The complex control tool is based on a combination of building and analysis of “quick and dirty” models of human systems or problem domains. It can be used when there is a need to think through complex, real world problems involving many perspectives and to make decisions with incomplete information in limited time.
Models (so-called Fuzzy Cognitive Maps or FCMs) can be built rapidly either individually or collaboratively with any group of stakeholders or organisational team. A preliminary model can be built and analysed within the course of a one day workshop, or even just a few hours. These models are most useful for issues which have many interconnected influences or factors of different types from many different domains, from economic, to technical to social. In many of these issues or complex systems, numerous interdependencies are thought to exist, but empirically-tested evidence on the nature of these interdepencies is unavailable or difficult to come by. Fuzzy cognitive maps, like those we help you to build, are perfect for such situations as they leverage the qualitative knowledge and expertise of groups of people in order to rapidly construct a simple network model of a specified issue. They are particularly useful when behaviour and decisions of stakeholders play an important role in determining the outcome of a system’s development; when detailed local knowledge, but not scientific data, is available; and in problems in which public or stakeholder participation is desirable or required. The model produced via an FCM process can be used for scenario testing, as a basis for designing interventions and to facilitate further discussion and interaction within/with a stakeholder group. Building these models helps all participants develop a whole-systems understanding of their problem and enhances understanding between different participants of each other's perspectives. This can be one of the most powerful aspects of the processes as different assumptions on how a problem works are made visible and can be debated.
Although the model, made up of important factors and their interdependencies, cannot give precise, quantitative predictions, the structure of the problem gives important information on how it can be managed. When resources are limited, our analysis can determine the best places to focus efforts to make change, rather than attempting to control every factor in the problem. Using our controllability analysis we can identify factors which can act as levers within the problem. That is factors which can have an impact on a large number of other factors in the problem. By combining this analysis with your knowledge of which factors you are most able to influence or control, you can explore the best ways for you to manage or change your system. Controllability analysis can help you find the most effective ways to intervene, help to identify other actors who you may need to collaborate with for best results, and can help you identify changes to which you are vulnerable and explore options for buffering your system.