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Just after 2:00 A.M. on 26 March 1991, the night crew at the Chaparral Steel minimill in Midlothian, Texas, cast the first production run of “near net-shape” steel beams in the United States. General Manager Lou Colatriano grinned with tired satisfaction and headed home for his first break in forty-four hours. From a sketch on a paper napkin to the first red-hot slab of metal that emerged from a patented mold to streak down the new mill line, the elapsed time was twenty-seven months. That included design, mold development, modeling, pilot runs, and construction, and it represented expertise from five companies on three continents. “One of our core competencies,” explained CEO Gordon Forward, “is the rapid realization of new technology into products. We are a learning organization.”
Every manufacturing company in the United States would like to be able to make that statement. Yet a steel mill seems an unlikely place to look for lessons on the quick commercial realization of inventions. In fact, so does any factory, as innovation is generally associated with research laboratories and development organizations. Moreover, we usually assume that the pressure to get product out the door conflicts with learning. But as speed to market becomes an increasingly important criterion of competitive success, we need to rethink our concept of what a factory is. Factories can be learning laboratories.
For decades, U.S. factories were passive service organizations to the rest of the company, churning out products designed without benefit of manufacturing input and burying product and process defects under mountains of inventory. The past decade has seen a transformation of many of these operations into low-inventory organizations dedicated to total quality and to active participation in new product development. What is the next frontier for production? In this article I suggest that it is running operations as learning laboratories.
What Is a Learning Laboratory?
A learning laboratory is an organization dedicated to knowledge creation, collection, and control. Contribution to knowledge is a key criterion for all activities, albeit not the only one. In a learning laboratory, tremendous amounts of knowledge and skill are embedded in physical equipment and processes and embodied in people. More important, however, are the nontechnical aspects, the managerial practices and underlying values that constantly renew and support the knowledge bases.
1. G. Forward interviewed by A.M. Kantrow, “Wide-Open Management at Chaparral Steel,” Harvard Business Review, May–June 1986, pp. 96–102. Organization theorists would see Chaparral’s culture as an appropriate response to such an environment. Scholars theorize that learning will not happen without a certain amount of stress and that complex, uncertain environments require decentralized, laterally linked organizations. See:
C.M. Fiol and M.A. Lyles, “Organizational Learning,” Academy of Management Review 10 (1985): 803–813; and
R. Duncan and A. Weiss, “Organizational Learning: Implications for Organizational Design,” Research in Organizational Behavior 1 (1979): 75–123.
2. Senge argues persuasively that successful leaders are systems thinkers, able to see “interrelationships, not things, and processes, not snapshots.” See:
P. Senge, “The Leader’s New Work: Building Learning Organizations,” Sloan Management Review, Fall 1990, pp. 7–23.
Other theorists similarly note how interrelated are strategy, struaure, and culture in creating learning environments. See:
Fiol and Lyles (1985).
3. I assume that learning occurs if “through its processing of information, the range of [an organization’s] potential behaviors is changed.” See:
G. Huber, “Organizational Learning: The Contributing Processes and the Literatures,” Organizational Science 2 (1991): 89.
That is, beyond contributing to an accumulation of formal knowledge bases, learning creates “capacities ... for intelligent action.” See:
G. Morgan and R. Ramirez, “Action learning: A Holographic Metaphor for Guiding Social Change,” Human Relations 37 (1983): 21. A growing literature on the topic emphasizes that organizational learning is more than an aggregation of individual learning. See, for instance:
B. Hedberg, “How Organizations Learn and Unlearn,” in Handbook of Organizational Design, eds. P. Nystrom and W. Starbuck (New York: Oxford University Press, 1981), pp. 3–27.
While the four critical activities proposed here have not been previously combined into a framework, each has been identified as characteristic of a learning organization. On problem identification and solving, see:
E. Hutchins, “Organizing Work by Adaptation,” Organization Science 2 (1991): 14–39.
On integration of internal information, see: Duncan and Weiss (1979).
On experimentation, see:
R. Bohn, ‘Learning by Experimentation in Manufacturing,” (Cambridge, Massachusetts: Harvard Business School, Working Paper No. 88-001, 1988).
On acquisition and use of external information, see: Huber (1991), pp. 88–115.
4. Chaparral managers have verified the accuracy of the descriptions of activities and events offered here, but they are not responsible for the characterization of learning laboratories in general or for the way I have analyzed their organizational culture.
5. Other researchers also imply the utility of stretch goals as stimuli for learning. Such goals may be thought of as “performance gaps” deliberately induced to motivate knowledge generation. See:
Duncan and Weiss (1979).
Itami suggests that “overextensions” and “dynamic imbalances” created to challenge the organization characterize the most successful Japanese manufacturing companies. See:
H. Itami and T. Roehl, Mobilizing Invisible Assets (Cambridge, Massachusetts: Harvard University Press, 1987).
Moreover, the goal for this particular project fits Senge’s prescription of a blend of extrinsic and intrinsic visions, in that both outside competition and improvement over prior performances are invoked: Senge (1990).
6. Morgan and Ramirez (1983) suggest that a “holographic” organization (which epitomizes a learning organization for them) is designed so that “the nature of’ one’s job’ at any one time is defined by problems facing the whole” (emphasis in original, p. 4). Similarly, from his study of knowledge creation in some of Japan’s top firms, Nonaka concludes that “very single member of the organization should be able to suggest problems ... and ... solutions.” See:
I. Nonaka, “Managing Innovation as an Organizational Knowledge Creation Process” (Rome: Technology Strategies in the Nineties Conference Paper, 21 May 1992), p. 44.
7. Quoted by B. Dumaine, “Chaparral Steel: Unleash Workers and Cut Costs,” Fortune, 18 May 1992, p. 88.
8. Argyris and Schon point out that “espoused theory” does not always influence behavior; “theory in practice” does. See:
C. Argyris and D. Schon, Organizational Learning (Reading, Massachusetts: Addison-Wesley, 1978). See also:
S. Kerr, “On the Folly of Rewarding A, While Hoping for B,” Academy of Management Journal December 1975, pp. 769–783.
9. Von Glinow argues that the most effective organizational reward system to attract and retain highly skilled people is an “integrated culture” that combines a concern for people with very strong performance expectations. Chaparral’s system appears to fit her description. See:
M A. Von Glinow, “Reward Strategies for Attracting, Evaluating, and Retaining Professionals,” Human Resource Management 24 (1985): 191–206.
10. In a macro-analysis of sixteen studies using forty-two different data samples that estimated the effect of profit sharing on productivity, the authors conclude that “these studies taken together provide the strongest evidence that profit sharing and productivity are positively related.” See:
M.L. Weitzman and D.I. Kruse, “Profit Sharing and Productivity,” in Paying for Productivity (Washington, D.C.: The Brookings Institution, 1990), p. 139.
11. This advantage was confirmed in a study by:
K. Clark and T. Fujimoto, “Overlapping Problem Solving in Product Development,” in Managing International Manufacturing, ed. K. Ferdows (North Holland: Elsevier Science Publishers, 1989).
Huber (1991) suggests a reason for the advantage: “When information is widely distributed in an organization, so that more and more varied sources for it exist, retrieval efforts are more likely to succeed and individuals and units are more likely to be able to learn. Therefore information distribution leads to more broadly based organizational learning” (pp. 100–101).
Fiol and Lyles (1985) similarly cite research showing that learning is enhanced by decentralized structures that diffuse decision influence.
12. Nonaka (1992), after describing very similar policies at Kao Corporation, observes: “Asymmetrical distribution of information destroys the equality of relationships and leads to unilateral command instead of mutual interaction” (p. 48).
13. For an understanding of the impact on communication patternsof physical proximity and centrally located common facilities, see:
T. Allen, Managing the Flow of Technology (Cambridge, Massachusetts: The MIT Press, 1977), ch. 8.
14. Interview by AM. Kantrow (1986). A remarkably similar philosophy was observed in four Japanese companies, where “employees are trained from the first day on the job that ‘R&D is everybody’s business.’ ” See:
M. Basadur, “Managing Creativity: A Japanese Model,” The Executive 6 (1992): 29–42.
Itami (1987) similarly proposes “ ‘excessive’ experimentation in production” since “experimentation and learning do not take place only in the lab” (p. 95).
15. Descriptions of Japanese best practices reveal similar strong emphasis on both on-the-job training and formal education. See, for example:
J. Sullivan and I. Nonaka, “The Application of Organizational Learning Theory to Japanese and American Management,” Journal of International Business Studies 17 (1986): 127–147.
16. For an interesting contrast in stimulating learning, see the Carefully constructed routines in the “learning bureaucracy”:
P. Adler, “The ‘Learning Bureaucracy’: New United Motor Manufacturing, Inc.,” in Research in Organizational Behavior, eds. B.M. Staw and L.L. Cummings (Greenwich, Connecticut: JAI Press, forthcoming).
17. Clearly a tradeoff exists between stability in the workforce and the diversity needed to stimulate innovation. March proposes that “a modest level of turnover, by introducing less socialized people, increases exploration and thereby improves aggregate knowledge.” See:
J. March, “Exploration and Exploitation in Organizational Learning,” Organization Science 2 (1991): 79.
However, others point to the “insistence on selection of company members at an early point in life and avoidance of the introduction of new people at higher management levels” as an important influence on an information-sharing culture:
I. Nonaka and J. Johansson, “Japanese Management: What about the ‘Hard’ Skills?” Academy of Management Review 10 (1985): 184.
Simon observes that turnover can become a “barrier to innovation” because of the increased cost of socialization:
H. Simon, “Bounded Rationality and Organizational Learning, Organization Science 2 (1991): 125–134.
Chaparral’s management takes pride in its low turnover rate.
18. Interestingly, Hanover Insurance CEO William O’Brien made a similar reference to Maslow’s hierarchy: “Our traditional hierarchical organizations are designed to provide for the first three levels [of the hierarchy] but not the fourth and fifth. … Our organizations do not offer people sufficient opportunities for growth.”
Quoted in Senge (1990): 20.
19. Such experience and knowledge sharing even at managerial levels is noted as a characteristic of Japanese organizations, which are “able to cover for an absent individual quite easily, because other individuals have a relatively greater understanding of the requisite information”:
Nonaka and Johansson (1985): 185.
See also the discussion of designing organizations with redundant skills:
Morgan and Ramirez (1983): 5.
20. Again the parallel with Japanese practice, at least as described in literature, is striking. Nonaka and Johansson describe how Japanese firms consult with outside experts, not as troubleshooters, but as educators on the general topic. It is up to the company’s own personnel to translate that newly acquired intelligence into application. See: Nonaka and Johansson (I985).
21. Kantrow (1986): 101.
22. I have argued that core capabilities almost inevitably have a flip side, core rigidities, that hamper nontraditional projects and can hobble an organization in moving to new competencies. See:
D. Leonard-Barton, “Core Capabilities and Core Rigidities in New Product Development,” Strategic Management Journal 13 (1992): 111–126.
23. Huber (1991) discusses this limitation. See also:
J. Kimberly, “Issues in the Creation of Organizations: Initiation, Innovation, and Institutionalization,” Academy of Management Journal 22 (1979): 437–457.
24. This includes Japanese transplants such as New United Motor Manufacturing, Inc., whose employees are mostly rehires from the same United Auto Workers workforce that had one of the industry’s worst labor records. See:
R. Rehder, “The Japanese Transplant: A New Management Model for Detroit,” Business Horizons, January–February 1988, pp. 52–61.
25. See the profiles of these two men in:
O. Port, “Dueling Pioneers,” Business Week, 25 October 1991, p. 17.
26. Nonaka and Johansson (1985). In fact, some management practices now being imported into the United States were advocated by younger U.S. contemporaries of Deming such as Chris Argyris, whose early books were translated into Japanese within a year of their publication in the United States. See:
C. Argyris, Personality and Organization (New York: Harper Brothers, 1957) and Integrating the Individual (New York: John Wiley & Sons, 1964).
27. See, for example, R. Rehder and H. Finston, “How Is Detroit Responding to Japanese and Swedish Organization and Management Systems?” Industrial Management 33 (1991): 6–8, 17–21;
R.T. Pascale, Managing on the Edge (New York: Simon & Schuster, 1990), ch. 9; and
G. Shibata, D. Tse, I. Vertinsky, and D. Wehrung, “Do Norms of Decision-Making Styles, Organizational Design, and Management Affect Performance of Japanese Firms? An Exploratory Study of Medium and Large Firms,” Managerial and Decision Economics 12 (1991): 135–146.
28. See, for example, M. Beer, Organization Change and Development (Santa Monica, California: Goodyear Publishing Company, 1980), ch.3.