The “engine” that drives OIS’s most profitable forecast is the solution to a problem Professor Kotler et al. have spent more that fifty years trying to solve. Specifically, how to size and allocate the S of SG&A most profitability. Please see OIS’s Solution for a process description of how the OIS’s most profitable forecast is developed.

Interestingly, OIS’s forecast also extends a current forecasting best practice to the best possible forecasting practice. The current best practice was with the author in the following quote from Professor Hanssens, UCLA’s Anderson school of business.

“Perhaps one additional perspective is the value of combining judgment and model based forecasts. I have attached an old, but very good article on this.” The article, “Data Based Models and Managerial Intuition” is available here.

Much more recently, a ChatGPT query on the same subject concluded: “In many cases, an integrated approach that leverages the strengths of both human judgment and forecasting models can provide more robust and reliable results.”

OIS eliminates the current best practice which requires somehow having to integrate a judgment  forecast and a model forecast. OIS  solves that problem because it is a single model within which both are integrated, allowing OIS create a new best possible best practice.

Finally, as noted elsewhere, OIS’s solution is necessarily superior to current best practices because:

Best possible (bp) (COGS + G&A) + bp(m) +bp(s) < bp (COGS + SG&A) where m + a = S