When forced to choose between adding more user features or doing more testing Most software development managers decide in favor of more testing?

 . Question 32 (2 points) Given that 8 employees have the following Promotion possibilities: Lower, Middle-A, Middle-B, Upper-C, Upper-B, Upper-A, Supervisor, Executive, Manager, AVP, SVP, VP, Presid...

BonesNoBones.csv: "Date","BonesDay","Day_of_Week","Weather_NYC" "11/11/2021","No Bones Day","Thursday","Cloudy" "11/09/2021","Bones Day","Tuesday","Sunny" "11/08/2021","Bones Day","Monday","Sunny" "11...

BonesNoBones.csv: "Date","BonesDay","Day_of_Week","Weather_NYC" "11/11/2021","No Bones Day","Thursday","Cloudy" "11/09/2021","Bones Day","Tuesday","Sunny" "11/08/2021","Bones Day","Monday","Sunny" "11...

BonesNoBones.csv: "Date","BonesDay","Day_of_Week","Weather_NYC" "11/11/2021","No Bones Day","Thursday","Cloudy" "11/09/2021","Bones Day","Tuesday","Sunny" "11/08/2021","Bones Day","Monday","Sunny" "11...

BonesNoBones.csv: "Date","BonesDay","Day_of_Week","Weather_NYC" "11/11/2021","No Bones Day","Thursday","Cloudy" "11/09/2021","Bones Day","Tuesday","Sunny" "11/08/2021","Bones Day","Monday","Sunny" "11...

BonesNoBones.csv: "Date","BonesDay","Day_of_Week","Weather_NYC" "11/11/2021","No Bones Day","Thursday","Cloudy" "11/09/2021","Bones Day","Tuesday","Sunny" "11/08/2021","Bones Day","Monday","Sunny" "11...

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For all the dollars spent by American companies on R&D, there often remains a persistent and troubling gap between the inherent value of the technology they develop and their ability to put it to work effectively. At a time of fierce global competition, the distance between technical promise and genuine achievement is a matter of especially grave concern. Drawing on their long study of the difficulties managers have had in closing this gap, the authors identify half a dozen key challenges that managers responsible for implementing new technology must surmount: their inescapably dual role, the variety of internal markets to be served, legitimate resistance to change, the right degree of promotion, the choice of implementation site, and the need for one person to take overall responsibility.

Introducing technological change into an organization presents a different set of challenges to management than does the work of competent project administration. Frequently, however, the managers responsible for shepherding a technical innovation into routine use are much better equipped by education and experience to guide that innovation’s development than to manage its implementation.

In the following pages, we describe some of the challenges managers must overcome if companies are to absorb new technologies efficiently. We also suggest strategies managers can use to address these difficulties. Although the examples we cite are all computer related and come from the experience of large manufacturers, the issues raised and strategies proposed apply every bit as well to small businesses, to service operations—in fact, to any organization where technological innovation flourishes.

Our findings derive from our combined research and consulting experience with more than 20 large multinational corporations and with some 70 organizations within General Electric. Our focus is on internally developed technologies; but as vendors of advanced manufacturing equipment have found in their efforts to help implement the systems they market, new technologies, no matter what their origin, confront managers with a distinctive set of challenges.

A Dual Role

Those who manage technological change must often serve as both technical developers and implementers. As a rule, one organization develops the technology and then hands it off to users, who are less technically skilled but quite knowledgeable about their own areas of application. In practice, however, the user organization is often not willing—or able—to take on responsibility for the technology at the point in its evolution at which the development group wants to hand it over. The person responsible for implementation—whether located in the developing organization, the user organization, or in some intermediary position—has to design the hand-off so that it is almost invisible. That is, before the baton changes hands, the runners should have been running in parallel for a long time. The implementation manager has to integrate the perspectives and the needs of both developers and users.

Perhaps the easiest way to accomplish this task is to think of implementation as an internal marketing, not selling, job. This distinction is important because selling starts with a finished product; marketing, with research on user needs and preferences. Marketing executives worry about how to position their product in relation to all competitive products and are concerned with distribution channels and the infrastructure needed to support product use.

Adoption of a marketing perspective encourages implementation managers to seek user involvement in the: (1) early identification and enhancement of the fit between a product and user needs, (2) preparation of the user organization to receive the innovation, and (3) shifting of “ownership” of the innovation to users. We discuss the first two of these issues in this section of the article; the third we cover later.

Marketing Perspective

That involving users in a new technology’s design phase boosts user satisfaction is quite well known, but the proper extent, timing, and type of user involvement will vary greatly from company to company. For example, software developers in an electronic office equipment company established a user design group to work with developers on a strategically important piece of applications software when the program was still in the prototype stage. Prospective users could try out the software on the same computer employed by the program’s developers. The extremely tight communication loop that resulted allowed daily feedback from users to designers on their preferences and problems. This degree of immediacy may be unusual, but managers can almost always get some information from potential users that will improve product design.

A marketing perspective also helps prepare an organization to receive new technology. Many implementation efforts fail because someone underestimated the scope or importance of such preparation. Indeed, the organizational hills are full of managers who believe that an innovation’s technical superiority and strategic importance will guarantee acceptance. Therefore, they pour abundant resources into the purchase or development of the technology but very little into its implementation. Experience suggests, however, that successful implementation requires not only heavy investment by developers early in the project but also a sustained level of investment in the resources of user organizations.

A very promising implementation effort in a large communications and computer company went off the rails for many months because of inadequate infrastructure in the user organization. New computerized processing control equipment was ready for shipment to prospective users enthusiastically awaiting its arrival, but a piece of linking software was not in place. Arguments erupted over who should pay for this small but critical piece of the system. Equally troubling, there were no resources for training because the developers did not see providing these resources as part of their normal responsibilities. No one in the user organization had prepared the way for the innovation, so there was no one to whom developers could hand it off.

Framework for Information

Just as marketing managers carefully plan the research through which they will gather critical product information, so implementation managers must develop an iterative, almost accordion-like framework to guide decisions about when and how to collect needed information from all groups affected by an innovation. We say “accordion-like” because the process necessarily involves a search for information, a pause to digest it, and then another active period of search—cycle after cycle. What information is important—and who has it—may vary at different stages of the implementation process, but someone must coordinate the iterative work of gathering it—and that someone is the implementation manager.

When, for example, a turbine manufacturer designed a CNC system for shop-floor control in one of its small parts operations, project managers were careful to:

• Observe the current job routine. System designers visited the factory floor several times and each time interviewed eight to ten operators about their work procedures.

• Pay special attention to those parts of the work that required users to make decisions or seek information about which tools or materials to use, which sequence of steps to follow in machining, and which jobs operators ought to run first.

• Discuss with workers what they found especially frustrating or rewarding about their work. In this case, it turned out that they liked some flexibility in the sequencing of jobs, felt that the choice of materials should be theirs, and were often frustrated by the difficulty of finding tools.

• Examine how this manufacturing process related to others. The machine operators were extremely dependent on materials personnel, maintenance, the tool room, and order expediters.

From their discussions with operators, the system designers could understand the important variables as the operators saw them and, therefore, could design a system that solved problems the operators really faced without creating new ones. These discussions also facilitated a transmission of information back to the users through education and hands-on practice sessions with the users and their supervisors.

Multiple Internal Markets

The higher the organizational level at which managers define a problem or a need, the greater the probability of successful implementation. At the same time, however, the closer the definition and solution of problems or needs are to end-users, the greater the probability of success. Implementation managers must draw up their internal marketing plans in light of this apparent paradox.

As these managers identify the individuals or groups whose acceptance is essential to an innovation’s success, they must also determine whom to approach, when, and with which arguments. Top management and ultimate users have to buy into the innovation to make it succeed, but marketing an idea to these two groups requires very different approaches. How, then, can an implementation manager foster general acceptance of an innovation from such a range of constituencies? We believe this executive must view the new technology from the perspective of each group and plan an approach to each accordingly.

Top management, most concerned with an innovation’s likely effect on the bottom line, is accustomed to receiving proposals that specify return on investment and paybacks. Many of today’s computerized technologies, however, do not lend themselves to justification in traditional financial terms, yet they may be essential to a company’s future. Amid growing calls for the accounting profession to provide better means to assess the value of robots, CAD, and computer-integrated manufacturing, some companies are beginning to realize the limitations of traditional capital budgeting models.1

When GE set up its state-of-the-art automated dishwasher plant, it originally justified the costs on the basis of savings over time, but the plant has experienced payoffs from the investment in unanticipated ways. The quality of the product improved, lower manufacturing costs led to an expansion of market share, and the plant proved able to serve as a manufacturing site for other products. Each time managers document such nontraditional benefits, they make it easier to justify similar investments later.

Top executives may also be swayed by strategic considerations. When large-scale automation was introduced into GE’s large steam-turbine generator business, the innovation was sold to top management on the basis of changing business needs: a shift from the manufacture of large, one-of-a-kind products to the manufacture of small parts. The new systems also helped drive the continual quality improvements needed to keep operations competitive when the currently sluggish market revived.

Selling top management on the case for new technology—without simultaneous involvement of user organizations in the decision-making process—is not enough. It is equally important for users of an innovation to develop “ownership” of the technology. The meaning of this term depends largely on the scope of the project. Although it is patently impossible to involve all users in the choice and/or development of an innovation, that is no excuse not to involve their representatives.

Perhaps even more important is to plan for the transfer of knowledge from the old operation, in which people knew the materials and the product very well, to the new process, which outsiders may initially design and run. The developers of the new process (especially when it is computer software) often know their tools very well, but rarely do they understand the materials and processes to which their software is applied as well as the people on the plant floor who have been working with both for years. At the very least, managers should provide some mechanism and time for such knowledge to flow from experienced worker to developer.

An example of well-developed ownership is the case of a marketing organization about to switch from manual files to an electronic filing, messaging, and data retrieval system used by both account officers and secretaries. Managers decided to take the time to do it right the first time instead of doing it over. The project manager set up a committee of elected representatives from all groups affected. This committee met regularly, first to select the right software package and then, when it became apparent that they would have to build their own system to get all the features they wanted, to give advice on its structure and content.

The result was an inventive, well-accepted, and widely used system. Moreover, users regarded the minor problems that did arise as bugs to be worked out of our system. As one manager told us, “The users wanted it, so they built it.”

Critical to the success of this project was the choice of opinion leaders among users for involvement. Managers who have wrought change have known for a long time that the opinions of a few leaders profoundly influence the speed and extent of an innovation’s diffusion. The basis for leadership differs from organization to organization, but these leaders are not usually hard to identify. Frequently, they occupy their place of influence as a result of technical proficiency, not formal position.

Opinion leaders, however, are not necessarily the most skilled operators. Behavioral science studies have shown that people commonly seek two kinds of credibility in such leaders: “safety” credibility (this person is enough like me for his opinions to be trusted) and “technical” credibility (this person knows what she is talking about). Someone whose technical skills are so superior that followers can have no hope of emulation may fall too far outside the norms of a group to be a real opinion leader.

In the marketing organization just described, one senior account manager refused to use the new electronic system. The system implementers were at first alarmed but then realized that this individual was not an opinion leader. Their efforts flowed around him, unimpeded by his opposition. Six months after everyone else went on the system, he capitulated, convinced at last of its utility.

Promotion vs. Hype

Many a technology developer will confess bewilderment that innovations do not win automatic acceptance. It may be overly optimistic to believe that an innovation will sell itself, but it is equally dangerous to oversell the new system. Novel and exotic technologies are especially vulnerable to hype.

Articles in the media about robots and artificial intelligence, for example, have raised expectations far higher than the actual performance of current technologies warrants. Potential users quickly grow disillusioned when much touted innovations perform below expectations. When one computer maker developed artificial intelligence software to be used in manufacturing, the outside world thought it was a finished product long before it was out of the “vaporware” stage. Months before they had their hands on the software, intended users faced questions from their customers about how they liked it.

The gap between perception and reality was traceable to the energetic efforts of one project manager early on. Knowing the importance of selling the concept to management, this enthusiast had extended his campaign to virtually anyone who would listen. Since it was a sexy topic, the new artificial intelligence system received wide attention in the media as well as in organizational newsletters. This oversell presented a problem to implementation managers, who had to fight the perception that their project was way behind schedule and that their product delivered less than promised.

Risky Site, Safe Innovation

There are two reasons for conducting a pilot operation before introducing an innovation across the board in a large organization: first, to serve as an experiment and prove technical feasibility to top management and, second, to serve as a credible demonstration model for other units in the organization. These two purposes are not always compatible.

If the innovation must succeed at the pilot site in order to survive politically, the implementation manager may choose a site that poses virtually no risk but that neither offers real benefit to the organization nor establishes a model for other units. At the same time, however, if the trial is to be a credible test, it cannot take place among the most innovative people in the corporation. Success at this kind of site is vulnerable to the criticism that these users are far from typical.

Testing the new technology at the worst performing unit, even though it may be where the innovation is most needed and would show the most spectacular results, is no better a choice. If the project fizzles, the implementation manager will not know how much of the failure was caused by extraordinary problems with the site and how much by the inherent properties of the technology. If the project succeeds, critics will be quick to note that anything would have helped operations at that site.

The solution, therefore, is to be clear about the purpose of the test—experimental or demonstration—and then to choose the site that best matches the need. The customized end of one large computer manufacturer’s business suffered from a problem. If customers canceled orders, the partially built systems were either totally scrapped—that is, broken down into components and sent back to the warehouse—or matched with incoming orders to determine if the fit was close enough to warrant retrofitting. When this matching process, which had been done manually, was computerized, the first applications site was an operation with an enthusiastic champion, but it was to be phased out in a matter of months. The site was politically risk free but not useful for a demonstration. Although the first application was successful, the operation closed down before the site could serve as a demonstration for other plants, and the implementation manager in charge of the next site had to start all over.

Consider a different example: a paper maker that chose one of its high-visibility mills as the first site for an expensive, large-scale computerized control system. Although the system was needed to boost sagging profit margins, the mill was neither the company’s best nor worst operation in financial terms. Local management was determined to see the system succeed for the sake of the mill; corporate management viewed it as an experiment. The site was promising but not risk free.

Even if managers realize that the trial of a new technology is a critical demonstration, they do not always ask the next question: a demonstration for whom? The physical and organizational position of the first site will heavily influence who the next wave of users will be.

Over the years, many studies have shown a strong inverse relationship between proximity to facilities and use of them. This result is not surprising if the distance is measured in miles. What is surprising is that out of sight—no matter by how much—generally means out of mind. The difference in the use of a library by engineers on a college campus depended on how many more feet, not miles, nonusers were from the library than users. Similarly, new computer terminals in a large oil company were used first by people with adjoining offices and only reluctantly by people even a few more feet down the hall. Distance is a relative, not absolute, measure to be weighed against current routine rather than against any objective standard.2

Obviously, it is not always possible to site new equipment for everyone’s convenience. Even so, the placement of an innovation frequently determines who uses the new technology first and most. If the equipment is located farther away from older or more reluctant potential users, they have a ready excuse for avoiding it. Consequently, managers who do not consider physical layout in their implementation strategies may, by default, select as first users people with little or no influence in the organization.

As noted earlier, involving opinion leaders in the planning process helps smooth the path of implementation. If the first users of a new technology are credible role models (neither extraordinarily adept nor very poorly skilled), their demonstration has heightened meaning for a wide audience. Sometimes these opinion leaders strongly resist the technology, and getting even one of them to use it can create the necessary crack in the dam. Getting them to try the innovation may require nothing more elaborate than a well-paced and tactfully presented training session.

Often, however, an implementation manager has to create new role models by siting the innovation where the workers most open to change can demystify the technology for others by using it themselves. Although it is definitely a mistake to correlate resistance with age per se, it remains true that people with a long-term investment in certain routines and skills often hesitate to give up the security of those habits. Again, it is best to avoid extremes and to site new technology near workers who are fairly open to change but not so different from those whose resistance makes them poor models.

When a large warehouse installed a materials handling system, it relied on its so-called “hippy” crane operators instead of workers on the loading platform. Once the crane operators had worked out the wrinkles, management could progressively install the system throughout the plant. The crane operators were not opinion leaders at first because of their relative youth and different backgrounds, but they were both receptive to innovation and not so very different as to be unacceptable role models.

The Many & the One

If an innovation is to succeed, the implementation team must include (1) a sponsor, usually a fairly high-level person who makes sure that the project receives financial and manpower resources and who is wise about the politics of the organization; (2) a champion, who is salesperson, diplomat, and problem solver for the innovation; (3) a project manager, who oversees administrative details; and (4) an integrator, who manages conflicting priorities and molds the group through communication skills. Since these are roles, not people, more than one person can fulfill a given function, and one individual can take on more than a single role.

Even if all these roles are filled, however, the project can still stall if the organization does not vest sufficient authority in one person to make things happen. One of these individuals—usually the sponsor or the champion—must have enough organizational power to mobilize the necessary resources, and that power base must encompass both technology developers and users.

There are, of course, many ways to mobilize supplies and people. By encouraging ownership of an innovation in a user organization, for example, skillful advocates can create a power base to pull (rather than push) the innovation along. But enthusiasm for a new technology is not enough. New technology usually requires a supportive infrastructure and the allocation of scarce resources for preparing the implementation site. A champion based in the development group with no authority among the receivers must rely on time-consuming individual persuasion to garner the necessary resources. Further, even if prospective users believe in an innovation’s worth, they may have to convince their superiors to free up those resources.

A short case will illustrate the point. A manufacturer of engineering test equipment was in trouble because many orders for its customized products reached the plant floor missing vital components. Technical experts were able to catch omissions and incorrect selection of parts before the orders went into production, but the mechanics of checking orders and cycling them back through the purchase-order process cost enormous amounts of time, money, and customer goodwill. Customers were angry at the delay of orders for weeks when manufacturing bounced them back to the initial salespeople and were even more dismayed when price quotations had to be revised upward because of a part forgotten in the first go-around.

An internally developed technology offered a partial solution: a computer program could automatically check the orders before salespeople issued quotations. Although the people who placed the orders were enthusiastic about the concept, the work of implementing the system was fraught with problems. No sales manager was willing to function as either sponsor or champion for the innovation. Although a user group funded its development, the appointed champion in that organization was too low in the hierarchy to control the resources necessary to install the system. Moreover, he lacked a clear endorsement for the project from his superiors and had mixed feelings toward the innovation. He believed in its purpose but was not certain it was being developed correctly and was afraid to stand behind it wholeheartedly lest it fail in the field. He was, therefore, slow to seek the resources and upper management support that would have moved the project forward quickly. Ultimately, an innovation has to be one person’s responsibility.

Legitimate Resistance to Change

Overt resistance to an innovation often grows out of mistakes or overlooked issues in an implementation plan. Tacit resistance does not disappear but ferments, grows into sabotage, or surfaces later when resources are depleted. Because the advocates of change have such a clear view of an innovation’s benefits, resistance often catches them by surprise. The worst thing a manager can do is shrug such resistance aside on the dual assumption that it is an irrational clinging to the status quo and that there is nothing to be done about it. Clinging to the status quo it may indeed be—but irrational, rarely. And managers can do something about it.

Thus the beginning of wisdom is to anticipate opposition. An innovation needs a champion to nurture it, and any new technology capable of inspiring strong advocacy will also provoke opposition. Where there are product champions, there will also be innovation assassins. Assassins, moreover, can fell a project with just one well-aimed bullet, but champions need to marshal forces and nurture support to implement new technology in the face of resistance. The most common reasons for opposition to a new technology are fear of the loss of skills or power and absence of an apparent personal benefit.

Fear of Loss

As talk about the deskilling potential of new computerized technologies has grown, unions are seeking retraining for their members whom automation would otherwise displace. Many companies are upgrading the status of their workers who are forced to trade hard-earned manual skills for the often dreary routine of button pushing. Although the problem is far from being resolved, it has at least merited recognition.

There is, however, another aspect of deskilling that has been much less obvious to implementers: the simple necessity of extending concern about deskilling to foremen and supervisors. They do not, of course, actually have to run the new machinery or to possess the intimate knowledge of the system that daily operators do. Even so, giving subordinates knowledge that supervisors and foremen do not have undermines their credibility. If the foremen or supervisors worked their way up through the ranks, they will know the old machinery well. They served as problem solvers when it broke down and derived no small part of their authority from their experience with it. To train their subordinates and leave them out is to invite hostility.

When a pulp mill introduced a new computerized control room, vendor representatives trained the operators and their assistants. No similar effort was made for the foremen, who thought (with some justification) that they had lost control over the mill’s operation. Some of the operators relinquished their novel power by tactfully educating their foremen, but others felt they had earned the right to more autonomy because the foremen’s knowledge was obsolete.

One way to deal with this kind of situation is to teach supervisors how to instruct hourly workers about the new technology. These sessions should transmit details of the information hourly workers require, instructions on how best to present it, guides to practice sessions, and audiovisual aids.

Another reason for resistance is fear that the innovation will be politically enfeebling and that supervisors and even operators will lose some control by adopting it. A good implementation plan should try to identify where a loss of power may occur so that managers can anticipate and possibly avert any problems arising from that loss.

In one large manufacturing plant, corporate research developed a computerized system for scheduling the production—in small batches—of customized health care products. Although the manufacturing manager outwardly supported the idea, he never made any of the decisions or appointments necessary to put the new technology into effect. The implementation team finally realized what he had seen at the outset: using the software removed from his hands control over a key piece of his operation. The programmers working on the project reported to management information systems (MIS), not manufacturing. The manager never voiced his opposition since there was little rational basis for it, but his resistance effectively stalled the project. In this case, the programmers were quite willing, as was MIS, to report for the duration of the project to manufacturing, a change that allowed the project to swing into place.

Personal Benefit

An innovation must offer an obvious advantage over whatever it replaces, or potential users will have little incentive to use it. The more visible the costs of an innovation (financial, convenience, the need to learn new skills), the greater the importance of making potential benefits and rewards apparent. These benefits include expanded influence over work (stopping a production line), increased value of work (no in-process inventory), greater recognition (being part of a valued implementation team), solution of a longstanding problem (a shop-floor control system that gives up-to-the-minute production reports), and preservation of jobs.

It is easy for managers to forget that benefits buried in the system, which they can see because of their position, may be totally invisible to the operators on whom the success of the innovation depends. A new technology may pay off for an organization as a whole but not for individuals in any form they can recognize. That is why it is so important to make these benefits visible through encouragement from supervisors as well as through explicit and timely feedback on how the innovation is affecting workers’ output. In general, the faster the positive feedback to users, the more visible the benefits will be.

A very large natural resources company ran into difficulties with introduction of a methodology for constructing software. This approach required programmer-analysts to sit down with their clients and, following a regimented procedure with standardized notations, analyze the client’s business. A structured approach was expected to identify more potential problems at the design stage and facilitate communication between client and designer. Moreover, the company hoped that a standardized notation would facilitate the transfer of project work between programmers and cut the time spent on program maintenance.

In retrospect, it is clear that all the benefits of the new technology accrued to the organization, not to the individuals who used it. In fact, many potential users thought they would be penalized for using the new methodology, since managers judged their performance on speed and low cost, not on the quality of their output. The organization’s rhetoric supported, indeed mandated, use of the new technology, but the reward structure militated against it.

Now, contrast this situation with one in which managers gave some thought to the challenge of translating organizational benefits into individual rewards. Before installing a shop-floor control system, a major appliance manufacturer conducted informal research into the problems of the hourly work force. They discovered that the current voucher system never permitted workers to know how much their pay would be in a given week. A small modification of the control system’s design made it possible for employees to receive a report on cumulative salary with each job they entered. Although this piece of information was not central to the needs of the organization, adding it to the system’s design was a low-cost way to boost the innovation’s benefits to workers. This small feature more than compensated them for the pain of developing new skills and habits, and the advantage of the new system over the old was apparent every time they used it.

A Word about Hedgers

Besides the champions and assassins in an organization, there will always be some “hedgers,” individuals who refuse to take a stand against an innovation so that others can address their objections but who also refuse to support the new technology. They straddle the fence, ready to leap down on either side to declare that they had foreseen the value of the innovation all along or that they had known it would fail from the start. These risk-averse managers can affect the future of a new technology when they are a key link in the implementation plan. Because these hedgers are usually waiting for signals to tell them which way to leap, astute implementation managers will see to it that they receive the appropriate signals from those higher up in the organization.

Like product assassins, hedgers can be found at any level in an organization, and dealing with them effectively requires a sequence of actions. The first, and the easiest, is to persuade top management to take some kind of quick symbolic action in support of the innovation. Whether the action takes the form of a memo, a speech, or a minor policy change, it must send a signal that top management will stand behind this technology even in a budget crisis.

The second step, which is harder, is to help managers at all levels send out the right signals. If, for instance, the first step was an announcement of a new drive for quality, the second should be to increase the emphasis on quality throughout the company. If workers hear an announcement about a new quality program but continue with impunity to ship products that they know are inferior, the initial symbolic gesture loses potency. Worse, all future gestures lose credibility too.

The third step is the hardest—and the most necessary. Managers must bring the criteria used to judge the performance of innovation users into conformance with the demands of the new technology. New technologies often require new measures. If, for example, a new, structured software technique requires more time than did the old, managers must evaluate programmer-analysts less on the basis of the quantity of output than on the basis of its quality.

Further, because productivity commonly declines whenever a new technology is introduced, more accurate measurements of productivity in the old sense may lead supervisors to fear that their performance will look worse—not least because, with a fully automated system, direct labor drops but indirect labor grows.

Other adjustments might include a phase-in period for the new technology during which the usual output measurements do not apply. It might also make sense to reward people for preventing rather than just solving problems and for developing work behavior identified with the new technology. Although operators do not respond well when they view technological systems as controlling their behavior, they respond quite well when a system gives them feedback on their performance and the performance of their machines. Information increases the amount of control people have over their environment.

Converting hedgers into believers is not a simple task, but it is one more of the inescapable challenges managers face as they try to implement new technology. Indeed, as the competitive environment changes and as the systematic effects of new technologies become even more pronounced, the work of implementing those technologies will increasingly pose for managers a distinctive set of challenges—not least, the task of creating organizations flexible enough to adjust, adapt, and learn continuously.

Risk has its place in a calculus of probabilities. It applies to a specific course of action. The risk of an action is the likelihood that it will produce an unwanted result. Risk lends itself to quantitative expression, as when we say that the chances of failing to strike oil in a field are better than fifty-fifty or that the chances of finding a defective part in a batch are two out of a hundred. In the framework of benefit-cost analysis, the risk of an innovation is how much we stand to lose if we fail, multiplied by the probability of failure.

Uncertainty is quite another matter. A situation is uncertain when it requires action but resists analysis of risks. A gambler takes a risk in an honest game of blackjack when, knowing the odds, he calls for another card. The same gambler, unsure of the odds and of the honesty of the game, is in a situation of uncertainty. He can act, but he cannot estimate the risks or rewards of his action. Even so, he operates in a risk like situation because, at any rate, he has two well-defined alternatives—to call for another card or not to call for it. But an explorer lost in the woods, short of food and water, confronts even greater uncertainty: He must act even though relevant alternatives are undefined. He must invent what to do. He has no way of calculating with any precision the risks of action. He has only rough guidelines of skill and experience to help him.

1. See Donald Gerwin, “Do’s and Don’ts of Computerized Manufacturing,” HBR March–April 1982, p. 107; Bela Gold, “CAM Sets New Rules for Production,” HBR November–December 1982, p. 88; Joel D. Goldhar and Mariann Jelinek, “Plan for Economies of Scope,” HBR November—December 1983, p. 141; and Robert S. Kaplan, “Yesterday’s Accounting Undermines Production,” HBR July–August 1984, p. 95.

2. See Thomas Allen, Managing the Flow of Technology (Cambridge: MITPress, 1977).

A version of this article appeared in the November 1985 issue of Harvard Business Review.

When forced to choose between adding more user features and doing more testing most software companies decide in favor of more features?

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Which of the following terms is defined as potential of gaining or losing something of value quizlet?