Goal setting for incentive plans is generally a difficult proposition. The ability to set meaningful goals is further challenged in today’s highly uncertain macro-economic, political, and regulatory environment where business plans are subject to a host of unforeseeable or unpredictable external factors.
This can be further complicated in highly cyclical industries or in industries with significant exposure to highly variable raw material costs or output prices (e.g., those subject to significant fluctuations in commodity prices). In many situations, it would be desirable to have the flexibility to adjust plan targets automatically on an “after-the-fact” basis if the actual operating environment deviated significantly from the company’s original budgeting and planning assumptions. This article lays out an approach for automatically adjusting plan targets in a prescribed manner and illustrates the approach with a case study based on one of our clients.
The Preferred Outcome
Ideally, a company would be able to adjust plan targets on an “after-the-fact” basis through an approach that met the following objectives:
- Provided sufficient structure to the adjustment process to safeguard the compensation committee and management from the potential criticism of a broad range of stakeholders and provided sufficient transparency to employees — issues which are typically associated with employing “blanket” discretion.
- Resulted in both upward and downward adjustments to plan results (depending on whether the external factors worked to the company’s advantage or disadvantage)
- Did not encourage management to seek forgiveness for everything that had a negative impact on results and recognized that management should be expected to respond, on a timely basis, to changes in the operating environment.
Some companies achieve this end through the use of relative performance measurement. But, as we know, identifying a meaningful peer group with sufficiently comparable companies can be a challenge in and of itself.
As an alternative, we propose a market-based framework (detailed below) for making “after-the-fact” incentive plan adjustments to better reflect a company’s ability to respond to challenges and opportunities in the operating environment that arise over the course of the performance measurement period.
The Market-Based Framework for Incentive Plan Adjustments In its simplest form, the market-based framework for adjustments works as follows:
- Step 1: Management and the Board agree upon a budget and/or long-range plan for the company based on assumptions about industry-wide growth.
- Step 2: The company establishes a framework for adjustment based on the degree to which any planning assumptions about the operating environment are or are not borne out.
- Step 3: At the conclusion of the performance measurement period, the company reviews independent, third-party data to understand the degree to which the actual operating environment differed from the original planning assumptions.
- Step 4: Incentive plan targets and resulting payouts are adjusted accordingly.
Three principles underlie this framework for making “after-the-fact” incentive plan adjustments. First, there must be an explicit understanding of the key planning assumptions made by management in developing the long-range plan. Further, there must be sufficient scenario testing to understand the sensitivity of company results to those underlying assumptions.
Second, the framework used must result in a defined set of adjustments. To the extent that the operating environment differs materially from the key planning assumptions, incentive plan targets and results will be adjusted in a formulaic manner. The formulaic framework must be developed with consideration for and understanding of the sensitivity of results to the key assumptions as described in the first step. Critical to this step is the availability of high-quality and timely third-party data that provides a basis for evaluating the actual operating environment relative to the assumed operating environment.
Finally, there must be an explicit acknowledgement as to when (if at all) the compensation committee will make discretionary adjustments (e.g., such as in the event of an unplanned acquisition/divestiture, changes in accounting rules, and other non-recurring events). This approach should generally avoid the need to make discretionary adjustments that fall outside the prescribed parameters. That said, the compensation committee should lay forth explicit guidelines as to when it will (or will not) consider discretionary adjustments that aren’t already addressed through the market-based framework.
We demonstrate how the market-based framework for incentive plan adjustments would work in practice through a case study of one of our clients.
Case Study: Semiconductor Company
Our study company designs and manufactures tailored semiconductor products and solutions for high valueadd applications. The cyclical and unpredictable nature of the semiconductor industry creates challenges with fixed, budget-based annual goals for revenue growth and/or profitability. When markets are unexpectedly robust, achieving the original goals may not warrant as large of a payout; when markets are unexpectedly weak, achieving the original goals may warrant a larger payout.
The approach can be used to improve goal-setting processes in highly cyclical or uncertain markets without the need for significant “after-the-fact” discretion that tends to decrease line of sight for participants. Key advantages include that such an approach allows companies to:
- Link budget-driven targets to the relevant market context and to inform actual performance results with actual market conditions — relieves some pressure to “get it right” with up-front goal setting
- Eliminate the need for “blanket” discretion by incorporating a market-based framework for plan adjustments
- Avoid the need to establish a specific performance peer group by using industry-level data
The primary disadvantage is that this approach requires the availability of high-quality and timely market/industry data to help quantify the degree to which the company’s performance lagged or outpaced comparators.
View the full article as it was originally published.