heuristically rather t h a n as a prescriptive t o o l . O u r intent is to get readers to t h i n k about the factors that influence deployment, not to plug into a c o o k b o o k .

Assessing Technology Deployment Efforts I n this final section, w e return to the questions that w e posed i n i t i a l l y : W h a t good is technology deployment a n y w a y ? W h o needs it? W h o s e ends does it serve? A n d h o w should w e tell w h e n we've done a good job? In the w o r l d of real organizations, it is unrealistic, as w e have suggested above, to assume that technology is an end in i t s e l f — h o w e v e r nice the toys m a y be. C e r t a i n l y production is a value for o r g a n i z a t i o n s , and better technology can enhance p r o d u c t i o n , but it is only one of the multiple goals that an organization pursues. A n y question of technology must be interpreted in an organizational context that includes the technology, not only in terms of its functional utility, but in terms of its coherence to the symbolic and value structure of the system. M o r e o v e r , any given technology deployment initiative is likely to have both direct and indirect, long- and short-range ripples across both developers and users. Perhaps the effort falls short, a n d the technology is rejected. Is the

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Nature of Technology Simple Hardware Complex Custom Product Tool

Few

Over the counter sales

Sales and marketing department with technically competent staff

Many

Catalog sales

Marketing partnership with other entities; use of field agents

Few

Door to door sales

Face-to-face diplomacy and outreach to high levels of management

Many

License the technology

Generally unsuccessful

Better educated, Enthusiastic

Less educated, Resistant

Figure 6 - 1 . D e p l o y m e n t Strategies

effort a failure if this experience sets the stage for a subsequent effort that transfers a better technology? Perhaps the effort succeeds in m a k i n g the technological change, a n d , as a consequence, half of the employees become unemployed. Is this a consequence w o r t h achieving? I f engineering succeeds in bringing in n e w m a n u f a c t u r i n g technology w i t h a consequent increase in production, but at the same time uses up key resources that might otherwise have gone to R & D , whose criteria of success are being achieved? T h e point here is simply that any technology deployment effort is bound to have a wide range of consequences, only a relative few of w h i c h have m u c h to do w i t h the technology itself. T h e process of anticipating consequences, and of m a k i n g educated tradeoffs between t h e m , is still largely an art f o r m . T h e degree to w h i c h an organization is responsible to those outside its boundaries, for either functional or symbolic/ideological reasons, and h o w it goes about defining that constituency, has a m a j o r effect on h o w it is likely to structure its technology deployment efforts (Staats 1 9 7 9 ) . F o r e x a m p l e , one of the m a j o r criticisms leveled for years against federal dissemination programs, in areas ranging f r o m education to m a n u f a c t u r i n g technology, has been that they do not pay enough attention to long-term implementation and effective use but instead concentrate on counting " a d o p t i o n s " ( D a t t a 1 9 8 1 ; Roessner 1 9 8 5 ) . I n large measure the c r i t i c i s m is v a l i d , but it cannot be interpreted outside of a knowledge of the context w i t h i n w h i c h programs typically operate—namely, an environment of short-term budgetary pressures, little

146

• The Processes

of Technological

Innovation

w i l l a n d less a b i l i t y to stay i n v o l v e d i n p r o j e c t s b e y o n d a n i n i t i a l i n t e r v a l , and constantly within

shifting program

which

these

programs

priorities imposed are

nested.

by

the

O n e cannot

political

structure

logically expect

to

c h a n g e a g e n c i e s ' b e h a v i o r m e a n i n g f u l l y w i t h o u t c h a n g i n g t h i s c o n t e x t signifi c a n t l y , s u c h as r e c e n t c h a n g e s in the legal c o n s t r a i n t s a n d m i s s i o n objectives at f e d e r a l l a b o r a t o r i e s ( B o z e m a n a n d F e l l o w s 1 9 8 8 ) . W h a t w e h o p e w e h a v e m a d e c l e a r is t h a t the p r o c e s s o f

technology

d e p l o y m e n t is s u b s t a n t i a l l y m o r e c o m p l e x t h a n the r a t h e r l i n e a r c o n v e y e r - b e l t i m a g e s i m p l i c i t in m u c h o f the c o n v e n t i o n a l l i t e r a t u r e w o u l d suggest. It is the l o g i c a l o u t c o m e o f the d e v e l o p m e n t p r o c e s s d e s c r i b e d i n the p r e v i o u s c h a p t e r s , but it a l s o c a n n o t be d i v o r c e d f r o m the p r o c e s s e s b y w h i c h u s e r s m a k e decisions a n d i m p l e m e n t tools w i t h i n their particular organizational contexts. I n the n e x t c h a p t e r s , w e s w i t c h o u r f o c u s f r o m d e v e l o p e r to u s e r a n d begin to e x p l o r e the d y n a m i c s o f t e c h n o l o g y c h o i c e a n d a p p l i c a t i o n . W e hope t h a t this d i s c u s s i o n o f t e c h n o l o g y d e p l o y m e n t h a s b r o u g h t the r e a d e r to the point of recognizing that developer a n d user are not t w o isolated p h e n o m e n a , e a c h w i t h its o w n l a n g u a g e a n d i s s u e s , but r a t h e r c o p a r t i c i p a n t s i n a n intricate d a n c e , the o b j e c t o f w h i c h is the e n h a n c e m e n t o f b o t h p a r t i e s .

Notes 1.

It is worth noting that deployment is itself a metaphor d r a w n from the military

and carries the implication of something put in a particular place for a particular reason. T h e notion of embedded purpose is what makes this metaphor particularly apt. 2. T h e center-periphery model might also be called the missionary model, since there is an implicit assumption that those on the periphery are not as well off as they would be if they had the information in question. T h e center-periphery model is at the core of the dissemination and technology transfer traditions. 3. In some cases, reciprocal interaction between technical person and user may be necessary not to facilitate reinvention but to prevent it. T h a t is, sometimes user tinkering with a complex technology may destroy its effectiveness. T h e r e is an interesting debate about how much reinvention or adaptation is permissible and desirable, as opposed to perverting or malignant ( C a l s y n , T o r n a t z k y , and Dittmar 1977). 4.

O n e interesting problem, particularly when a new technology is quite novel,

is to identify w h o , or what groups, are innovative enough to be early users. .5. It should also be noted that the nature of the information itself can be very complex. Users have information about their needs but may not understand the technology well enough to interpret it to the developers. Both the technology itself and the language used to describe it are subject to interactive development. 6. In some settings, machine vision is m a k i n g a comeback. Improvement in the technology itself, and increased wisdom about the nuances of implementation, have been the key. 7.

T h e necessity of a sophisticated user is probably more true in the early stages

of technology development than later. For example, in the second or third waves of

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technology product development there is typically a greater and greater attention to user friendliness, although the pace at which the underlying technology is changing may be accelerating. P C s are an excellent example. 8. E v e l a n d and Bikson (1989) refer to the " h u m a n w a r e " costs of implementing electronic communication systems—costs that vary significantly over time, changing in specific demands but always posing challenges. Eventually, their study indicates, the burden of hand-holding gets transferred from developer experts to user experts, but never goes away completely. 9. Teleconferencing stands out as an example. Several years ago it was expected that teleconferencing would be widespread and have a great impact on reducing the need for travel. T o date, that impact has been small and the number of teleconference facilities few. 10. T h i s is seldom, of course, an organizational title. T h o s e playing this role on a regular basis are usually called the sales force, field repre.sentatives, consultants, or the like. M a n y organizational members have occasion to span boundaries in the course of their ordinary w o r k , usually without thinking much about it. 11. For example, there is some concern about the movement of technology between U . S . multinationals and their foreign subsidiaries (or partners), and vice versa, and the net gain to those companies (Mansfield et al. 1983; Mansfield and Romeo 1984). 12. D r . Factory is a registered trademark of the Industrial Technology Institute in Ann A r b o r , M i c h i g a n .