Using Data to Uncover Operational Inefficiency

On October 8, 2015, Glenn Peterson, President of Primo Flight Parts, Inc. (PFP), faced an important deadline: In one week, he needed to finalize his 2016 proposed budget so that supporting materials could be assembled and sent to the Board of Directors in advance of its October 23 meeting, when (he hoped) the budget would be approved. Peterson had been through this process many times since becoming president of the company in 2008. About a month before, Peterson had received a puzzling 2016 Request for Personnel from VP of Sales Henry Gallagher. Peterson felt that Gallagher had always run a tight ship and was a strong contributor. Certainly, in the past five years, Gallagher’s department had hit its sales targets. With a projected 30% increase in sales for 2019, it was not surprising that Gallagher would ask for additional staff. However, Peterson was shocked to see a request for a 40% staff increase. “Why do we need 40% more people to generate 30% more sales?” Peterson asked himself at the time. To help him sort out this quandary, Peterson had called a consulting firm that had recently done helpful work in another part of the company. That firm, The Dorsey Group (TDG), was able to swiftly form a team to analyze PFP’s Sales department and had just reported on the findings from its three-week engagement. With that discussion fresh in his mind, he had to decide from among several options for the 2019 Sales staff: Approve Gallagher’s staffing request; follow TDG’s recommendation that no new personnel be hired; or approve a number between Gallagher’s request and TDG’s recommendation. Thanks to TDG’s work, Peterson now had the information he needed to make an evidence-based decision; but what was the right thing to do?