Bringing Science to Sales
Facing fierce competition and heavy pressure to deliver continually improving results, many sales organizations today are in a bind.
Executives' aggressive growth plans demand significant productivity improvements from the sales force. Those plans seldom come with additional sales investments, and the sales organization is often unable to produce accurate sales forecasts of the market's real potential.
The solution is to combine the art of selling with science, using a company's existing investments in CRM technology to mine hidden insights leading to more sales opportunities and better ways to capture them. We have seen that adopting a science-to-sales process can typically yield improvements in revenue of between 5 percent and 15 percent with little incremental investment.
Many obstacles stand in the way. Despite the widespread use of CRM systems, many companies lack sufficient information to accurately gauge how well they've penetrated a given account or segment -- or even to identify the best potential targets. Many sales organizations also have difficulty determining the factors that truly affect performance. Finally, the traditional foundation metric for a sales organization -- how well actual performance compares to set quotas or targets -- is flawed.
This is where the art of sales proves to be quite constraining. The application of science to sales is the answer, and it can be applied through a three-step approach:
1. Analyze performance to identify potential opportunities. Measuring the relative performance of each account or sales rep against metrics such as renewal rates, new-product penetration, or share of wallet will in short order show the extent of variability. Variance indicates opportunity for improvement.2. Segment underlying factors to identify what you can -- and can't -- control. Many factors can determine relative success, but some -- a sluggish economy, a downturn in a target account's industry, or even stepped-up activity by competitors -- are effectively outside the sales team's control. The sales organization, however, can take action to improve other factors, such as account coverage, product mix, discounting, and average deal size. By segmenting these controllable factors, the organization can adjust for them while performing a statistical correlation analysis to determine the extent of the variance they've caused.
3. Launch initiatives to capture opportunity. Each initiative by the organization should focus on addressing specific controllable factors in specific accounts or with individual sales reps. In most cases, the detailed analysis will have identified several areas for potential change, typically spanning three broad categories:
a) Dynamically adjusting account coverage: Revise territories, assignments, etc., to ensure the most effective mining of each account and rep's potential.b) Improving pipeline visibility: Actively manage the pipeline for completeness and frequency-of-refresh; make resource-allocation decisions accordingly.
c) Optimizing transactional pricing: Systematically reduce sales reps' level of discounting.
This rigorous process is already paying dividends at many organizations. One commercial hand-tool manufacturer that took this approach identified territory assignment as a primary factor that could aid growth. The company began prioritizing open territories deemed to have the highest potential for penetration, based on historic performance across seven factors. Those factors included district manager presence, density of territory, and the time the territory had been open. As a result, the manufacturer estimates an improvement in revenue of around 10 percent.
Our experience shows that bringing science to B2B sales requires only incremental technology investments. The needed insights can be gleaned from existing transactional sales data, once assembled, and those insights can drive key actions. Adopting a discipline to look beyond averages, and taking a few specific actions to close variance gaps, can help almost any sales organization substantially improve its results.
Anupam Agarwal is an associate principal in the Silicon Valley office of McKinsey & Co. He can be reached at anupam_agarwal@mckinsey.com.
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