Here is the call I have been getting more of this year.
A firm is two years into a hold. The deal thesis was sound. The value creation plan was specific. There were initiatives, owners, and a timeline. And the growth is not there. Revenue is tracking under plan, margins have not moved the way the model said they would, and the board deck has started to fill with explanations instead of results.
The hold clock does not stop while you figure out why. By year two you have spent roughly 40% of a five-year hold, and the back half is where multiple expansion is supposed to compound. A stall now is not a rounding error. It is the difference between a top-quartile exit and a flat one.
The instinct at this point is to do something visible. Reorganize. Replace the CEO. Hire a senior operator. Commission a new strategy. Those are interventions. None of them is a diagnosis. And intervening before you diagnose is how firms spend year three fixing the wrong thing.
Why year two is when it surfaces
Year one hides a lot. There is integration noise, one-time costs, a honeymoon on the forecast, and enough new initiatives in flight that nobody expects clean numbers yet. Everyone agrees to be patient.
Year two removes the excuses. The initiatives have had time to land. The forecast has been reset at least once. The board now expects the plan to show up in the actuals. When it does not, the question changes from “are we executing” to “is the plan even working.” That is the right question. Most teams cannot answer it, and the reason they cannot answer it is almost never the reason they think.
The three wrong first moves
Before the framework, the three interventions I see firms reach for first, and why each one tends to fail when the plan has stalled.
The reorg. Results stall, so the org chart gets redrawn. Six months later the same problems report to different people. The boxes were never the problem. I wrote about this in The Reorg That Fixes Nothing. A reorg feels like progress because it is concrete and fast. It moves accountability around without touching the constraint underneath it.
The new hire. The board hires a senior operator or a data leader to “fix it,” without first agreeing on what fixed means or what authority the hire actually has. Twelve months of roadmap later, you have activity without progress. The same trap applies to data leadership specifically, which I covered in Stop Hiring a CDO When You Have Not Made the Decision.
The permanent pilot. Rather than commit to a change, the company runs a proof of concept. It shows promising results on clean sample data, and then nobody funds the work to scale it. Fourteen months of “promising” on a five-year hold is a quarter of the runway spent not deciding. That pattern is its own post, The Pilot That Never Ships.
All three share a root. They are responses to a symptom by a team that cannot see the actual cause clearly enough to name it.
The diagnosis nobody runs first
When a value creation plan stalls, there are only a few real possibilities. The thesis was wrong. The execution was poor. The market moved. Or the company cannot actually see its own performance well enough to know which lever is working and which is not.
The first three are visible. The fourth one hides, and it is the one I find most often. A portfolio company that cannot trust its own numbers cannot diagnose its own stall. It cannot tell you which customer segment is actually growing, which product line carries the margin, which initiative moved the needle, or which one quietly consumed budget and produced nothing. So it guesses. And then it reorganizes around the guess.
You can test for this directly. Ask the management team four questions and watch how they answer.
How long does it take to get an accurate number for a metric that matters, say margin by product line or revenue by cohort? If the answer is “a few days and a couple of people pulling it together,” the company is operating blind between those pulls.
Do two leaders, asked the same question, give the same number? When sales, finance, and operations each have their own version of the truth, every initiative review becomes an argument about whose data is right instead of what to do next.
Can you attribute the last four quarters of growth, or lack of it, to specific initiatives? If growth is a single line that goes up or down with no ability to decompose it, you cannot know what is working.
When an initiative is declared a success, what evidence closes the case? If the answer is a narrative rather than a number, the plan is being managed on conviction.
If the team struggles with these, the stall is not primarily a strategy problem or a people problem. It is that the company has been flying the value creation plan on instruments it cannot read. This is the same gap that produces the dashboard nobody opens, where six figures of reporting infrastructure exists and nobody uses it because the numbers would force a conversation the organization is not equipped to have.
What unblocking actually looks like
The fix is not a data project in the IT sense. It is making the plan measurable, in weeks, so the back half of the hold runs on evidence instead of explanation.
Pick the five to seven metrics the value creation plan actually depends on. Not the forty on the dashboard. The handful that, if they move, mean the thesis is working. For most mid-market companies that is something like revenue by segment, gross margin by product or service line, customer retention or net revenue retention, sales cycle or pipeline conversion, and one or two operational drivers specific to the business.
For each one, establish a single source and a single definition that finance, sales, and operations all sign. The goal is not perfect data. It is one number per metric that nobody relitigates. Most of the value here comes from killing the second and third versions of the truth, not from new tooling.
Then instrument the initiatives against those metrics. Every line item in the value creation plan should connect to one of the handful of numbers, with a baseline and a target. The ones that cannot be connected to a metric are the ones to question first, because they were never measurable to begin with.
This is the discipline behind a one-page data value creation plan. When the plan and the measurement share the same small set of numbers, the year-two review stops being a debate and becomes a read. You can see which levers moved, which did not, and where to put the remaining runway.
None of this requires a twelve-month transformation. The diagnosis is a few weeks. Establishing trusted definitions for a handful of metrics is usually a quarter. That timeline matters, because the reason to do it now rather than at year four is the same reason the exit backlog is punishing firms that wait. Data readiness in the early hold compounds. Done in year two, it guides the back half of the plan and it is already in place when the company goes to market. Done in year four, it is a fire drill that the buyer’s diligence team will see through.
Diagnose before you intervene
A stalled value creation plan is a real problem and it deserves a real response. But the response that works starts with a question most boards skip. Can this company see its own performance clearly enough to know what is actually wrong?
If it cannot, then the reorg, the new hire, and the next pilot are all bets placed in the dark. Run the diagnosis first. Find out whether you have a strategy problem, an execution problem, a market problem, or a visibility problem. Three of those need different fixes. The fourth one is the one nobody names, it is the one I am called in to find most often, and it is the most fixable of the four if you start in year two instead of year four.
If you are two years in and the growth is not where the model said it would be, that is the moment to look under the plan, not just at it.