How to Use Predictive Business Analytics Effectively
- By Lawrence Maisel
- Published: 10/12/2016
During the broadcast of the Masters Golf Tournament, IBM ran an ad highlighting business benefits resulting from better predictive business analytics. In case you missed it, it visualized a small bake shop that sold cupcakes and paninis. It made the point that on rainy days, cupcakes sold better than paninis and on sunny days, paninis sold better than cupcakes. The ad emphasized that the shop keeper would decide cupcakes or paninis depending on that day’s weather forecast. This resulted in higher sales, less wasted inventory, etc. The point was that knowing customer patterns provides important business insights into better decision-making, which results in improved operating performance.
While the basic tenet that predictive business analytics (PBA) is a very valuable technique, the ad somewhat misleads us into thinking that business analytics can be used in such an agile fashion. I have been assisting clients in developing and implementing the concept of PBA and find several important characteristics omitted from the IBM ad.
One of the more misleading characteristics was the notion that a business can switch so rapidly from one line of products to another without missing a beat. Large companies, even those most agile ones, cannot and probably should not seek to run their business based on short-term forecast.
Case examples after case examples have demonstrated that to use PBA effectively, a company must commit to a sustained and rigorous analytical framework in order to achieve meaningful results. This framework is most effective when a data-driven decision management capability is integrated into a credible managerial review process. This includes the ability to establish a team of individuals with complementary skills and competencies, a repeatable set of practices and functional data and tools. Together, these are used to continuously analyze the right drivers and measures that have a strong cause and effect relationship to the decisions at hand.
Key business decisions need to be made with their likely expectation of outcomes or results. PBA is a backbone to enable more effective decision-making that recognizes how the future might play out. Dell computer illustrates an example of how PBA is applied by how it manages its logistics network and its inventory of components to assemble desktops or notebooks based on customer orders. Its agility is in how they have configured shippable products and the supply chain necessary to manage components and assembly at an efficient level.
So while predictive business analytics may seem like an esoteric distraction from your day to day business, it could be the most important thing you do this year.
Well, it’s starting to rain today; I think I’ll go get a cupcake.
Lawrence Maisel is president and founder of DecisionVu Group Inc. and co-author of “Predictive Business Analytics: Forward Looking Capabilities to Improve Business Performance”. Register for his Pre-Conference seminar, Developing an Effective Predictive Analytics Capability, here.
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