The following is a guest post from Michael Paull, president and CFO at The Ahola Corporation. Opinions are the author’s own.
I once inherited a forecast model that seemed too good to be true. Revenue growth and profitability were exceptional. Cash flow was strong, financing needs were manageable, and nearly every metric moved in the right direction. It looked almost like a textbook example. Everything worked exactly as you would want it to. My immediate reaction was that there was no way the model could advance until I understood what was driving those results.
The model itself was solid. The spreadsheet logic worked, and there were no obvious errors or hardcoded numbers driving the results. The problem was in the assumptions, but not in the way I initially expected. When examined individually, they were easy to defend. I could see the business meeting the growth target. The margins looked reasonable based on recent trends and planned improvements. The headcount and expense ramp made sense. The problem emerged in the aggregate. Nearly every assumption leaned toward the favorable end of what was reasonable. Any one of them could happen, but the model assumed that nearly all of them would.
What concerned me about that experience wasn't that the model could be wrong. Forecasts are wrong all the time. It was that we could carefully review every major assumption, conclude that each was reasonable, and still end up with a forecast that I didn't believe. It reinforced the importance of professional skepticism. Sometimes the individual pieces withstand scrutiny and you still have to question the conclusion.
Part of the problem is how models tend to be reviewed. We go through the assumptions one at a time. Revenue? The growth target is defensible. Margins? The improvement is supported by recent trends and planned initiatives. Headcount? The hiring plan makes sense. Capital spending? There's a business case. Each assumption passes its own test, so we move on to the next one.
But validating each assumption individually doesn't tell us whether the forecast as a whole is reasonable. The more important question is whether we believe the company can deliver the growth, margin improvement, hiring plan, productivity gains and everything else embedded in the forecast over the modeled period. Each may be achievable on its own. The question is whether the collective outcome is believable.
Financial models can make this harder to see because they create an appearance of precision. A model can tell us that revenue will grow by 8.37% and the EBITDA margin will reach 24.62% three years from now. But we shouldn't confuse precision with accuracy. The number of digits after the decimal point tells us nothing about the accuracy of the assumptions behind the result.
Over the years, I’ve come to see the same dynamic outside of financial models. Businesses make decisions one at a time and for very good reasons. A new hire may be justified. So may another strategic initiative, a compensation adjustment or an unplanned investment. Each decision may be entirely justified. Subsequent decisions are often made while earlier ones are still maturing and their outcomes remain uncertain. That means the next decision may be evaluated while the results of earlier decisions are still unknown.
I've seen this happen as businesses grow. The next incremental decision can appear less significant than it really is. Another $100,000 of expense looks different against a $25 million cost base than it did against a $10 million cost base. Five additional employees feel different in a 200-person company than they did in a 100-person company. The accumulated financial impact may be fully reflected in the latest forecast, but that doesn't eliminate the tendency to view the next decision incrementally.
One CFO I worked for used to say, “Expenses are variable on the way up and fixed on the way down.” I’ve remembered that for years. Companies can add costs incrementally and for perfectly legitimate reasons, particularly when the business is growing. The difficulty comes when circumstances change, and management looks at the resulting cost structure as a whole. What was easy to add one decision at a time can be considerably harder to unwind.
The CFO’s broad view
Strategic initiatives can create the same problem. I have participated in plenty of meetings where every proposed initiative had merit. The technology project made sense. So did the sales initiative and the operational improvement.
Assume each has cleared the normal financial hurdles. The return is attractive, the capital is available and, evaluated individually, I might support every one of them. But approving another good initiative doesn't create more management capacity to execute it. At some point, the addition of one more priority can actually reduce the likelihood that the others will succeed. I think of this as management dilution.
AI is a timely example, as companies pursue worthwhile use cases across multiple functions, all drawing on many of the same technology, implementation and management resources. Management capacity is finite, yet it is often neglected as a gating factor when new initiatives are considered. Each additional priority draws on the same pool of leadership attention and organizational resources, potentially changing the likelihood of success for initiatives that have already been approved. The individual projects may all make sense. Taken together, management dilution can change the equation.
Whether we are evaluating assumptions in a financial model, incremental business decisions or strategic initiatives, the challenge is similar. Most management processes are designed to evaluate what is incremental. Companies are good at reviewing what is new.
They're less naturally inclined to reconsider everything that is already there alongside the new request. We scrutinize the new hire, the new investment or the new initiative because that is the decision in front of us. Everything already approved becomes the starting point. Over time, that can make the base almost invisible. Periodically, management needs to change the question. Instead of asking only whether the next decision makes sense, ask whether the accumulated result still makes sense for the business today.
That doesn't mean constantly reopening every decision or second-guessing whether it was right when it was made. Circumstances change, businesses grow, and subsequent decisions can change the environment around earlier ones. A decision can have been entirely reasonable when it was made and still deserve reconsideration in the context of the business as it exists today.
There also needs to be some contingency built into the business. The fact that each commitment can be justified doesn't mean the business should commit every available dollar, every person or every bit of management capacity. Some things won't work out as planned, and earlier decisions may still be maturing when new ones are made.
That contingency can take different forms, including liquidity, borrowing capacity, timing flexibility or simply enough management capacity to absorb something unexpected. This doesn't mean sandbagging forecasts or artificially raising the hurdle for every new investment. The objective isn't to make every individual decision more conservative. It's to recognize the uncertainty that exists when those decisions are considered in the aggregate.
That same discipline is how I still approach forecasts. I want to understand the individual assumptions, but eventually I step back from the detail and ask whether I believe the result. I have learned to ask the same question about the business itself. Sometimes there isn't a bad assumption, a bad investment or a bad initiative to point to. Each decision may have been entirely reasonable when it was made. That doesn't mean the aggregate result is one we would choose today.
CFOs spend a great deal of time evaluating the next incremental decision, whether it is a forecast assumption, hire, investment or initiative. But the CFO also has a unique view across the business. We see the financial results, operating decisions, investments and commitments accumulating across the company.
That broader view is valuable precisely because the problem may not be visible in any one decision. Sometimes the value of that broader view is simply recognizing when all of the individual answers look reasonable, but the overall answer doesn't.
