INTRODUCTION Special Issue: Navigating Complexity

INTRODUCTION Special Issue: Navigating Complexity FRED PHILLIPS and DAVID DRAKE

This special issue of Technological Forecasting and Social Change reports on the conference “Navigating Complexity: The Future of Information and Learning in Organizations,” held in Wilsonville, Oregon, USA, in March 1998. An audience of 125 heard invited speakers from five countries, in two days of tutorials, practitioner sessions, research sessions, and vendor panels. An open space philosophy encouraged interaction and follow-up with speakers. The conference was underwritten by Dentsu, Inc., the Japanese advertising giant, as a reflection of their interest in the future of corporate communications—an activity that is central to the idea of the enterprise as a complex adaptive system. Catalyst Communications underwrote the significant contribution of David Drake’s time to the conference organization. Oregon Graduate Institute and the Cascadia Chapter of the American Society for Training and Development co-sponsored the conference. The event also enjoyed support from Sequent Computer Systems, Coopers & Lybrand, SAIF Corporation, CSG Visual Communications, the Business Journal, and Portland State University. Research on complex adaptive systems (CAS) at the Santa Fe Institute and elsewhere has made progress in modeling physical, chemical, and biological systems, and has started on related questions in economics. However, development of the CAS concept in the context of organizational and management research is still at its earliest stages. The advances in systems theory, mathematics and computer science on which the above progress rests should be useful also to managers and management researchers. This research opportunity coincides with companies’ FRED PHILLIPS is Professor and Department Head, Department of Management in Science and Technology, at the Oregon Graduate Institute of Science and Technology, in Portland, Oregon, USA; and is an Associate Editor of this Journal. DAVID DRAKE is Principal of Catalyst Communications in Portland, Oregon, and a doctoral student in Human and Organizational Development at the Fielding Institute in Santa Barbara, California, USA. Address correspondence to Prof. F. Phillips, MST Dept., Oregon Graduate Institute, P.O. Box 91000, Portland, OR 97291-1000, USA.

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needs for better knowledge management, better management of alliances, and many other issues relating to the flow of information into, within, and out of the business enterprise, and how this information is used. These include the need for more flexible enterprise computing solutions that do not lock the enterprise into rigid responses to a rapidly changing world.1 Research on the business organization as a CAS—the “evolutionary organization”—should focus ultimately on developing the adaptive enterprise models embodied in useful software packages. This approach strongly suggests a biological model of the firm. George Leonard [1] writes, “. . . our [prehistoric] forefathers supposedly prevailed only because of their large brains and their ability to use tools. This supposition has downplayed the prodigious human ability to create complex, well-knit social groupings, a challenge which, more than toolmaking, accounts for the development of the large brain.” Thus, we co-evolve with our organizations. Can we influence—and speed up—this co-evolution? Yes. Anthropologist Gregory Bateson (see [2], p. 356) notes that human populations, by thrusting themselves into challenging situations (such as, e.g., living at high altitudes), create the opportunity for emergent genes (for, e.g., a more efficient hemoglobin variety) to flourish. Experiments in artificial evolution of manufacturing systems ([2], p. 359) suggest that such guided evolution is speeded by learning, and indeed learning was a major focus of this conference. The biological analogy was explored in some of these articles. However, contributors were encouraged to bring multiple disciplines to bear on the question. In addition, the conference aimed at a knowledge-for-use target. Much recent writing on complexity has been either pure science on the one hand, or loosely interpretive and poetic on the other. In contrast to both of these approaches, this conference aimed to develop scientifically defensible tools for managers. To this end, speakers were given Figure 1 as a provocation. Figure 1 suggests that many disciplines can shed light on the knowledge and learning issues that are important within the organization and across its boundaries. The explicit division of these issues into “organizational” and “personal” categories highlights the truth that employees in an evolutionary organization are not passive human “resources,” but are the autonomous repositories of the enterprise’s intellectual capital. Keynote speakers Christopher Laszlo (whose book was reviewed [3] in this journal) and Virginia Whitelaw [4] took organizational and individual focuses, respectively. All speakers were urged to take a systems approach to analyzing the enterprise as CAS, for three reasons. The first of these three reasons has to do with the current trend toward the study of knowledge management and knowledge economics. When these phrases are used at conferences these days, the excitement is palpable, and one cannot but feel we are on the verge of a new scientific paradigm. But we guest editors, in our roles as chairs of the Navigating Complexity conference, believe that while this trend will yield powerful results, knowledge management as a concept is not broad enough to enable an understanding of organizational performance. For example, Baba [5] shows that reporting on informal information flows in an organization presents an ethical dilemma for scientific observers. This is because there is no surrounding system theory framework which would include notions of 1 This theme of the conference has now been reinforced by an article in The Economist (“SAP’s Rising in New York,” August 15, 1998, pp. 56–57) quoting the work of Boston University professor Thomas Davenport. Davenport’s work warns that companies may lose competitive advantage by putting the enterprise software cart ahead of the business horse; “Managers should ask whether . . . technical demands coincide or conflict with their company’s business goals.”

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Fig. 1. Map of issues and disciplines bearing on “Navigating complexity.”

empowerment, initiative, or flexibility; short-sighted managers have used these data on employees’ communication patterns to enforce stifling Taylorist work rules. A second reason why a system view is needed: Dell Computer and other companies using the “direct” model of business have shortened the feedback loop between customer needs and the design/production/inventory processes. This is an admirable example of the evolutionary management of an adaptive organization. But Tom Martin, V.P. of Dell, describes [6] how these tighter linkages increase the downside risks of suboptimization; a decision made in Department A, which under conventional business models would have been okay, had adverse effects on Department B and on the bottom line because the decision maker did not have an adequate overview of the interrelation of operations. Third, in a widely acclaimed work, Collins and Porras [7] have identified the management practices that are common to very long-lived, influential companies. It is shown that such companies are superior long-term investments. But are they the best investments? Shareholder return may be greater from spin-offs, liquidations, or the sale to another firm of the company’s well-known and long-lived brand names.2 A systems approach compels us to examine the fundamental goal, mission, and purpose of the organization whose performance we are analyzing. 2 Collins and Porras’ research design did not look at the stock performance of short-lived companies. But they remark (on page 9) that “We found the concepts in Charles Darwin’s Origin of Species to be more helpful in replicating the success of certain visionary companies than any textbook on corporate strategy.”

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It is our hope that the approach taken by this conference will stimulate much discussion and progress in understanding the organization as a complex adaptive system—that the discussion of complexity in economic organizations tracing back to the work of Simon [8], Grunberg [9], Boulding [10] and others may benefit from recent advances in mathematics and computation. Section I: Organizational Innovation, Genetic Algorithms, and Artificial Life David Goldberg, a pioneer in engineering applications of genetic algorithms, leads our special issue by providing an overview of genetic algorithms for planners and businesspeople. He shows how the structure of these tools parallels an organization’s ability to innovate, and therefore how they might be particularly useful for forecasting and planning in a complex competitive environment. Takao Terano’s article shows how, when the elements of a genetic algorithm are personified, their evolution can be regarded as “artificial life.” Moreover, these elements can interact in ways that emulate societies and organizations, hence “artificial societies.” The approach proves useful in forecasting the communication patterns of organizations with differing communications infrastructures. Section II: Contributions from Systems Theory The Phillips and Tuladhar article offers a look at one of the chief dilemmas facing modern organizations: How to maximize both flexibility (the ability to adapt) and efficiency (the ability to produce). The authors introduce a much-needed model to measure organizational flexibility in a way that can be combined with DEA studies on organization efficiency. They draw on theories of economics, systems and evolution to build their model and their case. Of particular interest to the authors was Ashby’s Law of Requisite Variety as a key consideration in modeling an organization’s ability to be flexible and adaptive. The article concludes with an analysis of ten years of financial data on a set of 44 computer-related companies—the results of which show that “companies scoring high on a flexibility measure achieve more consistent efficiency over the time span studied.” The authors make a couple of important distinctions along the way, most notably the difference between flexible (varied responses within a given business model) and evolutionary (change in the business model) firms. This work contributes to our understanding of the challenges facing organizations in a globally competitive environment. In the second article of this section, Miyazaki and Kijima categorize the dimensions of complexity and uncertainty (including regulatory complexities and uncertainties) in technology management, and use the resulting construct to supplement a patent analysis of the Japanese automobile industry. They find the industry is investing in well-understood areas such as safety while also attending to high-uncertainty areas like alternative energy plants, and that both are driven by regulation. They outline the implications for skill-building and alliance-building. Section III: Neural Nets and Learning Laxton’s ambitious article seeks to inform the practices of information technology strategy and planning by incorporating insights from the field of neural networks and in particular, the World Wide Web. The author hypothesizes that the development of the Web is similar to that of the human brain, and that this similarity can be exploited by organizations in designing their strategies. In particular, Laxton focuses on her study of web-enabled marketing strategies.

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Laxton lays out a solid foundation in current neuroscience research. Her excellent look at perception vs. cognition serves to underscore the complexities of the human mind vs. that of the machine, but points the way to understanding the power of the Web as it develops and how that power could be harnessed to serve an organization. She sees the Web as a good starting point for emulating the mind’s neural network approach to information processing and communicating. She goes on to apply these theoretical constructs to a company’s choices in technology and marketing in a rapidly changing global environment. She draws strong correlations between her explication of models and concepts from neuroscience and applications in the business sector. Continuing the thread of simulating societies based on their communication patterns, Kulkarni, Stough, and Haynes use a neural net approach to modeling the acquisition of knowledge and skills in business organizations. They find this approach meshes well with notions of Hebbian learning to represent “communities of practice,” an informal and hitherto unmodeled mode of organizational learning under a variety of information flow constraints. These communities are generally not part of the formal organization chart but are critical for knowledge transfer in the firm. This study’s model can lead to better ways of understanding the impact of communities of practice on organizational competence.

Section IV: Assessing Creativity and Learning in Organizations Ai-Tee Koh’s article provides a useful review of organizational learning and creativity which includes apposite examples from companies such as 3M, Sony, and Pepsico. Koh uses this framework to assess the progress of learning, knowledge creation, and creativity in East Asian firms. Finally, the Vincenzi and Adkins article is centered around a diagnostic tool for assessing an organization’s health relative to the desired level of anxiety to produce peak performance, and the perceptions of vitality as a function of the desired tension between the forces of rigidity and fragmentation. They build on Goleman’s work on emotional intelligence, Ralph Stacey’s work on organizations as complex adaptive systems, and the Praxis Group’s “Organizational Vitality Continuum” to build and test their model. The authors are “looking for clues as to where potential interventions will provide the highest leverage for improvement of organizational performance.” Their model looks at four key variables: purpose and values, quality of leadership and trust, diversity and innovation, and empowerment and the containment of anxiety. The article concludes with a case study based on an assessment of six organizations. Of note as well is their work on postulating a relationship between quality relationships and leveraging other forms of capital to achieve success and health in an organization. They contend that this “space for creativity” is found in the zone between rigidity and fragmentation; investments in human capital is what sustains an organization in this zone; and this space is an essential element for success in the information age economy. This article offers a much-needed and useful application of complexity theory to assessing and supporting organizational development. References 1. Leonard, George: Mastery. Dutton (Penguin Books), New York, NY, 1991. 2. Kelly, Kevin: Out of Control: The New Biology of Machines, Social Systems, and the Economic World. Addison-Wesley, Reading, MA, 1994. 3. Phillips, F.: Book: Review Laszlo, Ervin, and Christopher Laszlo. 1997, The Insight Edge: An Introduction to the Theory and Practice of Evolutionary Management. Quorum Books, Westport, CT, in Technological Forecasting & Social Change 58, 321–322 (1998).

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4. Whitelaw, Ginny: Body Learning: How the Mind Learns from the Body, A Practical Approach. Perigee/ Berkeley, New York, NY, 1998. 5. Baba, Marietta L.: Anthropologists in Corporate America: “Knowledge Management” and Ethical Angst, The Chronicle of Higher Education May 8, 1998, B4–B5 (1998). 6. Martin, Tom: “Dell Computer: The Direct Business Model.” Presentation at the IC2 Institute, University of Texas at Austin, TX, 1996. 7. Collins, James C., and Porras, Jerry I.: Built to Last: Successful Habits of Visionary Companies. Harper Business, New York, 1994. 8. Simon, Herbert: The Architecture of Complexity, American Philosophical Society, Proceedings 106 (April), 467–482 (1962). 9. Grunberg, Emile: “Complexity” and “Open Systems” in Economic Discourse, Journal of Economic Issues XII (3) September, 541–560 (1978). 10. Boulding, Kenneth: Ecodynamics: A New Theory of Societal Evolution. Sage, Beverly Hills, California, 1978. Received 7 March 1998; accepted 13 August 1999.