Far too many companies have bureaucratic investment procedures that evolve over time into a complex, cumbersome, conflicting, and confusing approval process. Whether it’s for the approval of a capital expenditure, acquisition, research and development program, or marketing investment, there are often too many different analyses, metrics, and go/no-go signals, and they often pull in different directions.
Should an executive approve an investment that displays an internal rate of return (IRR), net present value (NPV), average pretax profit margin, and average net income margin that all surpass approval hurdles?
What if that same investment has payback, discounted payback, and average return on capital over a five-year forecast period that don’t fit within the approval guidelines? What if, on top of this, the company’s business analysis team has prepared a plethora of sensitivity analyses and a Monte Carlo simulation with elaborate probability distribution graphs showing an above 50% probability of a positive NPV?
Corporate finance purists will say “approve all positive NPV investments,” but what if this is the result of a hockey-stick forecast that stagnates for four years and then kicks up aggressively in year five?
How can we make the approval process more effective? To be sure, decision-making can be challenging. The executive, committee, or board that is tasked with making a decision must make a judgment as to whether the expected benefits are likely to exceed the costs. They must form a view about what will happen in the future, which is no easy task. As a result, they turn to their business analysts to “give them the answer.”
If analyses could give answers without managerial judgment why would we need the executive, committee, or board?
The layers of complex analysis, tables, and graphs often confuse, rather than clarify. The goal of the decision-support analysis should be to clarify the factors on which judgment must be rendered. We need fewer and better analyses and metrics driving a clear prioritization of the factors on which to form judgments and make decisions that increase value.
Luckily, the essence of every decision is captured in a measure we call “residual cash earnings,” or RCE. RCE is a cash-flow-based variant of “residual income” or “economic profit.” Gross cash earnings (GCE), which is essentially after-tax EBITDA, less a capital charge for the use of gross operating assets (GOA), results in RCE, which is a period measure that ties directly to net present value (NPV). By balancing growth, margin, and asset utilization, executives drive improvements in RCE, which will drive share price appreciation over time.
If we set aside the menagerie of analyses and metrics, and focus on RCE and its drivers, we more clearly see the essence of a decision. For example, consider a new $5 million investment in equipment and software intended to improve product quality, customer satisfaction, and sales growth. By running a forecast through an RCE analysis, we see the level and pattern of value creation and can focus on the key decision criteria. Is the present value of RCE positive? How long will it take until forecast EBITDA is adequate to overcome the capital charge on an after-tax basis? Which assumptions in the analysis are most important to delivering positive RCE?
On this last question, the decision maker is tasked with forming a view or judgment on whether the project can be done within the budgeted cost, whether the quality will improve as expected, and whether the higher quality will motivate customers to buy enough to achieve positive RCE.
That’s the whole story. It’s not necessarily an easy decision but the factors that must be judged are few and clear. The decision becomes less clear if we now add calculations of IRR, average pretax profit margin, average net income margin, payback, discounted payback, average return on capital, Monte Carlo, etc. No matter how many analyses are completed, the judgment needed is still the same.
Why, then, does the investment decision process become so increasingly complex in so many companies? Among many reasons, its human nature to avoid sticking one’s neck out on a decision that can later be proven wrong. Managers prefer to fall back on a seemingly sophisticated investment decision process that appears intellectually defensible. Somehow they consciously or subconsciously believe that if their decision goes awry they can always fall back on the fact that “it wasn’t my fault, I did all these different analyses that justified my decision.”
However, this complexity often leads to poor decisions for two reasons. The first is that the litany of analyses can result in ‘analysis paralysis,’ where profitable growth and innovation can be stifled. Making no decision due to conflicting signals can seem to be the most prudent course of action. The second is that there is a temptation to selectively choose the one analysis that best supports the manager’s opinion. In such cases, the analysis is not used to come to a decision, but rather to justify an opinion.
Often times, closely held companies are naturally better than public companies at simplifying the decision process. Uncertainty can be daunting when it’s your own money, but because it’s your own money you are less worried about justifying and defending your decision and are more focused on just trying to find the right decision.
For a public company to embrace a private company mindset, it must adopt two managerial transformations. First, it must simplify the company’s focus on one measure (RCE), which captures the drivers of owner success. Second, it must reinforce this simpler and clearer decision process with absolute accountability for delivering results in the form of improvements in RCE.
When managers’ success is linked to changes in RCE, they know that investments that don’t deliver adequate RCE will negatively affect their performance review, and potentially pay. As a result, they behave much more like a private company owner does by treating the capital of the company as if it were their own money. They care about clarifying judgments rather than masking them, and they seek results rather than excuses.
Gregory V. Milano, a regular CFO columnist, is the founder and chief executive officer of Fortuna Advisors LLC, a value-based strategic advisory firm.