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Published: April 1, 1997


Getting the Most out of Re-engineering

Though re-engineering has turned into a mass religion during the 1990's -- with its true believers pushing "radical change" and a "clean slate" approach as the sure path to business nirvana -- the evidence of bottom-line payoff from these expensive projects is far from conclusive.

Re-engineering gurus take the happy experiences of such companies as GTE and Aetna to be representative of a pattern of success. Unfortunately, for each positive story there are many negative ones, most of which surface only as statistics in industry surveys.

Indeed, anecdotes about improved customer service and the successful reduction of turnaround time serve only as a starting point for thinking about salient features of good re-engineering management. A one-size-fits-all package of recommendations from the re-engineering literature is unlikely to bring significant payoffs. Instead, a more fundamental set of principles is required, one that can be applied to a wide variety of settings and readily customized for a given organization.

Toward that end, we have developed an approach we call business value complementarity. The central idea is surprisingly simple: If you correctly combine a set of factors that have a complementary value among themselves, that combination will have a significant positive impact on organizational change. The factors range from processes and people to strategies and technologies.

Put another way, the basic tenet of complementarity suggests that the value of changing two or more complementary factors in the right direction is higher than the sum of the values derived by making the same changes in one factor at a time. That is, for a set of complementary factors, the "whole is worth more than the sum of the parts."

The flip side of complementarity is that problems arise when factors are changed in isolation and the impact of such change on other parts of the organization has not been taken into account. This happens because of a lack of overall vision, myopic planning or self-interest. Some of the examples that follow fall into this category, as in the case when a company's decision structure or business processes are changed without a complementary change in the information technology applications.

The business value complementarity approach has two essential components: creating a business value model and learning how to use it.


A business value model shows your high-level performance measures (profitability, shareholder value, market growth, etc.); sector- and business-spe-cific intermediate-level performance measures (capacity utilization, inventory turnover, rate of new products, etc.); and "drivers," or design variables, involving characteristics of information technology, business processes, decision authority and incentives, among other areas.

These drivers are the "knobs" that you can turn in the course of a re-engineering project to favorably affect the intermediate measures, which in turn affect the highest-level measures.

For example, in the late 1980's, Frito Lay determined that in order to succeed in a saturated market with hostile competitors, it had to achieve sustained growth. Frito Lay also concluded that creating market niches and increasing the rate of product development would enable it to achieve that growth. As for the drivers of the business value model, Frito Lay management concluded that flexible information access, decentralized decision authority, appropriate management control systems, efficient business processes and a broad program of incentives would be critical to reaching those two intermediate goals.

At the Phillips Petroleum Company, disappointing financial performance in the late 80's forced management to conclude that the key to profitability in a new world of environmental and safety regulations and increasing global competition would involve two intermediate-level metrics: cost efficiency and higher product/service quality.

Management decided that cost efficiency would come from streamlining processes, easier information access, increased employee skills, a restructured decision authority and appropriate management control pro-cesses. As for the other metric, the company designed a number of different teams. These included "quality action" teams, which had a mandate to identify problems and recommend ways for improvement.

(The business value models for Frito Lay and Phillips are shown in Exhibits I and II, respectively, where an arrow from one factor to another implies that a change in the first favorably affects the second.)


Once the business value model is identified, the key question is in which directions and by how much should you turn the knobs? This is where complementarity comes into play.

For example, a team-based structure is expected to result in better decisions than those emerging from a strictly hierarchical design, but only when the team members have easy access to relevant information throughout the enterprise.

Consider the experience of a major credit card company that redesigned its customer service operations, but failed to provide its representatives with the necessary access to information. The customer service personnel had been empowered to make key credit-related decisions -- the only trouble was that to get complete profiles of customers, they still had to access multiple legacy systems separately. Thus, while access to information and employee empowerment are complementary design variables, management failed to consider the nature of the relationship, and focused only on empowerment.

Frito Lay started with changes in its decision authority structure and incentive systems. Unfortunately, the changes failed to contribute to the target performance measures for two reasons. For one thing, the information technology infrastructure was inadequate to provide information-sharing throughout the organization. For another, the appropriate management control processes had not been implemented for the new decision structure.

For its part, Phillips introduced team-based incentives to complement its new team structure. However, as in the case of Frito Lay, management control processes were not initially considered during the creation of the teams.

The bottom line is that neither Phillips nor Frito Lay came up with the complete business value model shown in Exhibits I and II from the very beginning. The vision of the overall value model was the culmination of a restructuring effort spread over several years.


To assess the complementary nature of relationships among re-engineering variables, or drivers, management must ask a key question: For a proposed change in any driver in a given direction (say from a strictly hierarchical to a decentralized decision authority), what changes in other driving factors are required to insure that the purpose of the change in the first factor is fully achieved?

Of course, taking factors one by one and repeating the complementarity analysis each time is painstaking and inefficient. A better approach is to identify various choices for each factor, and to analyze various combinations of alternatives in terms of their impact at the highest level in the value model.


It is incorrect to assume that all re-engineering changes must be of large magnitude. Many industry surveys show that a majority of re-engineering projects are incremental rather than radical in nature.

Our business value complementarity analysis suggests that such a piecemeal approach -- involving incremental changes heading in the right directions -- can be a rational response to budget constraints and unfavorable organizational and technological conditions. Those conditions can be anything from a lack of skills with regard to new technologies to too much heterogeneity in I.T. applications to a large installed base of legacy systems.

In other words, making radical changes may not pay off in all settings. By taking an organization's limitations into consideration, and gauging their impact on one another, our approach can help management decide just how much change is warranted.

Anitesh Barua, Anitesh Barua is an assistant professor of information systems at the Graduate School of Business, the University of Texas at Austin. He received his Ph.D. from Carnegie-Mellon University in 1991. His current research areas include complementarity-based I.T. business value and productivity assessment, organizational information and knowledge sharing, electronic commerce and collaborative systems. More than 25 of his research papers have appeared (or are scheduled to appear) in journals and conference proceedings, including IEEE Transactions on Systems, Man and Cybernetics, Information Systems Research, International Conference on Information Systems, Journal of MIS, MIS Quarterly and Organization Science.
Andrew B. Whinston, Andrew B. Whinston is the Hugh Roy Cullen Centennial Professor of Information Systems, Computer Science, Economics and Library Information Sciences, Jon Newton Centennial IC2 Fellow and director of the Center for Information Systems Management at the University of Texas at Austin. He is the editor of Decision Support Systems and the Journal of Organizational Computing, and co-author or co-editor of 20 books and more than 250 articles. He co-authored the pioneering book "Frontiers of Electronic Commerce" (Addison-Wesley).
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