# We Know the Number Is Wrong. Put It in the Deck Anyway. 2026-10-12 · Somerset County, New Jersey · Reported Feature The strangest part of stale business data is not that companies have it. It is that executives sometimes know it is stale, make the decision anyway, and keep moving. The strangest part of stale business data is not that companies have it. It is that executives sometimes know it is stale, make the decision anyway, and keep moving. --- Almost every large organization harbors a specific, familiar kind of meeting. The deck is finished. The forecast has been circulated. The numbers are clean enough to fit inside boxes, the boxes are aligned, and everyone has had just enough time with the material to develop opinions about it. Then somebody says the thing everyone already knows: the assumptions have moved since this was built. And the meeting continues. That is what makes a new survey from Board, an enterprise planning software company, more interesting than the software pitch underneath it. Board's 2026 Planning Intelligence Report surveyed 300 CFOs, CIOs and COOs at companies with at least $100 million in annual revenue. Eighty-three percent said their board had made a strategic decision based on a forecast it already knew was outdated. Forty percent said that decision produced significant business consequences. The problem is not simply that information gets old. Of course it does. Markets move, customers change their behavior, costs shift, competitors do something inconvenient and the world generally refuses to freeze while somebody finishes a PowerPoint. The more revealing part is what organizations do after everyone agrees the information has aged. Three-quarters of the executives surveyed said roughly half or more of their planning decisions rely on data that is more than 30 days old. At the same time, 85 percent said pressure to make decisions faster has increased over the past year. Only 27 percent said their organizations can re-plan in real time. That creates a wonderfully corporate contradiction: the decision has become more urgent while the machinery used to support the decision has not necessarily become more current. The deadline accelerates. The forecast does not. Eventually somebody has to choose between waiting for better information and making the call with what is already on the screen. There is comfort in a number, even when everybody in the room understands that the number is no longer quite right. A number looks like evidence. It can be placed in a table, compared with another number, turned green or red, and carried into the next meeting. Uncertainty is harder to format. “We don't know yet” does not fit neatly into a forecast model, and “the conditions changed Tuesday” is much less satisfying than a cell containing $14.7 million. This is how having information can quietly become confused with knowing something. The survey contains another version of the same problem in its AI findings. Fifty-nine percent of respondents said their organizations' AI investment currently exceeds the value it delivers, yet 92 percent of that group still plan to increase AI spending over the next 12 months. Twenty-one percent said their organizations present a more optimistic picture of AI performance to boards, investors and peers than current reality warrants. That does not mean the companies are irrational. It means organizations are very good at building momentum around decisions. Once a budget exists, a strategy has been announced, a board has been briefed and a program has acquired owners, stopping to say “the evidence changed” becomes its own kind of decision. Sometimes the stale forecast is not merely a data problem. It is an institutional friction problem. The report also says 61 percent of respondents cite large language models among the external sources that most influence their strategic decisions, more than industry peers and professional networks, technology vendors, external consultants or Gartner. Thirty-one percent said they follow an AI recommendation even when it conflicts with their own judgment; among CFOs in the survey, that figure was 48 percent. Only 39 percent reported formal governance and escalation processes for AI-driven decisions. Those numbers belong to a separate technology conversation, but they reinforce the same underlying question: what happens when the tools used to create confidence move faster than the systems used to establish accountability? Board, naturally, argues that the answer is better and more continuous planning. It sells an enterprise planning platform, so its report should be read with that commercial context in view. But the survey's most useful observation does not require buying anything. It is the gap between the pace at which organizations are expected to decide and the pace at which they can actually know. Modern business culture has spent years celebrating speed. Move faster. Shorten the cycle. Get to market. Make the call. Do not let perfect become the enemy of good. Most of that advice exists for a reason. Endless deliberation can become its own failure mode. But there is another failure mode hiding on the opposite side: treating decisiveness as proof that the decision is informed. A stale forecast can still be the best available forecast. A leader can knowingly use imperfect information and make a perfectly defensible decision. The strange part begins when the caveat disappears as the information moves upward. By the time the number reaches the boardroom, the messy conditions that produced it can become a footnote while the number itself remains large, centered and confidently formatted. The timeline remembers what the room forgets. The forecast was built on Tuesday. The market changed Thursday. The board met Monday. Everyone knew. The slide still said what it said. And somewhere, somebody clicked “Present.” SOURCE NOTES • Board, “83% of Executives Say Their Boards Acted on Forecasts Known to Be Outdated,” September 16, 2026 --- ProbleMattic is written and maintained by Matthew Kulcsar, a software engineer, project manager, technologist, platform builder, emergency-services-trained helper, grandfather, and lifelong collector of broken systems, odd behaviors, and useful nonsense.