Resource Allocation is Purely a Forecasting Problem

Prescription pharmaceutical brands can be extremely expensive to detail, sample and otherwise promote. As a result, companies spend considerable time and effort to have these marketing resources allocated in the way that will generate the most prescriptions. Or do they?

It is very likely that the vast majority of resource allocation plans don't come with a forecast. In other words, those who purport to know how to allocate resources have been able to claim, with surprising persuasiveness, that theirs is the most productive plan without specifying how much that plan, or any other plan, will produce.

It's a very cushy deal for the planners. Since they don’t commit to a forecast, no one can ever verify the value of the plan. Obviously, if a plan is implemented and the results come in nowhere near the forecast, a rational person would know that the plan was probably far from optimal.

Companies do generate forecasts. It’s just that these forecasts are rarely made by the individuals who created the plans on which the forecasts are based.

Measurements of forecast versus actual results are the economic report cards of business. If the actual results differ much from the forecast, one knows that either;

1. The plan on which the forecast was based was poorly implemented, or,
2. The plan on which the forecast was based could not actually achieve the forecast.

The latter is the case way more often than the former.

The pharmaceutical industry has a well documented history of lousy forecasting and a corresponding, but unrecognized, history of lousy resource allocation. For example, PBE has observed that nine out of ten forecasts for newly launched brands differ from the in-market results by at least (+/-) 30%. Companies also consistently expend 40% of their details for in-line brands against situations that good forecasting would have shown had no chance of paying off. Lousy forecasts beget lousy resource allocation decisions and hurt the bottom line.

PBE’s methodologies will, for all practical purposes, produce forecasts for the plans that are actually implemented, within (+/-) 10% of actual results. The break-out looks something like this:

• New Brands: Forecasts for any implemented plan should fall within (+/-) 6% of in-market results.
• In-Line Brands: Forecasts for any implemented plan should fall within (+/-) 4% of in-market results.
• DTC Advertising: Forecasts of the incremental impact of DTC Advertising for any implemented plan should fall within (+/-) 10% of actual results.

Everyone probably understands that the sales achieved over any given period of time do not occur accidentally. They represent the outcome of forces produced by the brand message, marketing tactics, and the market environment.

A mathematician would say that sales are a function of those three elements. So, if the impact of the brand message and the market environment can be accounted for, one can then vary the tactical plan to see how sales would respond to different resource allocation plans. This is the only way to truly optimize the use of promotional resources. It places plans and forecasts in the same equation.

This is in fact the approach some companies are successfully taking. They are starting to get a better handle than their peers on the resource allocation issues that are so important to the bottom line.