Why Predictive Analytics Is Meant for Decisions of All Sizes

Posted by: Gary Corrigan

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Nov 12, 2014 8:56:26 AM

Predictive analytics certainly has the power to influence major decisions at the top. For instance, if a company is looking into a merger, executives may want to forecast the financial risks involved or evaluate the impact the move could have on consumer demands. Or if decision-makers are contemplating a change in their current business model, predictive analytics can help them identify new opportunities that could come with the change.

However, according to James Taylor, because executive decisions have a larger reach and impact on the company, these decisions don’t completely lend themselves to analytics. These are strategic decisions that are only handled maybe a few times a year, if that. They are complex issues that require careful thought, planning, and time to arrive at an answer.

Taylor believes that predictive analytics are much better suited for making small-level operational decisions. And the evaluation should lead to some definitive conclusions, not just an assessment of a situation.

While it is important for organizations to use analytics to make smaller decisions, it is equally important for analytics to play a part in making bigger decisions—contrary to Taylor’s position. For predictive analytics to be truly effective, it should be coupled with the subject matter expertise and insight from an executive.

By using predictive analytics in strategic situations for bigger and smaller decisions, companies can gain tangible and immediate value from predictive analytics. Gaining deeper perspective on all of those “little” operational decisions can set up a clear, big-picture view for executives. When the time comes for making a bigger executive decision, decision-makers will have a keen understanding of where the organization is currently and where to take it next.

In Taylor’s view, getting proper return from predictive analytics requires understanding the types of decisions you need to make and finding out if those decisions would be bolstered by using predictive analytics. That philosophy is certainly applicable to decisions of all types and sizes.

What decisions would you look to make using predictive analytics? Let us know in the comments below.

Topics: Predictive Analytics


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