The explosive growth in the homecare industry helped this particular company go from $0 to $10 million in revenue between 1989 and 1991. From ’91 to ’92, however, revenue plateaued and the company lost a major hospital account. When I came on, I needed to learn what was happening in the company and reestablish the growth pattern set in the previous years.

Challenging Mental Models

As a starting point, I began to explore the different viewpoints held by the company’s key players. Corporate management and the board of directors had opposing visions and ideas that required reconciliation in order to make progress. The board of directors saw only one problem — an inability to sell new hospital contracts. Consequently, they believed that if the company could solve the problem of selling, everything else would “work itself out.”

Management, however, saw the problem in terms of fundamental weaknesses in the company’s underlying operation and infrastructure. They believed that these weaknesses, such as internal capacity constraints, were being masked by flat volume and would become much more evident once the company began to grow again. Ironically, the growth that the board prayed for every day was management’s biggest nightmare.

To prepare the board and management for the systems work, I needed to convey several ideas. First, that the nature of progress isn’t necessarily linear but discontinuous, and, as with learning, you can hit plateaus or take giant steps. Many organizations do not grasp this concept of learning and instead follow a behavior pattern that assumes a linear, constant developmental path. I also needed to convey that there can be multiple “right” paths for strategy, and different combinations of strategies and tactics can conceivably get you to your goal. Finally, to set the framework, I had to illustrate that individual strategies can reinforce each other, cancel each other, or balance each other. Therefore, the strategies need to be viewed as interdependent, and the analysis must take into account how any two or more strategies interact.

Service Volume

By increasing service volume, service demand will also rise. If demand grows and capacity doesn’t, service quality will drop, resulting in a smaller client base (B2). In order to keep customer satisfaction and sales high, service capacity must grow at the same pace as service volume. Higher service quality will ten lead to higher customer satisfaction, which will maintain or expand service volume, revenue, and profits.

Designing the Process

We wanted to incorporate a strategic planning process with certain primary specifications. First, the process needed to help us gain a basic systems-level understanding of how our clients are generated and how they interact with us. It also needed to enable us to explicitly play through alternative scenarios, while letting us treat strategies as dynamic and interdependent, thus allowing us to model the strategies in various ways over time.

Keeping with this criteria, we felt that an approach using systems principles and computer simulation using ithink software would work best. We chose this strategy because it would require a strong understanding of basic business dynamics and would allow little room for ambiguity. It also allowed for explicit definition and debate of underlying assumptions. We wanted to go through a process that included early dialogue to lay out every assumption we were making about both the way the industry was moving and the way our company functioned. Finally, this approach allowed us to generate “real-time” learning and hypothesis-testing, which we achieved by manipulating our assumptions in real time in an interactive computer-based ithink model.

Modeling the Macro View

We started by modeling a macro view of the company and its strategy using causal-loop diagramming. This macro view included assumptions regarding how clients are generated and how the financial and operating systems of the company function. Our primary goal was to frame and illustrate the major issues in a simple one-page strategy for the company. We also wanted to high-light interdependence among the different strategics that had been proposed within the company. The team that worked on the causal loops was a subset of seven senior managers in the company who had the best embedded knowledge of the company.

The causal looping took place in a two-step process. The team knew that the board’s fundamental issue was marketing, so it started by modeling the marketing function and then looking for all of the second-stage implications that might emerge. Suppose, for example, that we are successful in marketing. Would marketing alone be sufficient to successfully move the company forward? The board’s logic was that the marketing program would generate more clients, more clients would generate more service volume, and more service volume would generate more revenue. With reasonable expense control, the result would be higher profits. The board liked that plan and wanted to keep it that way.

As we drew the causal loop diagrams, however, I posed a question — “What would happen to our service volume if we boosted marketing efforts?” (see “Service Volume”). Marketing efforts will drive more service volume. If demand grows and capacity doesn’t, service quality will drop, which will ultimately reduce our client base (B2). The key is to turn this balancing loop into a reinforcing process. If service demand grows and service capacity keeps pace, service quality will be maintained or actually increase over time. If that happens, higher service quality will lead to higher customer satisfaction, which will maintain or expand service volume, revenue, and ultimately profits (R1).

Measuring Performance Standards

A gap between performance standards and perceived performance drives investment in service capacity, which will improve quality and lead to higher customer satisfaction (R3).

This way of thinking produced new insight for the board: a marketing program is important, but building service capacity is equally critical. We needed to invest in capacity immediately to anticipate and meet service needs. The next step, therefore, was to determine what drives service capacity. Our theory was that we operate based on something we call “perceived performance,” in which we are driven by our measures of service quality against some realistic standard. The company doesn’t have well-developed standards beyond the usual measurements of cost per case, cost per visit, and other basic economic standards. Therefore, without well-defined operating standards, we had no realistic understanding of our perceived performance.

Consequently, we were brought to the question of how to drive realistic performance standards. We concluded that we needed a formal learning program under the rubric of Total Quality Management. The belief was that our perceived performance should drive a steady investment chain in process improvement, while also inciting a greater need to study business processes (see “Measuring Performance Standards”). A gap between performance standards and perceived performance would then spur further investments in service capacity, which would raise the overall service quality (R3), leading to higher customer satisfaction and an increase in service volume. With this systemic understanding, we felt comfortable endorsing the creation of a structured program in order to create knowledge that would reinforce and refine the performance standards.

We went to the board with a plan to operationalize their vision by investing in four areas: marketing, service capacity, a rigid set of performance standards, and an organizational learning approach that would drive the kind of knowledge that sets the standards. The result was that the board and our management group began to understand that there was far more than one barrier to success in the company.

The board then challenged management with an acid test: based on the systems logic, they decided to allocate some money up front to start work on building capacity. They would not approve the full program, however, unless we demonstrated that we could deliver on selling new accounts.

We found that the easy part was adding accounts. The much harder part was the other three objectives: building capacity, creating credible performance standards with that reorganization, and instituting a TQM program throughout the company. These other aspects absorbed the vast majority of our time.

For the first three to four months, my time was spent mostly on marketing and partially on systems thinking. We were able to get over the initial threshold, proving that marketing was the apparent and not the real problem. When the board saw two signed contracts within four months, they were more willing to invest in the next stage of development. The next stage of work involved building an operational model of the company, which we used to develop and test our mix and timing of strategies. The model reinforced our understanding of the need for multiple, integrated initiatives to reach our goals.

Company Learning

Through the planning process, we realized that as a company we were not nearly as good as we thought we were. This was partly because there was little history of planning in the company. Previous strategy had been developed by the board, was very top-down, and had no involvement of the operating staff. Because strategy started and ended at the level of the board and executive management, it never found its way to the operating managers who represented 95 percent of our staff and 100 percent of our revenue. It also involved little understanding of the hospital client.

Another major reason for our performance shortfall was that the board had little exposure to the operational reality of the company. The radically different perceptions held by the board and management about future prospects and risks came about because the managers were much more grounded in the reality of the company, but they had no way to communicate that reality to the board. Although the managers could easily point out the systems that weren’t working, the measurements we weren’t doing, and the level of understanding about our core business we didn’t have, that knowledge was not being transferred to the policymakers. Our systems thinking work provided a forum and a language to stimulate that communication.

Until we started asking these questions and modeling our assumptions, many people in the company did not understand certain aspects of the business — such as how a new client was acquired (see “From Causal Loops to Simulation”). For all practical purposes, our clients “materialized out of a cloud.” So what we tried to do was work back from that cloud and really educate everyone in the company about the operational realities. Through that process, we learned a great deal about our company and our client institutions. As a result of the planning process and our work with systems thinking, we have reached a better understanding of our business and a new way of communicating and testing the complex strategies necessary for future success.

Steven DeMello was president and chief operating officer of Alliance Home Care Management, Inc. I le is presently the director of healthcare practice for High Performance Systems, Inc.

Editorial support for this oracle was provided by Anne Cycle.

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Automobile racing draws more spectators than any other sport. It’s not because of the danger, although the prospect of a crash certainly holds the crowd’s interest. What brings people out, time and again, is the simple demonstration that “he who learns fastest wins, but winning once does not guarantee winning again.” The spectators as well as the drivers understand that principle intellectually, emotionally, and viscerally. Although most spectators do not apply that rule in their own lives after they leave the track, the winners do, 24 hours a day, until the next race. They exemplify the difference between learning by watching, learning by miming, and learning by doing.

“Building the Winner”

The rate of learning in automobile racing is probably the highest of that in any organized human endeavor, including in the world’s best research labs, because winning—or even finishing—requires a wide variety of successful “doing.” Each race track is unique. Each lap around the track presents different traffic conditions. Each turn on a lap presents varying road conditions. Drivers, builders, and pit crew members all have “bad hair days.” The variety, excitement, and suspense of automobile racing is why Dennis Buede of the Stevens Institute of Technology and Bill Mackey of the University of Maryland believe that it provides the ideal learning environment for their graduate students in systems engineering. Others interested in learning cultures likely would discover new answers to their questions by spending 12 hours at a race track with Roger Penske, Richard Childress, or Leonard Wood.

Winning doesn’t guarantee learning. Winning can stall learning if winners begin to think they are superior or pay more attention to garnering praise and fame than to continuing to learn. Arrogance is a sad harbinger of a has-been.

Although winning is preferable, learning by losing is another good way of learning by doing. After Vic Edelbrock, Sr., founded the Edelbrock Corporation in 1938, one of his favorite sayings was, “Buy three of each part. After we have ruined two while learning what won’t work, we will have one left for building the winner.” Sixty-four years later, Edelbrock continues learning by doing as the innovation and sales leader in the automotive high-performance aftermarket.

The Learning Group

In racing, the consistent winners have learned that assembling the most knowledgeable and motivated people is not sufficient. Rather, the key is whether the working group becomes a learning group. The diagnostic ability of the driver–crew chief pair is critical to making the right choices in more than a dozen adjustments on the car. The pit crew, through its elaborate choreography, seeks to save a tenth of a second. Back at the garage, the 20 or more engine builders, chassis builders, test and instrumentation people, and their respective suppliers must collaborate at the idea level regarding design and fabrication as successfully as the pit crew does at the physical level.

The challenge in creating a team learning culture is to harmonize competition and collaboration. Many a highly talented person, fiercely dedicated to winning in competitions, simply cannot collaborate in doing, let alone in colearning by doing. Transforming a person’s values to team winning without suppressing the urge to innovate is key. Personal and group learning must meld into a specific “feel” that permeates the team.

To carry the automobile racing analogy just a little further, consider that an engine uses air and fuel to produce horsepower for the drive wheels, which, barring loss of traction, overcome both inherent inertia and motion-induced drag to maximize the speed of the racecar. Often the fastest car does not win because the engine fails, the tires overheat, or some other weak link becomes overstressed. The winner is the fastest car that finishes. In business, air is ideas, fuel is cash, drive wheels are the products and services that carry value to customers, and traction is the strength of the network of relationships throughout the team. Horsepower feels a lot like enthusiasm, which can overcome both structural inertia and dynamic drag, also known as fear. Enthusiasm, coupled with a learning culture, can even transform negative energy into increased motivation, which leads to superlative results.

Where is the learning? Learning is everywhere and happens every time someone wonders which ideas to pursue, what proportion of profits should be used for what purposes, how to generate enthusiasm, or whether the wheels are spinning because the right relationships do not exist. However, lack of knowledge or integrity—or too much greed— can overstress any one of these factors and create a loser.

Most organizations cannot get a grip on learning. Learning is necessarily multifaceted, but most organizations are filled with linear thinkers (this event causes that result) or scenario thinkers (these related events combine to cause that pattern of results) but few thinkers who consider entire systems (when salespeople overcommit our production, the factory output is actually below full capability). Besides, when joining the race, most organizations believe that business is about generating profit, not about learning.

Types of Doing, Types of Learning

Doing does not guarantee learning. Performing mindless activities by rote takes a long time, and the doer ends up learning little. Achieving a straightforward goal that is well within reach contributes more learning, but not all that much. When a person takes on a challenging goal at the edge of the unknown, learning accelerates.

There are at least three types of learning by doing. One type takes place at the visceral level, as demonstrated by the choreography of the pit crew. Another type exercises the mental level, as can be seen by drivers who learn as much or more between races and during the off-season as they do out on the track. Of course, in this instance, the driver is learning through reflection, examination, and practice—a kind of doing and learning that is very different from that which takes place during an actual race. This type of learning is also reported by golfers, who watch instant video playback to study their swing.

The third type of learning by doing is less tangible. It involves formulating propositions and vetting them in order to delete the ones that do not make sense. This kind of learning is often mistaken for abstract thinking or the dialectic of logicians. However, it is different in two ways. First, the effort is to understand a system of relationships and their dynamics, and to develop several propositions and focus on how they interact. Second, it is more than a mental exercise because the person becomes one with the physical world and arrives at a heightened understanding and sense of harmony. This phenomenon is reported not only by racecar drivers but also by musicians and other performers. And in a group setting, the ability to share this “feel” determines who becomes a part of the team and who does not.

Doing is what causes all types of learning to occur. Other ingredients of learning are purpose, nourishment, tenacity, and time. But without the doing part, as is well known, retention suffers and the ability to apply what was learned degrades quickly. And the vetting of doing helps ensure that what is applied makes sense.

Realistic Simulations

A good alternative to practicing doing in the real world is to practice doing in a simulated world, especially for the second and third types of learning. An effective learning culture arranges for the joy of achievement while immersing participants in realistic environments that protect them against undue penalty for error (no sense discovering gravity by being the apple). This aspect of a learning culture creates opportunities for the learner to discern, firsthand, without chance for denial, the results of his or her decisions. Such objectivism is essential. Just as scrimmaging is a valuable form of doing, realistic simulations hasten learning.

An airline pilot is not allowed to fly a real jet without first spending hours in a flight simulator. The same should be true for CEOs, who all too often are hired without anyone testing whether they can cope with the challenges of the job. This insanity is slowly coming to an end. GE’s manager development program has used business simulations for more than 40 years, most authored by David Sims. Also, several rudimentary management games are now commercially available.

As managers begin to emerge from the video game generation, this way of learning by doing will become standard practice, probably even featuring tournaments on the Internet. In fact, the technology exists with which managers can build business simulations by describing their own enterprises. Such descriptions can be translated to a computerexecutable program that exhibits the characteristics of the enterprise as if it were actually operating. Beyond allowing team members to scrimmage in a “war games” fashion, this software can be executed as a situationally sensitive TelePrompTer that guides managers and nonmanagers alike as each acts out his or her role. It can even ensure that legal and ethical guidelines are honored while business is carried out on behalf of all stakeholders.

Such software will also show what is not happening. Quality guru Phil Crosby has noted that as organizations get larger, managers find it increasingly difficult to know what is happening and practically impossible to know what is not happening. Realistic business simulations that let employees play the roles of competitors can help this situation. Further, because simulations lead to a high-fidelity representation of the enterprise, minute by minute, such folding of planning and reflection onto operations allows managers to perform, adapt, and align simultaneously, which is the ultimate in learning by doing.

MYOB

Who is qualified to prepare such simulations and models? Only those involved. MYOB, model your own business, is the best advice any manager can receive. When managers set out to see their business as a system, to describe the entities and relationships, and to reach consensus on what actually goes on in the business, they pursue a challenging goal that pays great rewards when achieved. An amazing number of viewpoints and disagreements that have been corroding business processes rise to the surface. No wonder larger companies are less productive and innovative than smaller ones are. They have exponentially more unresolved, even unrecognized, conflicts that interfere with their attempts to learn.

Modeling fosters the third type of learning by doing described earlier: the doing that develops systems thinking. When people construct a model of their organization, they come to a deep understanding of the elements at work and how they interact. They realize, for instance, that responses to requests are determined more by the nature of the interactions than by the competency of an individual.

However, we do not want to engage in just intellectual systems thinking. We want systems doing—systems thinking that is grounded in realworld results, as in the first and second types of learning by doing. To return to automobile racing, for example, we may decide that a greater angle on the aerodynamic lip at the rear of the car will shorten the time through Turn 4. It does, but it causes the car to push, thus putting wear and tear on the tires during Turn 2. This vetting of hypotheses is accomplished in minutes at the race track instead of hours in the wind tunnel or at the computer-aideddesign workstation. In this way we shall learn to model, and thus manage, the key entities in a business system: the people and, more important, their relationships.

We now have the technology to do so. Rudolph Starkerman has produced a model of robots in groups engaged in a process. He has associated the 23 parameters in this model with the attributes of a person involved in a one-on-one interaction.* We can now explore how these parameters implicitly interact to establish the trajectory of the microculture that will be created by any set of people. We can anticipate the effects of environment, nourishment, and purpose on colearning. Further, we can show people what they are doing for, and to, one another that is at odds with their best interests. In this way they can understand both the best learning culture and how to encourage it.

The third type of learning by doing, systems doing, is a prerequisite to arranging, implementing, and sustaining a culture for tripartite learning. No longer must we manage with linear archetypes, which allowed the multibillion-dollar debacle known as business process reengineering. No wonder all those employees with common sense rebelled. Ironically, their rebellion gave rise to programs for quelling resistance to change, which, based on further linear thinking, proved equally futile.

Doing While Learning

With systems doing, we can observe a set of people voluntarily bound by mutual purpose. Each acts independently, no two alike, such that the combined effect takes them closer to their goal. Each coadapts as his or her individual situation changes so that together they are still pursuing their goal. Such coadaptation necessarily involves colearning, which, of course, happens fastest through collaboration. This is not a picture of a utopian company. This is a description of the moment-by-moment doing while learning in today’s few leading-edge enterprises.

Some managers are still convinced that the organization is too busy to take time “away from work” for learning. Once we understand the selfaligning and self-cleansing power of learning by doing, we will be able to create true learning cultures. When we all spend our days learning by all three types of doing, then we will all be winners.

Jack Ring has 50+ years of experience as an intrapreneur and executive in a variety of businesses. He is currently cofounder of Kennen Technologies LLC, OntoPilot LLC, and Educe LLC. Jack is a Fellow of the International Council on Systems Engineering, an Industrial Fellow of the Stevens Institute of Technology, School of Systems and Enterprises, and a Senior Analyst with Cyon Research.

* Starkerman’s work is summarized in William L. Livingston, Friends in High Places (FES Publishing, 1990), Appendix 1.

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But although such problems may seem intractable, there is a creative power underlying most conflicts that, if tapped, can energize a group, community, nation, or even the world, as people work collaboratively to improve their situation. By focusing not on the symptoms but on the roots of problems, people can transform deep conflicts into opportunities for participatory and systemic change. By envisioning a different future, they can change conflict from being a barrier to hope and a cause of hurt into a doorway to healing and fulfillment of mutual needs.

Beginning in early 2001, groups in Cincinnati began to successfully apply participatory tools for engaging conflict and transforming an intensely emotional debate about racial profiling into systemwide change. After a six month process of visioning and consensus-building, representatives from various stakeholder groups reached agreement on a five-point platform for change. This platform in turn served as the foundation for a collaborative settlement agreement that launched a new era in police-community relations in the city by marrying ongoing community participation with structural reforms. This model will be studied and replicated throughout the U. S. for years to come. We’ll describe what was learned during the process, what worked and what can be improved, and how you can adapt a similar approach to situations within your communities and organizations. We rely on a systems thinking approach to shed light on the process and describe the benefits of integrating simulation modeling into efforts to resolve seemingly impenetrable clashes.

The Cincinnati Collaborative

In 1999, Bomani Tyehimba, an African-American businessman from the west side of Cincinnati, claimed that two police officers had violated his civil rights by handcuffing him and unjustifiably pointing a gun at his head during a traffic stop. Then in November 2000, an African-American man suffocated while in police custody after being arrested in a gas station parking lot. These events led the Ohio chapter of the American Civil Liberties Union to join forces with the Cincinnati Black United Front and Bomani Tyehimba to file a class-action lawsuit against the Cincinnati Police Department. The suit alleged that the department had treated African-American citizens differently than other racial groups for more than 30 years. Through this action, the petitioners hoped that a judge would issue a court order or a consent decree that would force the Cincinnati police to change the way they conducted internal investigations and would mandate that they collect data about the handling of traffic stops and other incidents.

The federal judge assigned to the case, Susan Dlott, did not believe that traditional litigation was the answer to the problems of alleged racial profiling. In her view, court action would only further polarize the parties and would not solve the social issues underlying the police-community conflict. Through Judge Dlott’s efforts, all parties eventually agreed to set aside normal litigation and instead pursue an alternative path of collaborative problem solving and negotiation. In April 2001, Jay Rothman was retained as special master to the court to help mediate and guide the parties along this new path.

Jay began holding regular meetings with leaders from the three sides—police, city, and community. He first proposed to launch a problem-definition process, suggesting to the parties that without a common definition of the problem, they would have difficulties finding a common solution. However, the police leadership strongly resisted this approach. They argued that focusing on problems would only result in finger pointing—at them! Moreover, the police and city attorneys were unwilling to engage in an effort to define a problem—racial profiling—that they simply did not agree existed.

In response to these concerns, the mediator suggested that the parties instead undertake a broad-based visioning process focused on improving police-community relations. The city and police department accepted this proposal because it seemed a constructive way for representatives from all parties to work collaboratively. The leaders of the Black United Front found this approach appealing largely because it was to be conducted within a framework that promised some form of judicial oversight during the process and after its conclusion.

Thus, only weeks before the city was engulfed in riots in April 2001 following the police shooting of a young African-American man, an ambitious collaborative process called the Cincinnati Police-Community Relations Collaborative—was launched. Jay appointed representatives from the Cincinnati Black United Front, the American Civil Liberties Union, the Cincinnati city and police administration, and the Cincinnati Fraternal Order of Police as his Advisory Group. As its first act, the group decided to invite participation from all citizens in the goal-setting/visioning process. Based on previous studies of tensions in police-community relations, they organized the population into eight stakeholding groups (African-American citizens, city employees, police and their families, white citizens, business/foundation/education leaders, religious and social-service leaders, youth, and other minorities). With considerable cooperation from the media, the Advisory Group invited everyone who lived or worked in Cincinnati or were from surrounding suburbs to answer a questionnaire and participate in feedback groups to envision a new future for police-community relations. Thirty-five hundred people responded, and some 700 of those respondents engaged in follow-up dialogue and agenda-setting.

A Broad-Based Process

The Cincinnati Collaborative used methodologies for engaging conflict (the ARIA Process) and for involving stakeholders in forming goals and action plans to shape the future (Action Evaluation). Citizens and oth ers were invited to answer a simple What, Why, How questionnaire, either online or in writing:

• What are your goals for future police-community relations in Cincinnati?
• Why are those goals important to you and what experiences, values, beliefs, and feelings influence your goals? and
• How do you think your goals can best be achieved?

After only a month of a “getting out the voice” campaign, the Collaborative sponsored the first of eight four hour feedback sessions, this one held by religious and social-service leaders at a local church. Following this first session, at a pace of one or two a month for the next six months, members of each stakeholder group were invited to meet with other members of their own group to dialogue about and reach consensus on a platform of principles. Participants in each feedback session selected representatives to work with representatives from the other groups to craft a platform of goals for improving police-community relations (see “Vision of the Future: A Collaborative Platform”). This intergroup platform then guided negotiators, who were the lawyers for the parties who had served all year on the mediator’s Advisory Group, as they worked to successfully craft a settlement agreement.

Judge Dlott ratified the agreement, which will be implemented over five years at a cost of $5 million. In addition to court oversight, the lasting power of the process is that it engaged people’s hearts and hopes.

People’s responses to the questionnaire—especially their “why” stories—captured their concerns about fairness and respecting differences, needs for safety, and expressions of support for the police. The discussions that they participated in were tremendously powerful. They enabled the citizens of Cincinnati to experience resonance with one another—to find commonalities between their own and others’ fears, hurts, hopes, and dreams (see “Participants’Voices”).

Many found this outlet to express themselves critical—up until that point, they felt that they were not being listened to and that their concerns were not being heard. As a young African-American woman said, “When we felt pain, no one from the city came to listen to us. We needed someone to comfort and listen to us.” Healing began as city leaders finally heard people’s ideas. The inclusive and participatory process has helped citizens feel a sense of ownership for the agreement and move from fear and mistrust to cooperation and joint problem solving. The ability and willingness to truly listen and hear others will continue to be critical as Cincinnati’s citizens and public officials begin to implement the changes that are outlined in the settlement agreement.

A Systems-Informed Solution

In Cincinnati, citizens, public officials, and the police force came to realize that the city needed to move away from enforcement-style policing and toward problem-oriented policing. These two styles represent two ends of a continuum. Enforcement-style policing focuses on the apprehension and prosecution of criminals. Public safety experts have begun to question the enforcement paradigm in recent years for a variety of reasons, not least of which is the struggle to deal with increasing tensions between police and minority communities. These minority groups often feel unfairly targeted by police enforcement activities.

Whether real or perceived, such allegations serve to highlight a problem with the enforcement paradigm, especially in modern American cities with poor, minority neighborhoods. Poverty is considered a leading indicator of crime; that is, the higher the poverty rate in a given area, the higher the crime rate will tend to be. Cincinnati’s Over-the-Rhine and West End neighborhoods are examples of areas with extreme poverty and also high crime rates. Unfortunately enforcement-style policing does not foster good relationships between police and community members in these kinds of communities, because residents often feel that the police aren’t concerned with what they perceive to be the most important issues, such as vandalism, weapons, and other quality-of-life issues. While most community members and police officers agree that violent criminals must be apprehended and prosecuted, they agree less on other policing priorities.

TWO POLICING STRATEGIES

The enforcement approach (the first outflow) seeks to reduce the stock of safety issues by enforcing the laws. Through the Cincinnati Collaborative, stakeholders emphasized more of a problem-solving approach to prevent crimes from occurring (and entering the stock of safety concerns) in the first place by mitigating underlying conditions.

In problem-oriented policing, officers seek to build a working relationship with the community to address quality-of-life issues. Problem oriented policing requires citizen input and involvement. By centering on solving problems with the entire community instead of on simply apprehending and punishing criminals, this model transforms police community relations and prevents crime from happening in the first place. It should not be surprising that a recommendation for problem oriented policing would result from a participatory process such as the one used in Cincinnati.

For community problems to be effectively identified, analyzed, and addressed, citizens and police officers must be able to trust, understand, and communicate with each other in a productive manner. The collaborative agreement signed on April 5, 2002, two days short of the anniversary of the riots, provides for specific mechanisms for police officers to collect the input and concerns of community members and to incorporate this data into their patrolling and policing activities. Through its emphasis on problem solving, the agreement encourages the police to foster working relationships with the residents they serve. In the spirit of mutual accountability, the agreement also spells out through its “community partnering plan” that citizens must be willing to work with police officers to address problems and create solutions. In this way, the police and citizens have formed a mutually beneficial, proactive partnership with the goal of creating safety, respect, and trust.

A Systems Thinking Analysis

Why has the collaborative process described above worked so well? Although we didn’t use system dynamics models in the Cincinnati case, we have done so retrospectively to shed light on how and why the approach was successful, what the implications are for the solution, and where implementation problems might occur. The purpose of these models is not to discover “the Truth” about what happened, or to accurately predict what will happen; rather, we’re trying to build the most useful theory—open to testing!—of why the process has gone the way it has, and to use that theory to think about possible futures.

We’ll start with the solution of implementing a problem-oriented policing strategy (see “Two Policing Strategies”). We can think of safety issues in a community as a “stock.” The stock of safety concerns continually grows as crimes occur and diminishes as they are resolved, usually through the arrest and prosecution of perpetrators. (For an introduction to the language of stocks and flows, go to www.pegasuscom/stockflow.html.) The enforcement approach (the first outflow in the diagram) seeks to reduce the stock of safety issues by enforcing the laws. Through the Cincinnati Collaborative, stakeholders agreed to address safety issues differently. They emphasized adopting more of a problem-solving approach. Such an approach attempts to prevent crimes from occurring (and entering the stock of safety concerns) in the first place by mitigating underlying conditions and focusing more generally on quality-of-life issues within neighborhoods.

The key to making this process work is the active participation of community members in partnering with police to identify and reduce these underlying conditions. Unless residents work closely with the police and city staff, the problem-solving approach will be impossible to implement. So, let’s turn our attention to how community members become active participants. As you’ll see, the model suggests that the visioning process employed in Cincinnati was instrumental in beginning to develop such contributors.

During the intervention, some members of each stakeholder group were what we might call “Grudging Participants” (see “From Grudging toActive Participation”). In the initial meetings, Jay noticed the difference in commitment between individuals who were accepting of and those who were enthusiastic about participating. He wondered how to motivate everyone to take equal ownership for the process. In this case, an unfortunate turn of events actually spurred the participants to new levels of engagement the riots in early April 2001. They dramatically surfaced the problems in the city for all to witness and focused energy and attention on trying to address underlying causes. Optimally, however, groups seeking to emulate this collaborative process can launch their projects in a more proactive way before a crisis requires it!

By getting 3,500 people to discuss their dreams for the city—how it should work and feel—stake holders began building trust and creating a shared vision. Somewhat uncharacteristically, the media seemed to capture this positive outlook as well. This virtuous cycle led to higher levels of participation and commitment to a vision. The end result: There are now more and more active participants involved in the problem-solving approach to combating crime (see R1 and R2 in “From Grudging to Active Participation”). That’s the good news!

Looking Ahead

But, of course, there’s more. The initiative is only beginning. The community must identify and avoid potential barriers to success. To do so, the Cincinnati Collaborative must:

1. Build greater levels of trust (keeping participation high)
2. Avoid reverting to an enforcement approach (preventing a loss of trust)
3. Give them selves time and resources to show success with the problem solving approach (building more trust and shared vision)

Although a participatory process should automatically build trust, several factors threatened to prevent this from happening in Cincinnati. One of the African-American stakeholder groups, the Black United Front, was instrumental in filing the proposed suit against the city. A large part of their strategy was to keep pressure on the civic institutions through negative press and an ongoing economic boycott, even while the collaborative process was forging ahead. So while on the one hand the Black United Front was participating in the collaborative process, they were also continuing their more adversarial activities.

Also, it’s unclear whether the city’s involvement in the Collaborative was a strategic decision—to address social problems through an inclusive process—or merely tactical so it could avoid litigation. As the Black United Front continued to take confrontational actions, the city’s participation became increasingly lukewarm and inconsistent. In this negative cycle, each side was able to cite ample evidence to support its own assumptions about the other side’s antagonistic goals and motivations. The danger in this pattern of behavior is that, over the long run, it might undermine trust. If so, active participants might cease contributing. Let us hope that the momentum of the agreement itself will indeed prove the saying that “Failure is an orphan while success has a thousand parents.” If so, all sides will appropriately share credit for the agreement and work to ensure its fulfillment. Another issue is that, if the level of safety doesn’t increase to satisfy the community’s or police’s expectations, the police will tend to fall back on the more traditional enforcement approach—with the support of some residents. African-American citizens might experience such enforcement activities as racial profiling—something that would seriously reduce trust and perhaps convince many residents to stop participating in the collaborative process. This scenario could undermine or reverse any progress made!

FROM GRUDGING TO ACTIVE PARTICIPATION

The process of building shared vision together—along with the crisis spurred by the April 2001 riots—helped move grudging participants into the stock of active participants. The reinforcing loops (R1 and R2) create a virtuous cycle of increasing numbers of Active Participants.

Thus, in order to keep the current virtuous cycle going, the city must practice the problem solving approach intensively enough to show some improvements in important indicators of safety and quality of life. And leaders should widely publicize those successes. Doing so will keep stakeholders involved (because they’ll see the fruits of their efforts) and also bring others into the process.

What Systems Thinking Adds

Systems thinking isn’t just useful in doing an “after the process” analysis (as described above), but also as part of the development of an intervention. In any conflict that involves multiple stakeholder groups, because participants have different backgrounds and perspectives, they often have difficulty understanding each other. Building systems thinking maps (similar to those in this article) requires stakeholders to use a common language to refine a collective “mental model” of the important system behaviors they wish to address. To be successful, a systems thinking approach also must involve voices from all parts of the systems, giving participants the chance to hear other points of view.

This common language encourages stakeholders to answer the crucial questions: How does this system work and how is it producing the behavior that we see? We used this framework to develop the maps above to determine what convinces stakeholders to participate in the Collaborative and what might cause them to stop participating. Also, because the process of building and refining a collective map breaks down the “us versus them” barriers, participants generally come to trust each other more.

Further, if they desire, a group can convert their maps into computer models to run in public sessions or even over the Internet. Using these simulation models, interested parties can see if the agreed-to goals are achievable, and if so, what strategies would be necessary for achieving them. In this way, the models help participants reach agreement on appropriate goals and strategies and understand how the system will behave over time as the strategies are being implemented.

For example, we mentioned that in the Cincinnati case, the police might begin to feel pressure to revert to an enforcement approach—and that much of the pressure might come from the community! A model can simulate how this pressure might arise and show that if the police and community can ignore it and stick to the new policing strategy, then the pressure will subside as the new approach begins to show success. When people see this “worse before better” dynamic play out in a computer simulation, they are generally better able to wait it out in real life.

Suggestions for Similar Processes

For other organizations and communities experiencing conflict around a contentious issue, the Cincinnati experience holds tremendous promise. Here are some suggestions for how to implement (and improve on) the process employed there:

1. Identify stakeholder groups.
2. Work with both individual stakeholder groups and cross-stakeholder groups to identify What, Why, and How goals (consider employing or adapting the Action Evaluation Process described at www.aepro.org).
3. Use the systems thinking language of stocks and flows or causal loop diagrams to focus discussion and identify high-leverage goals.
4. Build simulation models to explore policies for achieving the goals (optional).
5. Assemble a cross-stakeholder group to refine the goals during an iterative process of exploring diagrams or models, reflecting, and engaging in dialogue.
6. Communicate the resulting goals to others in the stakeholder groups. Use public forums, workshops, and perhaps even the Internet to engage others in the process and make the goals a reality.

The conflict engagement process used in Cincinnati is already a dramatic improvement over the adversarial and legal approach traditionally taken in such situations. Many positive things have resulted, including the development of five goals that all stakeholders agree are worth trying to accomplish. The most important outcome is the commitment by citizens, public officials, and the police department to a community-based problem-solving approach.

By developing the goals together through a participatory framework, the stakeholders have created the foundation for a shared vision of what the community should be and how citizens and city officials should work together. From a systems perspective, this shared vision may be the most crucial component in ensuring the long-term success of the agreement. Only time will tell how the agreement will affect Cincinnati’s well being and if it will be the beginning of the deep healing process the city needs after many years of racial unrest. Systems thinking—as used in this article and as part of similar stakeholder processes—can help us understand how new behaviors will ultimately unfold and create positive and self-fulfilling prophesies.

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