In the hunt for sales growth, profit growth, or share growth from the sales force, every sales leader, whether new or seasoned, or from a growth-stage or a mature-stage company, faces the same question. Where will the growth come from?
The best answers are frequently unearthed by looking at differences in performance, sales activity, and market potential across different pieces of the business — certain customer segments, selected products within a broad portfolio, or specific groups of sales people.
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Better analytics, as well as improved data storage and organisation technologies, are enabling companies to get more creative in the way they analyse data to discover and take advantage of these hidden pockets of growth.
Strategy in action
Here are several examples:
1. Global Healthcare Company, Novartis, gets More Out of its Average Performers
Working first with the US sales force, Novartis identified a group of sales people who were outstanding performers and isolated a set of behaviours that differentiated their performance from that of average performers.
The company developed a new sales process that was derived from the behaviours of the outstanding performers, and it aligned sales hiring, development, and other programmes to support the new process. A key part of the initiative was a selling skills training programme called Performance Frontier — The Next Generation in Sales Excellence.
In a controlled study, newly trained previously ‘average’ sales people realised twice the growth rate in sales when compared to a control group of ‘average’ sales people who were not trained on the newly identified behaviours. Based on this success, Novartis replicated the approach globally.
2. A Manufacturing Company Accelerates Growth among
New Hires
The company tracked performance of sales people over their first 20 months to understand how quickly new sales people became effective and why. A key finding was that the quality of the first-line manager (FLM) had a large impact on new sales person performance.
Sales people reporting to top-performing FLMs performed much better in their first 20 months on the job compared to sales people working with average-performing FLMs.
Top-performing managers did two things that contributed to the performance difference: They spent more time coaching in the field and they arranged for mentorship from experienced team members. Based on these findings, the company established new coaching expectations for FLMs and implemented a tracking system to ensure accountability.
3. A Medical Supply Company Boosts Profits by Reallocating Sales Effort Across Products
The company had several products in its portfolio. The amount of sales time devoted to each product varied by sales person.
By analysing differences in the amount of time that sales people spent by product and the resulting product sales and profits, the company determined a vastly improved way to allocate sales effort across the portfolio.
The company aligned the incentive plan to reflect that effort allocation, and educated the sales force about how to spend sales time in order to optimise performance. The result was a measurable increase in sales and profits without any change in sales force headcount.
4. A Business Services Outsourcing Company Improves Performance in Non-Metro Geographies
The company compared performance of its 50 least urban (i.e. non-metro) sales territories to that of its 50 most urban territories.
Sales per territory averaged $1,2 million in both groups. Yet when compared to urban territories, the non-metro territories had 79% more prospects and 49% more overall market potential. Sales people in urban territories visited good prospects on average four times a year; but in non-metro territories, that average was just 2,8 visits.
Sales people in non-metro territories were not realising opportunities because they were stretched beyond their capacity. The company reduced the size of non-metro territories and assigned coverage of many prospects in outlying areas to an inside sales team.
This led to increased market share, reduced travel costs, and improved sales force effectiveness outside metropolitan areas.
5. A Telecom Company Gets More Business from its Low Performing, High Potential Customers.
The company took advantage of an emerging way to hunt for opportunities by using a collaborative filtering model, similar in concept to algorithms used by companies such as Netflix and Amazon.
The company found ‘data doubles’ for low performing, high-potential customers – i.e. other customers who had a similar demographic profile (for example, the same industry and scale), but who were buying much more.
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The company analysed the purchase patterns and sales strategies at these more successful data double accounts and shared the insights gained with the sales force.
The information enabled sales people to improve targeting of the right products for under-performing customer accounts, thus driving stronger uptake of new product lines and dramatically improving the realisation of cross-selling and up-selling opportunities.
Data Mining
Companies will always be thinking about their next source of growth. Today’s world of big data enables companies to creatively slice and dice historical sales force data to find new and better sources of insight.
