Scientific approaches to sales force sizing and allocation • Optimizing return on sales Return on sales optimization (ROS) utilizes basic optimization techniques to find the size and allocation of the sales force that provides the highest profit for the company. The return on sales optimization approach has been used for decades in industries with large sales forces like healthcare and pharma. The sales force however is a cost centre but also a means for revenue generation, and since ROS optimizes profits, as opposed to sales cost, it is a powerful tool to gain insights into profit and revenue management. The profit optimization is based on estimates of potential sales through an estimation of the sales response curve, data on segment and product profitability, and costs for sales resources. A strength of ROS is that it takes the threshold effect and the decreasing return on sales into account. The threshold effect is a consequence markets and customers requiring a certain amount of sales resources to start generating significant sales. There is no point for a sales rep to spend time to identify a customer’s needs if he does do not have time to finish the deal, and as the word spreads, within the customers’ organizations or between customers in a segment, companies typically spend less sales resources for additional euro of sales. Similarly, as the market potential becomes exhausted it takes an increasing amount of sales resources to secure each additional euro of sales, making it nearly impossible to capture 100 percent share of any market. Not accounting for these effects may lead to incorrect conclusions,
especially for large changes in sales force size or allocation. The weakness of ROS is that it requires estimates of return on sales that sales managers are not used to making explicit. They will feel uncomfortable doing so, at least the first time around, and there will be errors in their estimates. Therefore a ROS exercise should be iterative, to allow for testing and scenarios, and it should be used regularly to enable a feedback and learning process based on actual outcomes. An additional benefit of ROS is that it can generate not only sizing and allocation insights but also sales and call plans.
“A strength of ROS is that it takes the threshold effect and the decreasing return on sales into account”