How to Radically Improve the Sales Incentives Plan By Gene Yap, Consultant, Total Rewards, Aon Hewitt With contribution by Tim Glowa Are Sales Leaders Short of Ideas for their Sales Incentives Plan? Is there any sales leader who hasn t fiddled with their sales incentives plans only to achieve very little? Many sales veterans will admit that sales incentives are not always the right tool for the job (with a few exceptions) and it should not be regarded as a proxy for disciplines like role design, talent management, learning & development and communication. 1 Regardless of its shortcomings, though, the sales compensation plan continues to be the subject of frequent reviews. Oftentimes, this review exercise stems from an instinctive reaction to particular sales challenges or opportunities. Ironically, so many arbitrary adjustments have been made to sales incentives plan features that sales executives are beginning to run out of ideas on how to enhance their plan anymore. In fact, many of the sales improvement suggestions tossed around these days seem to be reduced to one-liner proposals conveniently designed to deliver that knock-out punch to sales issues. My top performers are complaining about the cap in their bonus payout. Okay, looks like the only way to incentivize them is to raise the cap. Do we have market data on that? Our sales reps have been falling behind on their quotas. Well then, it s time that we increase their target bonuses. Do we have market data for that? We need to enhance consistency in sales production throughout the year. All right, let s introduce yield-to-date measurements. (You can imagine what comes after.) It s not uncommon to find even the most seasoned sales leader falling into the trap of thinking that silver bullets exist for sales incentives issues. Instead of providing our clients with one-liner quick fixes and market benchmark data, we introduce them to a simple, yet comprehensive, Aon Hewitt framework that yields multiple points of view and facilitates holistic solutions to an organization s sales incentives issues (Figure 1). 1 Gene Yap and Jairus Ashworth, HR Connect Asia Pacific, Beyond Sales Incentives Plan: Tackling Key People Issues, May 2013 Aon Hewitt Singapore Pte. Ltd. Co. Reg. No.: 198901141D 1
Start by Looking Beyond Just Market Benchmarking Designing the sales incentives plan strictly from a benchmarking perspective is like taking a swing at a piñata one can t be sure if it s enough to get it right at the first impact. Relying on uni-dimensional input to improve a sales incentives plan will most likely result in much trial and error down the road. But factoring multiple inputs (as shown in Figure 1) into the sales incentives design is not new, nor is it rocket science. As we have discovered in past client engagements, the real challenge for business leaders lies in juggling the competing points of view held within the organization. For instance, a country CEO at one of the world s leading life sciences conglomerates in China learned how the process of seeking consensus across functions almost put off the decision on a minor but symbolic tweak to the sales incentives plan. The Shanghai-based sales organization had used a stair-step payout curve 2 to incentivize their sales reps and was considering a change to a straight line curve. Uniform bonus payouts at different tiers of performance or steps had seemingly stunted sales performance. To coax a better sales performance, we recommended a straight-line payout curve. A simplified illustration is shown below in Figure 2. 2 A stair-step payout curve is characterized by the achievement of the next higher tier performance level before a higher rate of incentives is paid out. A straight-line curve pays on increments of sales performance and does not have limitations imposed on the payouts. Aon Hewitt Singapore Pte. Ltd. Co. Reg. No.: 198901141D 2
The sales executives were ecstatic when we forecasted a 1.5--2% increase in sales production as a result of a change in the payout curve. On the other hand, Finance viewed the sales incentives plan as an expense to control. They were not that enthusiastic when they learned that incentives costs would inch up by another 5%. Though the CEO eventually signed off on the recommendation after factoring in market data on sales-cost ratios, it was not without intense bickering between the Sales and Finance organizations (Figure 3). 3 So, the lesson is this. Most companies typically overemphasize the external input. Market benchmarking often plays a powerful role in sales comp plan decision-making. However, counting on market data as a quick fix for a sales compensation plan is not sufficient. The ideal incentives structure is one that aligns all four inputs, not just market data. It makes financial sense to the organization, harmonizes with leadership and talent strategies, and most importantly, meets employees needs, thus motivating better performance. Although we observe that more companies are systematically adopting such a multidimensional approach in their plan design (albeit a daunting managerial undertaking), the majority still overlook that oh-so critical fourth element the sales representatives input. 3 Thomas Steenburgh and Michael Ahearne, Harvard Business Review, Motivating Sales People: What Really Works, July- August 2009. Aon Hewitt Singapore Pte. Ltd. Co. Reg. No.: 198901141D 3
Complete the Circle by Unlocking the Fourth Element You ve probably heard of the phrase, Our employees are our greatest asset. Clichéd as it may sound, high levels of employee engagement tend to result in lower turnover rates, more productive talent pools, and overall better financial performance. In fact, Aon Hewitt s Best Employers research suggests that organizations with high levels of employee engagement tend to achieve strong company earnings, attain higher growth in profits, and post total shareholder returns higher than average. 4 This leads to the million-dollar question: how do we design an incentives package that will effectively drive sales representatives to be highly engaged and economically productive? To secure employees opinions on the requisites for an ideal sales incentives plan, there are several methods, as shown in Figure 4. Figure 4: Different Methods of Seeking Employee Opinions Survey Research - Questionnaire Qualitative Research Interview and Focus Group Experimental Research Conjoint Analysis If you want to gather opinions on How satisfied are my sales employees with their compensation plan? What areas of the sales compensation plan require improvement? What are some suggestions to improve the current sales compensation plan? What are employees reactions to different strategic scenarios? What are the innate preferences and drivers? How are these proven? How different are the perceived values to different sets of sales plans? How are employees making trade-offs? Which plan would optimally appeal to sales employees and management objectives? Use the following methods Multiple-choice questions Four-point rating scale Executive interviews to gather verbal feedback Focus group sessions with sales representatives Conjoint analysis Optimization analysis 4 Aon Hewitt, Best Employers 2.0 Asia 2013 Study Aon Hewitt Singapore Pte. Ltd. Co. Reg. No.: 198901141D 4
Each method has its advantages and disadvantages. But in evaluating these options, the conjoint approach is the ideal tool to measure a wide range of employee preferences for sales compensation. Consider this, if asked directly about which attributes of their plan are important, sales employees would likely claim that almost everything--high base salary, high bonus, aggressive payout schedule, and frequent payouts--is important. In this sense, employees are no different than their customers who also want the best of everything that is available. Simpler approaches, such as employee satisfaction surveys, often are rather blunt tools to determine employee preferences because the responses obtained often lack any differentiation among attributes. Most respondents would evaluate all favorable attributes of the sales compensation plan with high ratings, with the lower half of the scale largely ignored. The conjoint method, on the other hand, is eminently suitable in revealing employees true preferences because it mimics a real-world environment where difficult trade-offs and concessions are made. These subtle predilections are usually collected through forced-choice questions that require expressed preferences for one feature over another (Figure 5). Aon Hewitt Singapore Pte. Ltd. Co. Reg. No.: 198901141D 5
The concept of conjoint analysis is actually not new. 5 For about forty years, this Nobel Prize winning research method has been used extensively in market research to infer how people psychometrically value different features that make up a product or service. The statistical method has been widely used by market researchers to assess the value consumers assign to product attributes so they can continuously design better products and pricing strategies. In the context of sales incentives design, the conjoint approach is used to measure the relative preferences for different attributes of the sales incentives plan, such as quota setting, base salary, target incentives, pay mix, pay frequency, performance measures, and so on. It also tells us about the responder s sensitivity and receptivity toward change, which can be used to estimate the appeal of new sales incentives features. Each sales representative has their own personal preferences among sales compensation plan features. Conjoint analysis decodes this private information and quantifies how any given feature drives a sales representative s engagement and propensity to perform (Figure 6). 5 Green, Paul E., Yoram Wind and Arun K. Jain (1972), Preference Measurement of Item Collections, Journal of Marketing Research, 9 (November). Aon Hewitt Singapore Pte. Ltd. Co. Reg. No.: 198901141D 6
However, this is not the end of it. For conjoint analysis to come full circle, employee preferences need to be taken into account in a way that optimizes value for both the employee and the organization. For example, if we were to ask consumers what they want in a new car, they will say safety, performance, reliability, comfort, style, superior audio and a low price. To meet all of their stated preferences, we might end up designing an Audi and selling it for $1,000! Amid a multitude of individual preference drivers, management has to fashion incentives plans that will hit a sweet spot maximizing the firm s profit-taking potential, while responding to the collective preferences of their heterogeneous sales force. This optimal relationship between business objectives (external, leadership and cost inputs) and effective rewards (sales representatives input) can be achieved through the simultaneous application of optimization techniques and conjoint analysis. In work for a China-based consumer company seeking to optimize the effectiveness of its current compensation and benefits (C&B) plans, we helped the company plot a preference and cost frontier consisting of hypothesized portfolios featuring different reward elements (Figure 7). To start, we gathered external input from market best practices and worked with the leadership team to craft a questionnaire that would efficiently quantify employee attitudes, needs, and opinions related to the company s programs. Upon administration and analysis of the employee survey data, conjoint insights about employee preferences were optimized with the company s cost constraints. As seen in Figure 7, a range of alternative reward packages (shown as orange dots) are plotted along a frontier which is considered optimal from two perspectives one is cost, and two is employee preferences. The end result for the plans that are to the upper left of the grey dot (the current plan) saves the company money AND leads to higher employees engagement. This preference-cost optimization model served as the primary input for guiding the company s C&B strategy and cost-effective changes. Aon Hewitt Singapore Pte. Ltd. Co. Reg. No.: 198901141D 7
Connecting the Dots When it comes to sales incentives, companies ought to stop focusing so much on market benchmarking studies. To radically improve their sales incentives plan, management should consider the following: Market benchmark data is important, but recognize that it s a means to an end. While it is important to consider hard market intelligence such as salary levels and prevalent incentives practices, an unhealthy devotion to market best practices could oversimplify a more complex situation. There are other critical factors to consider when determining the most appropriate sales incentives plan for a company s business situation. Force-fitting market data into the heart of decision-making could turn useful intelligence into a liability for the company. Involve the Finance organization (and other relevant stakeholders) early in the design process. Many sales veterans assume that it s easy to tweak the effectiveness of the sales comp plan. As a result, it s not unusual for Finance to be sidelined and involved only later during the sign-off stage, when it comes down to how much additional funds are required to finance the plan. From our observations, incorporating cost-conscious perspectives from Finance early on in the design phase can bring out valuable points of view, such as the plan s impact on the firm s account receivables, contribution margins and pricing strategy. Achieve a balance between the company s and sales representatives interests. For too long, the fourth element (sales representatives Input) has either been ignored or relegated to a nice-to-have, optional piece of the design puzzle. With conjoint analysis, however, a company is able to capitalize on the knowledge of its employees preferences and the trade-offs of different plans. It not only puts the sales leader in a favorable position to realize higher returns of investment from his/her sales spend, but also unleashes the power to re-energize your sales force. Contact Gene Yap is a Consultant with Aon Hewitt s Total Rewards Practice. He can be reached at gene.yap1@aonhewitt.com. Aon Hewitt Singapore Pte. Ltd. Co. Reg. No.: 198901141D 8