The Matrix of Change

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Just as total quality management owes much to tools like statistical process control and the “house of quality,” business process reengineering can benefit from tools to supplement and focus managerial intuition.1 Unfortunately, current tools for managing change don’t do the job.2

Effective change management depends on recognizing complements among technology, practice, and strategy. Interactions play a critical role in affecting outcomes, a role that leads to new analysis and theory.3 In developing a theory of complements, Milgrom and Roberts showed mathematically how interactions can make it impossible to successfully implement a new complex system in a fully decentralized fashion.4 Instead, managers must plan a strategy that coordinates the interactions among all the components of a business system. In particular, because information technology and new organizational paradigms eliminate time, space, and inventory buffers, operations may become more tightly coupled. These linkages further aggravate change management problems and process interactions.5

In this article, we introduce a new tool, the “matrix of change,” that can help managers anticipate the complex interrelationships surrounding change. Specifically, the tool helps manage concerns about feasibility (stability of a new system of practices), sequence (which practices to change first), location (greenfield or brown-field sites), pace (fast or slow), and stakeholder interests (sources of value added). The matrix of change was inspired by formal analyses of Milgrom and Roberts and also draws on the established design principles of Hauser and Clausing.6 The implementation steps may already be familiar to anyone acquainted with quality function deployment (QFD) or the house of quality. The resulting support for process design, analogous to product design, becomes formal and systematic but remains managerially relevant and intuitively accessible.

The Landscape of Change

An old proverb states that “you can’t cross a chasm in two steps.” The same wisdom applies to many organizational change efforts. Advances in information technology (IT) and rising competition have led to new modes of organizing work. Many of these new organizational forms are complete departures from past practice instead of incremental improvements. The resulting gains for companies can be substantial. Hallmark, for instance, discarded sequential product development in favor of cross-functional teams and reduced new-product introduction time for one greeting card by 75 percent. After reorganizing, Bell Atlantic cut service order rework and saved $1 million annually, while simultaneously improving product quality.



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2. T. Davenport and D. Stoddard, “Reengineering: Business Change of Mythic Proportions?” MIS Quarterly, volume 18, June 1994, pp. 121–127.

3. A. Barua, S.H.S. Lee, and A.B. Whinston, “The Calculus of Reengineering” (Austin, Texas: University of Texas, Department of Management Science, 1995).

4. P. Milgrom and J. Roberts, “Complementarities and Fit: Strategy, Structure, and Organizational Change in Manufacturing” Journal of Accounting and Economics, volume 19, 1993, p. 179; and

P. Milgrom and J. Roberts, “The Economics of Modern Manufacturing: Technology, Strategy, and Organization,” American Economic Review, volume 80, number 3, 1990, pp. 511–528.

5. J.F. Rockart and J.E. Short, “The Networked Organization and the Management of Interdependence,” in M. Scott Morton, ed., The Corporation of the 1990s: Information Technology and Organizational Transformation (Oxford: Oxford University Press, 1991), pp. 189–216.

6. Milgrom and Roberts (1990, 1993); and

Hauser and Clausing (1988).

7. M. Hammer and J. Champy, Reengineering the Corporation (New York: HarperCollins, 1993).

8. B.J. Bashein, M.L. Markus, and P. Riley, “Preconditions for BPR Success,” Information Systems Management, volume 11, Spring 1994, pp. 7–13; and

Hammer and Champy (1993).

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R. Parthasarthy and S.P. Sethi, “Relating Strategy and Structure to Flexible Automation: A Test of Fit and Performance Implications,” Strategic Managment Journal, volume 14, October 1993, pp. 529–549.

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W.J. Orlikowski and J.D. Hofman, “An Improvisational Model for Change Management: The Case of Groupware Technologies,” Sloan Management Review, volume 38, Winter 1997, pp. 11–21.

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Milgrom and Roberts (1990, 1993).

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18. Data supplied by MacroMed based on Nielsen data.

19. Austin (1993).

20. The matrix process has evolved since its inception as a research and consulting project originating in the Leaders for Manufacturing program at the MIT Sloan School of Management.

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J.M. Harrison and C.H. Loch, “Operations Management and Reengineering” (Stanford, California: Stanford Graduate School of Business, working paper, 1995).

24. Only pairwise interactions are identified. In principle, more complex interactions may be important; for instance, two practices may be complements only in the presence of a third practice. Typically, framing the question in terms of a reference set of practices will resolve such potential ambiguities without resorting to a matrix with more dimensions.

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26. Harrison and Loch (1995).

27. Specification of such models must be done with some care since the clustering of variables will depend on the source of heterogeneity in the environment that gives rise to sample variation. See:

B. Holmstrom and P. Milgrom, “The Firm as an Incentive System,” American Economic Review, volume 84, September 1994, pp. 972–991.

28. Harrison and Loch (1995).

29. Davenport and Short (1990).

30. “Importance” can be usefully interpreted as “benefit-cost” of “the practice in isolation.” We revisit this interpretation in the section on determining net value added.

31. R.S. Kaplan and D.P. Norton, “The Balanced Scorecard —Measures That Drive Performance,” Harvard Business Review, volume 70, January–February 1992, pp. 71–79.

32. For a large system of interconnections, a graph-spanning algorithm can identify independent blocks of practices as well as connection counts within blocks.

33. An early analysis of the complete set of fifteen new practices discovered several other competing relationships. Most were associated with the practice of “line rationalization,” which seemed appealing when proposed in isolation (who could be opposed to “rationalization”?), but which conflicted with the principles of worker empowerment and flexibility embodied in many of the other practices.

34. Firms adopting the popular SAP software package report that it is inflexible in how it handles many basic business functions. Typically, this forces them to change their business practices to conform to the software’s requirements. Some customers view this as a feature, not a bug, because it compels recalcitrant managers to discard their old practices.

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36. Sterman (1994).

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38. In principle, if the new system really does create more value, then it should be possible to compensate the losers so that everyone is better off. In practice, it may be hard to determine which grievances are legitimate, so some claims will need to go uncompensated. Nonetheless, if a majority of stakeholders appear to be worse off under a new system, this is a warning sign that the change is merely reallocating benefits and not creating much new value.

Milgrom and Roberts (1990, 1993); and

D.M. Rousseau, “Managing the Change to an Automated Office: Lessons from Five Case Studies,” Office: Technology and People, volume 4, January 1989, pp. 31–52.

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40. D. Leonard-Barton, “Implementation as Mutual Adaptation of Technology and Organization,” Research Policy, volume 17, 1988, pp. 251–267; and

D. Leonard-Barton, “Implementation Characteristics of Organizational Innovations: Limits and Opportunities for Management Strategies,” Communications Research, volume 15, number 5, 1988, pp. 603–631.

41. Gallivan et al. (1994).

42. Leonard-Barton (1988).

43. Gallivan et al. (1994), p. 336.

44. Ibid.

45. J. Sterman, N. Repenning, and F. Kofman, “Unanticipated Side Effects of Successful Quality Programs: Exploring a Paradox of Organizational Improvement,” Management Science, April 1997, forthcoming.

46. D. Croson, “Towards a Set of Information-Economy Management Principles in Improving Allocation Efficiency” (Cambridge, Massachusetts: Harvard University, Department of Economics, unpublished Ph.D dissertation, 1996).

47. R. Nolan and D. Croson, Creative Destruction (Boston: Harvard Business School Press, 1995).

48. Croson (1996), p. 32; and

Croson and Nolan (1995); and

N. Rosenberg, Inside the Black Box: Technology and Economics (Cambridge: Cambridge University Press, 1982).

49. Orlikowski and Hofman (1997).

50. Sterman (1994), p. 321.

51. Sterman et al. (1996).

52. Gallivan et al. (1994).

53. M.V. Alstyne, “The State of Network Organization: A Survey in Three Frameworks,” Journal of Organizational Computing, forthcoming;

C.C. Snow, R.E. Miles, and H.J. Coleman, “Managing 21st Century Network Organizations,” Organizational Dynamics, volume 20, Winter 1992, pp. 5–20.

54. T.W. Malone, J. Yates, and R.I. Benjamin, “Electronic Markets and Electronic Hierarchies,” Communications of the ACM, volume 30, number 6, 1987, pp. 484–497.

a. T.W. Malone, J. Yates, and R.I. Benjamin, “Electronic Markets and Electronic Hierarchies,” Communications of the ACM, volume 30, number 6, 1987, pp. 484–497; and

O.E. Williamson, Markets and Hierarchies (New York: North-Holland, 1975).

b. M.V. Alstyne, “The State of Network Organization: A Survey in Three Frameworks,” Journal of Organizational Computing, volume 7, forthcoming; and

W.W. Powell, “Neither Market nor Hierarchy: Network Forms of Organization,” Research in Organizational Behavior, volume 12 (Greenwich, Connecticut: JAI Press, 1990), pp. 295–336.

c. P. Milgrom and J. Roberts, “Complementarities and Fit: Strategy, Structure, and Organizational Change in Manufacturing,” Journal of Accounting and Economics, volume 19, 1993, p. 179;


P. Milgrom and J. Roberts, “The Economics of Modern Manufacturing: Technology, Strategy, and Organization,” American Economic Review, volume 80, number 3, 1990, pp. 511–528.


The authors thank Miriam Avins, James Champy, Kevin Crowston, Michael Gallivan, Debra Hofman, Mary Pinder, Jack Rockart, Robert Sombert, Michael Tushman, the referees, and numerous anonymous individuals at “MacroMed” for helpful comments and insights, while retaining responsibility for any remaining errors in the paper. They also acknowledge the Leaders for Manufacturing Program, the Center for Coordination Science, and the Industrial Performance Center at MIT for generous financial support.

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