The use of analytics that include statistics is a skill that is gaining mainstream value due to the increasingly thinner margin for decision error. There is a requirement for organizations to gain insights, foresight and inferences from the treasure chest of raw transactional data (both internal and external) that many organizations now store, and will continue to store, in a digital format.
A problem, however, is that organizations are drowning in raw data but starving for information to make decisions with.
An experienced analyst is like a caddy for a professional golfer. The best ones do not limit their advice to the pro to factors such as distance, slope, and the weather but also strongly suggest which golf club to use.
There is a continuum of business analytics. The sequence is descriptive, diagnostic, predictive, and at its zenith prescriptive analytics – optimization. Few organizations have attained prescriptive analytics. It can involve linear programming. But be patient. Its time is coming. This blog discusses the third level – predictive business analytics.
Predictive business analytics allows organizations to make decisions and take actions they could not do (or do well) without analytics capabilities. Consider three examples:
These three examples are “fill in the blanks” questions. Which “X” is most likely to “Y”? One can think of hundreds of others where the goal is to maximize or optimize actions or decisions.
I was a bit loose by referencing “optimizing” as part of predictive business analytics. To clarify, with predictive analytics what-if scenario analysis can be performed. Keep incrementally changing an independent input variable (e.g., customer order forecasts) for sensitivity analysis of the model’s dependent output (e.g. sales volume, mix and profits). It is a brute force trial-and-error approach to seek the “best” answer.
Prescriptive business analytics says, “Get out of the way. Let the computer calculate the best answer.” A few software vendors are now emerging in the marketplace to do this.
With predictive business analytics, the best and correct decisions can be made and organizational performance can be tightly monitored and continuously improved. Without predictive business analytics, an organization operates on gut feel and intuition; and optimization cannot even be in that organization’s vocabulary.