History of the problem: OIS solves a problem first articulated by department store mogul, John Wanamaker, in the 1880s.  Paraphrasing: “I know half my advertising is wasted, I just don’t know which half.”

Confirming Wanamaker problem, Professor Kotler et al in the 15^th edition, 2020, of their iconic marketing text, Marketing Management, page 551 described the problem as: “One of the most difficult decisions is choosing how much to spend on the marketing communications budget (MCB).”

Professor Kotler et al. spent 55 years and 16 editions of their text trying to solve the problem. Initially, a prescriptive approach was proposed; subsequently, a predictive approach was adopted.  For a summary of the predictive approach, see the summary from the 16^th edition.

Solution to the MCB problem: The solution is OIS, a model of the firm’s income statement. It is however, a very significant departure from the traditional income statement and creates very significant new advantages for the firm including the most profitable forecast possible.

Summary of OIS’s solution:

1. Modeling Technique: OIS’s modeling technique is a prescriptive technique. It answers the question of what is the best possible solution.
2. The specific modeling technique OIS uses is a mix of integer and linear math programming (MILP).
   1. The first step in creating OIS is to create a MILP model of the firm’s income statement. This model has a fixed forecast.
   2. the next step is to relax that model’s assumption of a fixed forecast using data from a marketing mix model.
   3. When optimized, a new income statement is created including a new forecast that includes the most profit possible.

See ChatGPT query result confirming the above,