Sales Compensation Best Practices: Executive Analytics
|Compensation - CompensationDesign|
|Written by Robert Conlin|
Peter Drucker famously said “you can only manage what you can measure.” While widely popular, this quote provides executives and managers with only part of the equation on best practice sales management methodology.
The missing part: time.
Given enough time, almost any business metric can be measured – but sales managers rarely have time on their side. Active management requires real-time, or near real-time, measurement of key sales performance indicators. For most sales managers however, those indicators are available only after the close of the month or quarter, when sales compensation is calculated and performance reports are available - - and when it is too late to make adjustments. For most sales managers, real-time measurement and analysis is simply a dream.
Sales compensation is the sales executive’s best strategic tool to drive sales performance and motivate specific selling behaviors. When designing sales compensation plans (see “Designing New Plans”), one of the most important steps is to identify the appropriate measures on which your sales representatives will be paid. At the plan level, these measures align the sales team with corporate sales goals. At the corporate level, these measures become the key indicators for the health of the business. The sales transactions and commission calculation results related to these measures reveal a great deal about how well an organization is operating.
This is where the element of time comes in. Analysis of individual and corporate level measure results is only useful to the extent that it provides executives and managers with actionable information delivered in time to make a difference. Best practice for executive analytics is to provide performance analytics in near real-time. In addition, performance analytics should be shared with the entire sales management team, providing each level of management with secure views into the performance of their individual teams.
Following are the four key types of analysis that prove to be most useful for sales (and finance) executives and sales managers:
1) Forecast Analysis: Executives and managers should model various forecast assumptions then analyze the results to evaluate impacts to revenue and commission costs. Forecast assumptions may involve best-guess scenarios or leverage trend analysis (see below). In addition, forecast results may be analyzed based on maintaining existing compensation plans or they can be based on new plan models. Forecast analysis provides executives and managers with a view into revenue attainment and commission costs under a variety of scenarios. Best practice for Forecast Analysis is to perform this exercise annually before rolling out new compensation plans, then again mid-year to determine if adjustments are needed to keep commission costs in line with revenue projections.
2) Attainment Analysis: When assigning measure quotas, most organizations plan for a standard distribution or bell curve attainment model. In this model, the majority of sales representatives plot towards the middle of the curve, with an equal distribution above and below midline. But what if a company’s results reflect something different? Are too many sales representatives plotting significantly above or below the mid-line? Were quotas set too high or low? If too many sales representatives are exceeding attainment projections it may indicate that quotas were set to low or that participants are not being challenged. It would also indicate that commission costs are likely to sky rocket as commission accelerators kick in. Conversely, a large cluster below midline may indicate that quotas are too high, and may result in unusually high turn-over. At minimum, monthly attainment analysis is required to ensure that attainment results meet expectations. A recommended best practice is to baseline expected results for the year using the results of your forecast analysis and then monitor the results in near real-time so that adjustments can be made as needed.
3) Trend Analysis: Analysis that leverages comparison data from the previous quarter, the same month in the prior year or budget data will give valuable information about whether or not results are in line with expectations. Trending over multiple periods will establish a level of predictability that can be used for additional analysis, such as attainment and forecast analysis. Best practice for Trend Analysis is to identify and capture data for those key measures that will be relevant over time.
4) Top and Bottom Analysis: Top sales people are usually at the top for a reason – they are good at what they do. But, sometimes they are just good at working the plan! Analytics tools that enable executives and managers to drill into the details behind the earnings of top producers can be valuable in helping an organization uncover good sales practices or bad plan design. The same is true for analysis of those at the bottom. Poor performance may be related to effort, or it could signal resource needs, manager issues, territory constraints, training/mentorship investments or other human resource needs that need to be planned and executed. While it is most likely a direct manager’s responsibility to take action following top and bottom analysis, executives will benefit from knowing this analysis is occurring on a regular basis.
While each organization is different, these 4 methods can be applied to uncover valuable information about the health of a business. Keep in mind that the closer the analysis is to real-time, the more relevant the exercise. Sales compensation data is a rich resource that executives can mine to monitor key performance indicators at the corporate and individual level and then apply strategies to address issues where they surface.
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