What Ventana Models Do

Ventana® models help organizations make successful choices by applying their experience and data to understand the outcomes of actions in advance.

Ventana models deliver:

Intelligence amid mixed signals by combining human expertise and corporate data to determine the true signal.
Focus amid distractions by using cumulative knowledge to highlight new leverage.
Consensus amid multiple views by integrating knowledge and reconciling differences.
Understanding amid complexity by tracking the interactions of causes, effects, and side effects.
Confidence amid uncertainty by showing the odds and the best ways to influence them.
Longevity amid volatility by capturing insight in tools that improve as experience deepens.

The result: People making smarter choices for better performance. Ventana models improve performance by helping individuals and organizations make smarter choices. The models absorb, test and leverage the collective intelligence of experts and experience to determine which choices are most likely to improve performance, and why. By converting mountains of information into clear, compelling knowledge in the form of stories that are rooted firmly in experience, and with evidence, they help decision makers to understand the best path forward and communicate that path to the organization. How is this possible? The outcomes of an organization's actions are determined by predictable reactions and by unpredictable influences. Ventana models help decision-makers to manage both.

Predictable reactions

Organizations are deeply familiar with scores of predictable, cause-and-effect phenomena in their businesses, many of which are obvious: Growing the customer base raises demand for service. Hiring more people raises payroll expenses. Diverting resources to one area removes resources from another. A customer who buys a product may not need another one until the first one wears out. Each of these is straightforward, but two difficulties arise when trying to consider all such effects at once. First, there are too many of them. The human brain juggles only so much at one time, raising the possibility of overlooking one or another of these effects. Second, when multiple factors are interacting to influence results, it is easy to believe that the root driver of performance is one thing when in fact it is another.

Ventana models help humans manage this complexity. Ventana models track multiple, interacting influences with ease, and Ventana techniques triangulate among data, expert knowledge, and causal models to detect logical gaps and conflicts. Ventana tools move organizations from initial questions and hypotheses to clear, winning choices.

Unpredictable influences

Organizations must cope with an unpredictable environment. Economic, competitive, regulatory, natural, and other factors buffet plans and affect results. Ventana models calculate the effects of these influences across their full range of possible values, not just the historically experienced range. This addresses two important problems. First, history may not be predictive of future conditions. Second, humans tend to underestimate risk. Ventana models also account for interactions among uncertain influences, rather than assuming risks are uncorrelated. This often greatly affects results, and is crucial for early detection of brittle or vulnerable business structures. Rather than averaging together extreme opportunities with extreme vulnerabilities, or ignoring them due to low probability, Ventana models outline the whole range of possibilities, uniquely identifying both threats and leverage and explaining the odds behind them.

In addition to unpredictable external effects, all quantitative conclusions formed from models and data contain some inherent uncertainty. This is because both models and data can be incomplete or inaccurate. Ventana triangulation techniques avoid single-source bias and sift for corroborated, reliable estimates, reducing this analytical uncertainty to a minimum. The effects of data noise and model approximations are reported in the model output, and indicate the value of further information.

The resulting set of possible futures is often very different from current planning. By considering the correct range of potential outcomes, clients can evaluate their risk in advance, to design strategies that exploit the odds and defend against shocks. In the end, people, not models, are responsible for decisions. But people with good models make better decisions than people without good models. In fact, that is the definition of a good model: one that helps people and organizations succeed.