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Case Study: Pharmaceutical Sales


Pharmaceutical Sales: Resource Optimization

An interview with Dawn Eash

BRG consultants quantified the productivity of a pharmaceutical company’s sales force, which served to inform our client’s optimal allocation of this resource.

What was the main challenge or opportunity?

The client was a pharmaceutical company with a sales force that worked in an autonomous capacity. They were generally unsupervised and worked an unclear number of hours. The firm’s sales leadership wanted to optimize their utilization, payment, and reward systems in order to maximize output and performance while ensuring that they had the best talent working for them.

The client commissioned us to collect primary data on their sales force instead of relying on outdated, generalized, secondary data, and to provide analysis of the sales force’s performance.

What was your analysis of the situation?

In terms of logistics, we sent a qualified team of analysts into the field to collect data with a customized software/hardware solution to capture in real time what tasks their sales force performed. We designed a sample of their sales force stratified by key variables. First, we stratified by their different lines of business because human resources interviews had revealed that sales associates may have drastically different routes, techniques, and limitations based on the business line. Second, we stratified by geography because sales associates in certain geographies had additional driving time that could be considered a different type of work. We wanted to be able to capture the differences between employees who spend more time driving to see clients versus employees who spend more time actually interfacing with clients, and how those differences translate into hours worked.

We stratified by both of those variables and ended up sampling 150 sales associates. We extrapolated those numbers out to the entire sales force community. By doing so, we had a clear picture of the types of activities the different sales associates performed. These activities were then broken down into eight niche categories for further analysis.

The project culminated in a final report that our client used to inform higher-level management of what changes were needed in terms of compensation structure, reward structure, training modules, and the type of employees they should optimally invest in. Their recommendations were supported and formed based on the current, individualized, primary data and analysis from our study.

How did your client use your work in optimizing its costs?

Overlaying the gathered data with sales performance allowed us to quantify the effectiveness of different sales strategies on the firm’s overall performance. We investigated what types of activities the sales associates performed and for what duration. Further, we investigated what the effect of that activity was on the company’s economic performance. The company could see where there were efficiencies and which strategies were less effective. This information allowed them to formulate a mutually beneficial reward structure that could easily translate into return on their investment. On the cost-efficiency side, they could better plan the industrial organization that would optimize their cost of labor.