As consultants, our greatest source of learning is our clients. Aon carries out a lot of work in the space of incentive structure design which forms a key element of a compensation philosophy. The design process requires us to critically evaluate all plan parameters from both an employer as well as an employee perspective.
A good incentive structure must motivate employees to outperform and help drive business results by not restricting their goals to what’s in their ‘goal-sheets’. The plan should promote cooperation and collaboration amongst employees while creating a sense of ownership in their minds. While the plan must encourage new ideas, efficiency, and innovation it must also discourage excessive risk taking and short-term thinking. This article focuses on three elements of an incentive structure that have the biggest impact on behavior – quantum, target setting and payout curves.
Show Me the Money
For an employee, the motivation to achieve variable compensation can be driven only if its perceived value is substantial thereby making it dependent on the quantum. An employee’s additional efforts in achieving above targets must be rewarded enough to significantly impact his/her ‘take home’ salary. A higher weightage on variable compensation also helps organizations manage costs over time since payouts are linked to performance. One must be cautious that the quantum of variable compensation should not be such that leads to excessive risk taking or unethical behavior.
Targeting the Target
One of the most commonly asked questions while designing incentive plans is “What is a reasonable target?” The definition of “reasonableness” is subjective and ultimately boils down to how easy or difficult is it to achieve them? Target setting is important, not just at an individual level, but also at an organization level. Other similar questions that are frequently asked include:
- How does one assess how easy or difficult the target is to achieve if no industry benchmarks are available?
- What if we are a conglomerate and the industry dynamics across our firms are different but we want to use the same incentive plan, at least from a philosophy standpoint?
- Does the degree of stretch in targets change with the lifecycle stage of my company?
- How do we account for exogenous factors (like demonetization and GST) that have made initial targets irrelevant to an extent?
- How do we ensure fairness in the target setting process across all our business units when they are growing at different rates?
- What if, we have two business heads – one who sets ambitious targets and slightly under-delivers and the other who sets easy targets & over-delivers? Which behavior should we encourage?
Given the internal, domestic and global uncertainties, setting targets with precision is becoming a challenging task, especially long-term targets and this trend is common in most industries. Setting targets is essentially forecasting and we have been taught enough times that history does not repeat itself.
Let’s do a quick mental exercise.
Step 1 – Think about what your monthly expenses will be over the next 12 months.
Step 2 – Assume an expected increase in income and compute your expected annual savings.
Step 3 – Now answer a simple question – Do you think your actual savings will be very different compared to your forecast?
If your answer is “Yes” (or, “More Yes than No”), then imagine having to carry out this exercise pan organization. Statistical techniques like time series analysis of past targets and actual performance are utilized for designing incentive plans however, such analysis assume that history would repeat itself. Additionally, given the weak disclosure norms in India with respect to variable compensation, almost no company discloses its financial targets making it difficult to carry out a robust intra industry comparison. This is exactly why having a trustworthy leadership team and an independent governing committee is critical to any organization.
At an individual level, if you set the targets too high too soon, you may set the individual up for failure. It’s like asking a budding cricketer to play international test cricket before domestic first-class cricket. Similarly, setting targets that do not challenge the individual will also hamper long-term growth and development. At a firm level, the same principles apply as far as setting a “Target” level of performance is concerned. Most companies also define maximum and threshold levels of performance in their incentive plans. There are a couple of ways to do this if industry benchmarks are unavailable:
- Mathematical Modeling Approach: Modeling the performance against target performance in past years on a normal distribution curve and setting maximum at the far right of the tail and threshold to the left of median
- Probability Approach: Maximum performance levels can be set at a 25%-30% probability of achievement (Threshold at 90%-95% and Target at 75%-80%). Assessing the probability of achievement is usually a judgment call and depends on the experience of the judge. So, choose your judge(s) wisely!
If the industry that the organization is operating in is expected to undergo a period of high volatility; it is generally recommended that the range between threshold and maximum level of performance should be wide as well. This will help account for fluctuations in performance caused by exogenous factors.
How to Pay-for-Performance?
- Differentiate: Organizations must sufficiently differentiate incentive payout between the top and average performance levels. This will ensure that top performers remain motivated to stay at the top of the curve and it is aspirational for the average performer as well. If the quantum of incentive itself isn’t attractive, then differentiation alone may not suffice.
- Use Market Benchmarks Only for Reference Purposes: Quite often, organizations are hesitant in doing what the market is not. While the wheel need not be reinvented, sometimes one size does not fit all. Organizations should focus on both what as well as why the market is doing what it is. Don’t reward exponentially for exceeding targets if your targets are relatively easy to achieve (i.e., there is a high probability of success). Similarly, don’t penalize underperformance too much if your targets have a significant stretch in them (or a high probability of failure)
- Higher the Volatility in Expected Performance, the Wider and Flatter Your Payout Curve Should Be: Volatile business environments call for incentive plans that have lower thresholds with reduced payouts. This is because, in such an environment, actual performance has more to do with a turning business cycle than employee effort. This approach provides a cushion to employees in terms of performance expectations and doesn’t reward disproportionately for the same effort in a good year
- If Target Setting is Impossible, Reward Incremental Actual Performance: In this approach, instead of rewarding actual performance vis-à-vis targets, we reward incremental actual performance compared to a reference point in time. This approach works particularly well when you observe a tendency of employees to consistently under-promise and over deliver. An example of this approach is the profit share plan which does not impose limits on an employee’s performance. They are free to aim (and achieve) as high as possible as their rewards are completely in sync with their performance. Messaging becomes critical as we are not making employees reach for a hypothetical, unscientific and inaccurate target. We are driving long-term profitable growth & not just designing a plan that incentivizes meeting targets
- At Times, Discretion is Not Just Required, it is Recommended: A formulaic approach has become indispensable to ensure a fair and transparent approach to incentive design as it helps maintain more discipline and works particularly well in a relatively stable business environment. However, the organization must have ability to set reliable targets. If your performance or target setting process itself is in question, then simply fixing payouts will not help. Judgment and discretion should be applied to ensure that the results from a formulaic payout approach make intuitive sense. Not just to the employees but to all the stakeholders. Caution is recommended while using discretion as well. It has its side effects. Firstly, it can be misused. Secondly, it is hard to fairly administer across different teams as it may have the error of bias. Finally, it is a habit that is hard to change. We must strive towards keeping both target setting and performance evaluation as independent and robust as possible in our organizations. No incentive plan can guarantee business results. All it can do is motivate the right people and the right behaviors. If we do that, the results will follow.
Consultant: Executive Compensation,
For more information, please write to us at email@example.com
Follow us on LinkedIn at Aon India & Twitter @Aon_India