During the recent broadcast of the 2012 Masters Golf Tournament, IBM ran an ad that highlighted the business benefits resulting from better 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 shopkeeper would decide on cupcakes or paninis depending on that day's weather forecast. This resulted in higher sales, less wasted inventory, etc. The point is that knowing customer patterns provides important business insights to better decision-making and by IBM's example improved operating performance.

While the basic tenet that business analytics is a very valuable technique is sound, the ad somewhat misleads us into thinking that business analytics can be used in such an agile fashion. I have been developing the concept and approach to Predictive Business Analytics (PBA) and find several important characteristics that were omitted from the IBM ad.

One of the more misleading characteristics is the notion that a business can switch so rapidly from one line of products to another without missing a beat. Large companies, even those that are the most agile, cannot and probably should not seek to run their business based on short-term forecasts.

Case examples after case examples have demonstrated that, for a company to use PBA effectively, it must commit to a sustained and rigorous process in order to achieve meaningful results. 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. For example, Dell manages its logistics network and its inventory of components to assemble desktops or notebooks based on customer orders. Dell's agility is in how it has configured shippable products and the supply chain necessary to manage components and assembly at an efficient level.

PBA is the technique that links levels of inventory to planned assembly labor capacity to forecasted customer orders in an orderly and hopefully cost-efficient manner. At the end, its inventory and assembly are integrated into its total business model, and customers receive ordered products in a timely manner, and Dell achieves its targeted operating margins, market share and customer loyalty.

Well, it's starting to rain today; I think I'll go get a cupcake.

Larry Maisel is the managing partner at consulting firm DecisionVu and a leader in the field of strategy and performance management. He is a regular contributor to Business Finance.

Related Articles:

Q&A: DecisionVu's Larry Maisel on Predictive Business Analytics

How to Build a Predictive Business Analytics Foundation