Team Learning and Systems Thinking in Management

TEAM LEARNING AND THE FIFTH DISCIPLINE

Both the perspective and the tools of systems thinking figure centrally in team learning.

David Bohm’s work on dialogue is informed throughout by a systemic perspective. In fact, an integrating thread throughout Bohm’s work has been to continue to advance the perspective of “wholeness” in physics. Bohm’s primary critique of contemporary thought, the “pollution” in the stream of collective thinking, is “fragmentation,” the “tendency of thought to break things apart.”

Likewise, the approach taken by learning teams to defensive routines is intrinsically systemic. Rather than seeing the defensiveness in terms of others’ behavior, the leverage lies in recognizing defensive routines as joint creations and finding our own role in creating and sustaining them. If we only look for defensive routines “out there,” and fail to see them “in here”, our efforts to deal with them just increase the defensiveness.

The tools of systems thinking are also important because virtually all the prime tasks of management teams—developing strategy, shaping visions, designing policy and organizational structures—involve wrestling with enormous complexity. Furthermore, this complexity does not “stay put.” Each situation is in a continual state of flux.

Perhaps the single greatest liability of management teams is that they confront these complex, dynamic realities with a language designed for simple, static problems. Management consultant Charles Kiefer says it this way: “Reality is composed of multiple-simultaneous, interdependent cause-effect-cause relationships. From this reality, normal verbal language extracts simple, linear cause-effort chains. This accounts for a great deal of why managers are so drawn to low leverage interventions.” For example, if the problem is long product development times we hire more engineers to reduce times; if the problem is low profits we cut costs; if the problem is falling market share we cut price to boost share.

Because we see the world in simple obvious terms, we come to believe in simple, obvious solutions. This leads to the frenzied search for simple “fixes,” a task that preoccupies the time of many managers. John Manoogian, director of Ford’s “Project Alpha,” says, “The find and fix mentality results in an endless stream of short-term fixes, which appear to make problems go away, except they keep returning. So, then, we go off and fix them again. The find and fix experts will go on forever.”

The problems compound in a diverse, cross-functional team such as a management team. Each team member carries his or her own, predominantly linear mental models. Each person’s mental model focuses on different parts of the system. Each emphasizes different cause-effect chains. This makes it virtually impossible for a shared picture of the system as a whole to emerge in normal conversation. Is it any wonder that the strategies that emerge often represent watered-down compromises based on murky assumptions, full of internal contradictions, which the rest of the organization can’t understand, let alone implement? The team members genuinely resemble the proverbial blind men and the elephant—each knows the part of the elephant within his grasp, each believes the whole must look like the piece he holds, and each feels that his understanding is the correct one.

This situation is unlikely to improve until teams share a new language for describing complexity. Financial accounting is a widely shared language of business. But accounting deals with detail complexity not dynamic complexity. It offers “snapshots” of a business’s financial condition, but those alone do not explain the processes that created it. Senge considers several alternatives to accounting as a business language. These include competitive analysis, “Total Quality,” and, though much less widely used, scenario methods such as those developed at Shell.16 He argues that these tools give insufficient attention to dynamic complexity.

The systems archetypes offer a potentially powerful basis for a language by which management teams can deal productively with complexity. As teams learn the basic archetypes, they can discuss underlying structures and leverage rather than concentrating on crises and short-term “fixes.”

In Senge’s ATP case, the management team focused on meeting monthly and quarterly sales targets. Systems archetypes would have helped them examine a consequence of that focus. In particular, they would have realized that when they increased pressures to meet sales targets, they communicated very clearly to the salesforce the message: “When push comes to shove, it’s better to pursue the low-risk additional sale to a current customer than the high-risk effort to create a new customer.” This “shifted the burden” from building their customer base to making more sales to existing customers, thereby making them more dependent on a few key customers.

If the corporate managers had likewise been able to see and discuss this structure, they would have been able to surface their concerns about Jim Tabor’s management more effectively. Rather than wrestling with how they could raise issues that might appear critical of Tabor’s management skills and unsupportive, they could have simply laid out the two feedback processes and inquired into how any of them could be more confident that the fundamental solution of broadening the customer base was receiving adequate attention.

Systems archetypes can help “objectify” conversations about complex management issues. The conversation becomes about “the structure,” the systemic forces at play, not about personalities and leadership styles. Difficult questions can be raised in a way that does not carry innuendos of management incompetence or implied criticism. Rather, people are asking, “Is the burden shifting to selling to current customers versus broadening our customer base?” “How would we know if it was?” This, of course, is precisely the benefit of a language for complexity—it makes it easier to discuss complex issues objectively and dispassionately.

Without a shared language for dealing with complexity, team learning is limited. When one team member sees a problem more systemically than others, the insight can be difficult to communicate without a shared vocabulary. On the other hand, the benefits of teams developing fluency in the language of the systems archetypes are enormous, and the difficulties of mastering the language are actually reduced in a team. As David Bohm says, language is collective. Learning a new language, by definition, means learning how to converse with one another in the language. A team can develop that vocabulary by using it to discuss its own problems.