Why Ventana® Models Work

Smart choices come from solid understanding and clear communication of which actions will improve performance and why. Four qualities of Ventana models combine to yield better performance through smart choices:

• Alignment: Ventana models are focused on client choices and client performance. Inputs include all the organization's options for action, and the outputs describe outcomes by the organization's measures of success. The models are built through a responsive, flexible process to align the model with the organization's decision needs.

• Reliability: Ventana models are industrial-strength and robust, to help clients consistently choose actions that maximize the odds of success -- even in conditions never before encountered.

• Persuasiveness: Ventana models inspire confidence through demonstrable consistency with expert knowledge; through output that supports compelling, data-supported stories about what will happen and why; through realistic, easily visualized internal mechanics; and through an inclusive development process that earns the trust of the organization.

• Organizational Fit: Ventana models fit the way the organization's people spend their time and make decisions, relate to the way they think about their business, and inspire them to use the model to its full advantage.

> Alignment
> Reliability
> Persuasiveness
> Organizational Fit

Persuasiveness

Once the model has reliably helped to identify optimal choices, what makes it believable? In Ventana's experience, people believe models only if they understand and agree with the results, and with the reasons for them.
Ventana models have several features to ensure model results, and their causes, are understood:

• Simplified what-if testing: Vensim Reality Check makes it easy to demonstrate that a model responds appropriately to changes in any factor, and stores what-if questions for automatic re-testing at any time.

• Causal structure: Each equation describes a real-world cause-and-effect relationship, making it possible to describe why a model result occurs. Equations are organized through influence diagrams, and Vensim Causal Tracing makes it easy to visualize *why* things happen.

• Familiar language: Model variables are named using the client's terms for the real world concepts they represent.

• Openness: It is Ventana policy to openly share the basis and contents of models with clients. The model development process invites critique by client experts, and challenges can be stored as Reality Check statements to test for ongoing compliance at any time.

• Simplicity: Ventana models are designed to be the simplest correct description of how client decisions will affect client outcomes. This usually takes the form of a handful of linked sub-models, each of which is simple enough to be easily grasped. This structure enables people to get a solid overview in less than an hour, and facilitates complete understanding by client personnel who are able to spend more time.

While these features make behavior and causes available and comprehensible to clients, it is the collaborative building process that most develops the model's credibility. The initial model draft starts from ideas supplied by the client, and rapidly evolves in response to continuous client critique and Ventana testing. When clients find flaws in model logic, or when Ventana tests find inconsistencies in ideas, Ventana and the client work together to correct the causal description. This collaboration is crucial: quite rightly, people tend to meet new approaches and ideas with skepticism. The process of collaboration and correction allows people to move from skepticism to exploration, and from exploration to acceptance. In each project, Ventana strives to include everyone whose confidence is required for the model to be used, especially the people who will make the decisions supported by the model. Ventana also makes a point of soliciting the critique of the organization's respected experts, not only to create a legacy of their knowledge and apply it in the model, but also to increase the model's credibility for the rest of the organization. Over the course of the collaboration, all client stakeholders contribute to -- and become confident in -- the model results and the causal assumptions on which they are based.