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Increase Effectiveness

Evaluating critical possibilities with more
certain probabilities.

Investing in effective solutions for tomorrow’s marketplace requires executives to balance multiple and often conflicting requirements.

For example, meeting higher fuel economy standards requires automakers to sell vehicles equipped with higher levels of technology. In order to deploy new technology in 5 years, capital expenditures on research & development are required today.

However, the most cost-effective technology today will not be the most cost-effective technology in five years. And Scenaria estimates that more than 5 million unique combinations of technology could be used within a light-duty “engine”. By one manufacture, in one model year.

Companies with deep-pockets can try to pursue a development pipeline with a wide range of different technologies; a “shotgun approach” to effectiveness.

Regardless of financial reserves, all companies face the same question: given varying degrees of uncertainty and risk, how do you effectively plan for the future, while achieving commonality across conflicting targets and requirements?

In order to increase effectiveness, Scenaria uses attribute trade-offs to find optimal and robust solutions.

  • An optimal solution is determined analytically based on attribute priorities and performance. Picking the best trade offs and aligning to market needs and product targets requires an analytically driven system level view with a correct understanding of requirements

increase effectiveness optimal

  • A robust solution is determined by quantifying scenarios and evaluating sensitivity (changing market factors, attribute trade-offs, and tipping points). In simple terms it means identifying a solution that remains optimal under a wide range or variance of conditions

increase effectiveness robust


You can be certain of one thing: change. So why not plan for it? Let Scenaria help you find a choice that’s robust to market conditions, attribute trade-offs, and tipping points, and under what conditions your solution must change.