- August 2, 2017
- Posted by: Dave Kurlan
- Category: Understanding the Sales Force
Today I’m bringing you some insightful information that was not widely read when it was published back in 2014. Tony Cole, CEO of Anthony Cole Training and one of OMG’s great partners, forwarded me an article that appeared in the October 2014 issue of the Journal of Marketing Research. The 19 page article, by Kumar, Sander and Leone, was much more intelligent than anything I have ever written or developed. They used vocabulary that I had to look up! It was so intelligent, that after my third attempt to read it, I still can’t figure out what they are saying. I’m not smart enough. Anyway, even if you don’t attempt to read this article, you need to click on the link and skim the pages just to see how unreadable and math-based it is. So who are these authors?
Kumar (VK) is the Chang Jiang Scholar (HUST), Richard and Susan Lenny Distinguished Chair & Professor of Marketing, and Executive Director.
Sarang Sunder is a doctoral student in Marketing, Center for Excellence in Brandand Customer Management, J. Mack Robinson College of Business, Georgia State University.
Robert P. Leone is the J. Vaughn and Evelyne H. Wilson Chair and Professor of Marketing, Neeley School of Business, Texas Christian University.
On the ninth page of the article they begin the section on methodology with this paragraph:
“We estimate a latent class model to account for the unobserved heterogeneity. We also account for the potential endogeneity problem that arises due to the opt-in nature of the training interventions using an instrumental variable approach. Next, we describe the details of the model specification and its estimation.”
That was the only paragraph in the entire article that I came close to understanding. To me, it looks more like a document on physics!
They claimed that nobody had ever looked into a methodology for evaluating sales forces until their foray into this area, so they couldn’t have looked very hard. A google search on sales force evaluation turns up 1.8 million results and OMG and/or Dave Kurlan occupies most of the top 10 spots.
At the risk of offending these three scholarly writers, what do they know about sales and salespeople? Their article studies one large company with around 500 salespeople and they attempt to determine a salesperson’s future value to a company. In their work evaluating the sales force, they don’t measure any of the 21 Sales Core Competencies. As a matter of fact, it appears they aren’t even aware of the Core Competencies of Selling. They paid more attention to CLV (Customer Lifetime Value) than any selling competencies that this sales force might have possessed. If you take a peek, you might conclude the same thing that I did. which, Their model is based more on historical buying patterns of existing customers, retention, and application of those findings to potential new customers. Then they consider the impact of incentives and training. In other words, this isn’t even about the salespeople – it’s about the customers and whether salesperson incentives and training will cause current and future customers to purchase more.
On the other hand, Objective Management Group (OMG) has a proven process for conducting a thorough sales force evaluation that focuses on the people, strategies, systems and processes of the sales force. We can accurately predict how much additional revenue your group can bring in after correcting gaps and flaws. We can identify which salespeople will perform more effectively. We conduct a pipeline analysis, messaging analysis, and measure 21 Sales Core Competencies. One of our analyses suggests the best role for each salesperson (when you have multiple roles). We can definitely answer nearly any question you have about your sales force and back it up with science! Check out a real sales force evaluation!
I thought I knew sales. I’ve been studying what makes salespeople tick for 32 years and continue to learn and share more each day. OMG has evaluated more than 2.3 million salespeople and with around 250 findings, we have 275,000,000 data points!
I thought I was pretty smart but I was wrong. The authors of this article are way smarter than me.