Incentive plan goal setting is one of the most challenging aspects of managing an effective executive compensation program in any industry. Commodity price volatility creates additional goal-setting challenges for companies in the oil & gas industry. Historically, one of the ways the industry has attempted to mitigate the impact of commodity prices was through metric selection, specifically:
- Choosing metrics that exclude commodity prices: volume metrics, cost efficiency
- Measuring results relative to peers: relative TSR primarily
Investors have criticized these approaches primarily for insulating management teams from commodity price movement and skewing management’s incentives. Oil & gas companies have reacted to this feedback by shifting more weight to commodity-influenced metrics such as free cash flow (FCF), earnings, and return on capital.
This shift in metrics will certainly lead to greater variability in incentive results; the large swings in commodity prices are now more likely to influence incentive outcomes, just as investors intended. At the same time, the pandemic and other macro factors (e.g., reduced influence of OPEC, inflation) have increased volatility and uncertainty in the market.
A good incentive program is one where there is a high probability of performance being “on the scale.” Said another way, there should be a low probability of a maximum or zero payout in any one year; management team performance should dictate where on the scale the company falls. Extreme volatility in incentive payouts due to factors outside of management control can make the program seem more like a lottery ticket and less like an incentive program.
So how might oil & gas companies go about setting goals in this environment? Potential solutions include the following:
Create wider performance ranges for commodity-influenced metrics than non-commodity influenced metrics
As incentive programs become more weighted to commodity-influenced metrics, it is important that these metrics have ranges that are wide enough to account for commodity price volatility. If +/- 5% around target was the range for production, then a cash flow metric should have a wider range. Companies can test appropriate ranges by reviewing historical results to gauge metric volatility. Metric results should fall between Threshold and Maximum a strong majority of the time (70-80%). If historical metric results would have fallen outside the Threshold to Maximum range 50% or more of the time, the range is likely too narrow.
Use wider ranges in highly uncertain environments
The last two years have been extraordinary in terms of volatility and uncertainty. 2022 may be less volatile, but we are still hearing a lot of uncertainty around the strength and breadth of the recovery, inflation, energy legislation, etc. The level of uncertainty should also influence the range spread. Greater uncertainty = wider ranges, for more than just commodity-price influenced metrics.
Price adjust for significant price changes
We have seen examples of companies that have made some commodity price adjustment to metrics such as earnings or free cash flow without completely neutralizing for the commodity price. A few alternatives might include:
■ Price brackets: Create brackets within which there are a different set of goals for different ranges of commodity prices (example below). In this approach, commodity price impact is limited but not completely neutralized. One advantage of this approach is that it allows for adjustments even if there isn’t a direct relationship between price and the performance metric, so it could be used for companies like oilfield services where revenues are not directly tied to price levels. One of the challenges of this approach is that the adjustments aren’t linear, so measurement at the range cutoffs can be volatile.
▪ Price barriers: Establish commodity price barriers—this approach sets a range within which commodity price influences results, but sets a ceiling (ex: $100/barrel) and a floor (ex: $60). Beyond the ceiling and floor, results are calculated based on a price-adjusted basis. So if oil goes above $100/barrel, operating cash flow is calculated assuming a $100/barrel max. This approach only works for companies that can directly calculate the impact of prices on their results (e.g., E&P companies).
These approaches (and other similar approaches) can help mitigate the extreme swings in commodity prices and may provide a more accurate reflection of management’s contribution to financial performance. However, these approaches also add complexity to the program and by limiting the impact of commodity price on incentive payouts, they can still result in the skewed incentives and misaligned outcomes investors have been criticizing.
When considering potential price adjustment approaches, consider how the metric fits within the broader annual incentive plan. For example, if commodity-influenced metrics comprise a minority of the annual incentive plan (as with most upstream companies), it is likely more appropriate not to price adjust since most of the plan is already insulated from the impact of commodity prices. Conversely, if the majority of the plan is weighted towards price-impacted metrics, perhaps some price adjustment is appropriate.
Regardless of the approach chosen, we view discretion and judgment as important aspects of a sound annual incentive plan in the oil & gas industry. The industry is too volatile to put incentive programs on autopilot – 2020 was a perfect illustration of that.
Additionally, as a matter of good governance, compensation committees should regularly conduct an ongoing retrospective evaluation of the goal-setting process. This involves reviewing results from completed performance periods to identify key learnings for future goal-setting. It’s impossible to get it right every time, but continuous improvement is a worthy goal.
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