Accurate-ish: Balancing Accuracy, Adaptability, and the Trap of Detail
MarkOrganizations don’t fail at planning because they lack smart people or sophisticated spreadsheets. They fail because their models collapse under the weight of their own detail.
Most planners have lived this. Months of late nights go into building a beautiful plan: endless reconciliations, dozens of variables, hundreds of calculation elements stitched together. The spreadsheets are immaculate and precise, the integrations fragile but holding. And then… someone asks the first hard “what if?”
Can we reduce our capital spend further? How can we still meet our guidance if production falls short in one segment?
Suddenly, weeks of effort are required to resolve these new questions. In one real-world case, an oil and gas planning team spent two months reconciling data across three regions. Then leadership asked for a 10% capital spend reduction — a scenario the planning system couldn’t handle. To avoid delaying decisions, the business ends up approving a superficial plan — not because it was right, but because there was no time to create an alternative. Downstream departments were left unclear on their goals, allocations, and constraints. Execution suffered before it even started, the organization was strategically misaligned, and all that hard work felt wasted.
Good planning is not about polishing one answer to a high shine. It’s about exploring, imagining, analyzing, and iterating. That takes time — but the right kind of time: time spent on exploration, not reconciliation. To escape the trap, planners need to balance accuracy with adaptability across three dimensions: people, process, and technology.
The People Side of the Trap
It’s not just about models. Planners are human, and humans love detail. Add one more variable, one more adjustment, one more process to “make it right.” Stakeholders drown in detail with a plan that feels comprehensive, but is impossible to grasp end-to-end.
It takes discipline to resist the pull of detail. To ask:
- Is this variable material?
- Will it change the decision?
- Can we explain it simply to non-experts?
If not, it probably belongs on the cutting-room floor.
There’s also the psychological hurdle of uncertainty. Precision feels safer than ambiguity. But leadership doesn’t need the illusion of exactness — they need clarity on ranges, likelihoods, and scenarios. A planner who can communicate uncertainty with confidence is far more valuable than one who hides it behind decimals.
Process Under Strain
Over-detailing doesn’t just tax the planner — it taxes the entire process. Every new calculation element introduces a dependency: fresh data feeds, reconciliations, and cross-department handoffs. Complexity scales faster than value. Each extra layer is another chance for errors to slip through.
Worse, the lag time between iterations grows. Instead of re-running the plan overnight, cycles stretch into weeks as the demand on other departments increase exponentially. By the time an updated plan emerges, the business has moved on. The process intended to produce clarity ends up producing irrelevance. Goodwill and engagement are lost.
Strong processes don’t abandon rigor; they prioritize it. It recognizes that not all variables are equally valuable and that not all opportunities are worth chasing. Test everything broadly in the early stages, but strip back aggressively on those elements deemed negligible. Keep iteration fast, the plan comprehensible, and the organization responsive.
Technology’s Double Edge
Technology can either amplify the trap or help escape it.
On the wrong side, it enables sprawling models with endless tabs and formulas, stitched together by poorly governed integrations. It gives the illusion of control while embedding fragility. Pushed too far, models break with novel errors, files crash and integrations break - leaving the planner and the business with a pile of data that is impossible to make sense of.
On the right side, technology accelerates iteration and supports robust analysis. Tools that run sensitivities in minutes (not weeks), handle the challenges of uneven, fat-tailed distributions, and have the right analytic capabilities to visualize and frame uncertainty in a way that makes sense for the business — these make true planning feasible. They allow planners to explore many futures, not just one polished but brittle version. For example, a dashboard that instantly recalculates multiple scenarios can turn hours of reconciliation into minutes of decision insight.
Technology can’t make the hard choices for you. But it can reduce the friction of running endless, mind-numbing iterations and provide context rich dashboards so your energy is spent on exploration and judgment, not reconciliation and debugging.
Materiality as a Discipline
The discipline that cuts across people, process, and technology is materiality. Not every variable deserves equal attention. Not every adjustment improves accuracy. Good planning explores widely and iterates quickly — but always with focus.
Careful analysis pursued too narrowly only deepens the trap. By contrast, disciplined planning widens the lens, stress-tests assumptions, and pays attention to where the fat tails live. It asks the questions that matter and ignores the ones that don’t.
Identifying the critical variables and opportunities is a discipline that requires a deep understanding of the business and the data. It is not a science, but an art. It requires a combination of data analysis, business knowledge, and a healthy dose of intuition. Done right, it identifies that which is most important to the business and the most likely to change. Whether that is water takeaway capacity this quarter or the performance of a new section of land next year, the right plan will help the business make the right decisions. Further, refining your focus to these are essential to reducing your people's cognitive load, streamlining your workflow and enabling your iterations to run faster.
Toward Accurate-ish Planning
The test of a good plan is not whether it looks impressive in a binder. It’s whether it helps make good decisions. Whether it can be explained clearly. Whether it can be iterated quickly. Whether it still holds under stress.
That’s the principle of “accurate-ish” planning: accurate where it matters, approximate where it doesn’t. It values speed of iteration over false precision, clarity over comprehensiveness, robustness over perfection.
Because the alternative is clear. A plan overloaded with detail is not a stronger plan. It’s just a slower, more fragile one — risking delayed decisions or missed market turns.
The real skill isn’t adding detail — it’s knowing what to leave out, so you can focus on exploring the scenarios that really matter.
Want to see how Bear Decisions can help you build more practical, decision-focused planning models? Join our waitlist for early access and updates. I'd love to hear about your own experiences with planning—what's worked, what hasn't, and how you've learned to balance accuracy with practicality.
Drop me a line at mark@babybearanalytics.com or connect with me on LinkedIn. I read every message.