BEA™ Test & Learn

From a culture of plausible speculation to a culture of evidence based decisions.

Many business ideas that seem sustainable at first sight prove to be poor investments in hindsight – even when they were supported in advance with extensive calculations in excel sheets, and declared orally in a plausible manner with analyses in PowerPoint and word. This process is referred to as plausible speculation in trade jingo and often leads to an avoidable squandering of resources (time, capital, personnel, etc.) in enterprises and in politics. A business based and accurate planning alone cannot compensate in many cases for missing evidence and the thus associated unencumbered and unbiased viewpoint on the most important drivers behind an idea.

Decisions in a corporate culture that are made on operative or strategic problems due to plausible speculation have another large disadvantage: They are often incomprehensible after the fact to persons not involved in the decision process and cause high dependencies within the enterprise – and often lead to mistakes that could have been avoided in advance.

Business experiments in an evidence-based corporate culture guarantee efficient and rapid decisions. They are rationally comprehensible, reduce risk, ensure a steep learning curve in the company, and thus guarantee high and sustainable profitability.

Many leading companies and political decision makers already use test & learn settings in their decision making. This culture of experimentation allows them to set the switches for the future rapidly, based on reliable data.

Our consulting achievements

> We determine if ideas have not yet been tested – and whether they can generate a substantial economic value
> We make sure that the test and control groups are set appropriately and that they are sufficiently large.
> Statistical analyses minimize the number of necessary tests.
> Subjects are instructed and possible disturbances are removed from the test setting.
> At the same time, we guarantee that the business experiment does not disturb employees.
> Data from the business experiment are analyzed and prepared in such a way that the fewest possible side effects and biasing factors can be excluded.
> Comprehensible decisions can be made on the basis of this knowledge.
> We determine how complex the implementation of new measures will be based on the test results.
> The implementation will only follow after this.