My favorite is #11.
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1. Develop a model to solve a particular problem, not to model the system. A model must have a clear purpose and that purpose must be to solve the problem of concern to the client. Modelers must exclude all factors not relevant to the problem. The goal is to improve the performance of the system as defined by the client. Focus on results.
2. Modeling should be integrated into a project from the beginning. The value of the modeling process begins early on, in the problem definition phase. The modeling process helps focus diagnostics on the structure of the system rather than blaming problems on the people making decisions in that structure.
3. Be skeptical about the value of modeling and force the “why do we need“ discussion at the start of the project. There are many problems for which system dynamics is not useful. Carefully consider whether the system dynamics is the right technique for the problem. Modelers should welcome difficult questions from the clients about how the process works and how it might help them with their problem. The earlier these issues are discussed, the better.
4. System dynamics does not stand alone. Use other tools and methods as appropriate. Most modeling projects are part of a larger effort involving traditional strategic and operational analysis, including benchmarking, statistical work, market research, etc. Effective modeling rest on a strong base of data and understanding of the issues. Modeling work best as a complement to other tools, not as a substitute.
5. Focus on implementation form the start of the project. Implementation must start on the first day of the project. Constantly ask, How will the model help the client make decisions? Use the model to set priorities and determine the sequence of policy implementation. Use the model to answer the question, How do we get there form here? Carefully consider the real world issues involved in pulling various policy levers. Quantify the full range of costs and benefits of policies, not only those already reported by existing accounting systems.
6. Modeling work best as an interactive process of joint inquiry between client and consultant. Modeling is a process of discovery. The goal is to reach new understanding of how the problem arises and then use that understanding to design high leverage policies for improvement. Modeling should not be used as a tool for advocacy. Don’t build a client’s prior opinion about what should be done into a model. Use workshops where the clients can test the model themselves, in the real time.
7. Avoid black box modeling. Models build out of the sight of the client will never lead to change in deeply held mental models and therefore will not change client behavior. Involve the clients as early as possible. Show the model. Encourage them to suggest and run their own tests and to criticize the model. Work with them to resolve their criticism to satisfaction.
8. Validation is a continuous process of testing and building confidence in the model. Models are not validated after they are completed nor by any one test such as their ability to fit historical data. Clients build confidence in the utility of a model gradually, by constantly confronting the model with data and expert opinion – their own and other’. Through this process both model and expert opinions will change and deepen. Seek out opportunities to challenge the model’s ability to replicate a diverse range of historical experience.
9. Get a preliminary model working as soon as possible. Add detail only as necessary. Develop a working simulation model as soon as possible. Don’t try to develop a comprehensive conceptual model prior to the development of a simulation model. Conceptual models are only hypotheses and must be tested. Formalization and simulation often uncover flaws in conceptual maps and lead to improved understanding. The result of experiments inform conceptual understanding and help build confidence in the results. Early results provide immediate value to clients and justify continued investment in their time.
10. A broad model boundary is more important than a great deal of detail. Models must strike a balance between a useful, operational representation of the structure and policy levers available to the clients while capturing the feedbacks generally unaccounted for in mental models. In general, the dynamics of a system emerge from the interactions of the components in the system – capturing those feedbacks is more important than a lot of detail in representing the components themselves.
11. Use expert modelers, not novices. Modeling requires a discipline approach and an understanding of business, skills developed through study and experience. Get the expert assistance you need. Use the project as an opportunity to develop the skills of others on the team and in the client organization.
12. Implementation does not end with a single project. In all three cases the modeling work continued to have impact long after the initial project is over. Models and management flight simulators were applied to similar issues on other settings. The modelers developed expertise they applied to related problems and clients move into new positions and new organizations, taking the insights they gained and, sometimes, a new way of thinking, with them. Implementation is a long-term process of personal, organizational, and social change.
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