Putting the Science in Sales Management

Sales management is the only business function where all the research and innovation has been exclusively the domain of businesses and not academics. Selling may be an art, but sales management is a science. Every other business function has extensive academic research and you can have advanced degrees in marketing, psychology and behavioral economics which are arguably less predictable than sales processes especially large scale enterprise selling. Yet there are less than 1% of universities with bachelor or masters degrees in sales management and only 1 of the top 100 colleges (Purdue). There are few Professors of Sales Management and very few PhDs. In fact, a recent Harvard Business School Review article argued for the need to treat sales management with the same scientific rigor as marketing, HR or other corporate functions studying interpersonal processes.

Any of us working with large enterprise sales teams know the level of sophistication, analytics, regression analysis and even machine learning that goes into anticipating human behavior. Not just predicting buying patterns of customers but also anticipating systemic mistakes of the sales force, like overusing certain tactics (product demonstrations) while avoiding others (business case development, board-level selling, etc). Great sales management understands that certain activities have higher correlation to closing than others and work for some customer segments in certain industries in certain economic cycles. They understand and measure the buying behavior of the given group of executives making a decision which would vary account by account. They analyze the recurring bias of overly optimistic or conservative sales teams and normalize based on past forecast performance.

Science of sales management can account for the sales velocity differences given the buyer’s executive power and the industry they operate in. They have big data sets knowing all their customer’s past purchases, competitive landscape, the client’s business pressures and business performance against their peers. All of these factors can provide predictive set of activities as next steps for the sales force with much higher propensity to close.

A scientific sales management team would not tell their sales force to “make more calls” to grow sales. They would tell them to “call customers A, D, F and Z offer to improve their in-store sales by 11% because historically those customers underperform their peers in that area and that they use an old technology that does not allow for sensor based traffic and e-commerce up-sell of in-store customers”. And they would do it based on the data they are tracking about customers, sales and the market.

We as a profession have all the data, analytics and AI we need to operate at this level and beyond. It is time for academia to catch up.

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