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What predicts a turnaround? Rate of change.

July 5, 20268 min readMichael Franklin

TL;DR

The best predictor of a turnaround is not the plan, the new leadership team, or the capital structure. It is the rate of change - how fast the company runs experiments, learns, and goes again. We call the engine that drives it the Rate-of-Change Loop: ship the good-enough idea now, learn from it, repeat. Speed and quality climb together. You can start this week.

Here is the most useful pattern I have found in more than 20 years of turnarounds. What predicts whether a company comes back is not the strategy deck. It is not the new leadership team, and it is not the capital structure. It is the rate of change.

Rate of change is how fast the organization can try something, learn from it, and try the next thing. Raise that number and almost everything else follows. The best news for an operating partner: it is the most controllable lever you have, and you can start moving it this week.

What actually predicts a successful turnaround?

The rate of change predicts it. A company that runs ten small experiments a quarter will outrun one that spends the quarter perfecting a single plan. Each cycle teaches you something a deck never could. Many fast loops compound into gains that no amount of planning can match.

The capital markets are converging on the same point. Bain's 2026 global private equity report finds that leverage and multiple expansion have waned as reliable return drivers, while firms with real operational muscle pull ahead. McKinsey calls the fastest organizations decision-making winners: they decide fast, execute fast, and are twice as likely to report superior returns.

Isn't private equity already moving fast?

Faster than ever, and that is real progress. Alvarez and Marsal's 2026 value creation survey found 58 percent of firms now deploy resources within the first 100 days, double the 29 percent of a year before. But the same survey found 65 percent captured less than half the value they targeted. The gap is rhythm, not intent: early deployment that never settles into a compounding cadence.

Why does good enough beat perfect?

Voltaire put it three centuries ago: the best is the enemy of the good. A good-enough idea in production teaches you more than a perfect idea on a slide. You learn from contact with reality, not from analysis. The longer you wait for the perfect answer, the longer you learn nothing.

What is the Rate-of-Change Loop?

The Rate-of-Change Loop is Cold Iron Labs' name for the operating rhythm that turns a company around. You run it in four beats:

  • Pick the good-enough move.
  • Ship it now.
  • Learn from what actually happened.
  • Repeat tomorrow.

No single cycle has to be brilliant. The power is in running many cycles fast, which is the one thing planning can never replicate. You do not need a number on the wall. You need next week to hold more shipped experiments than last week.

Two cautions keep the loop honest. First, speed only helps if you cycle on the right hypothesis. Fast cycles in the wrong direction burn cash just as fast, so the first move is choosing the bet worth running. Second, good enough applies to commercial, operational, and process experiments. It does not apply to product safety, regulatory compliance, or any change you cannot reverse. There, you earn the right to move fast by building the guardrails first.

But doesn't moving fast mean lower quality?

It is the most common worry, and the evidence runs the other way. In McKinsey's survey of more than 1,200 managers, those who called their decisions fast were 1.98 times more likely to also call them high quality. The two travel together. McKinsey's own read is that good decision habits produce speed and quality at once, not that rushing manufactures quality. Fast cycles simply give you the feedback that sharpens the next call.

Here is the contrast operators feel in the building:

Perfect-firstThe Rate-of-Change Loop
Planning horizonMonthsDays
Cycles per quarterOne big betMany small ones
Where you learnThe conference roomThe real world
Risk per moveHigh, all on one planLow per move, when bets are small and reversible
Team energyWaiting for sign-offMoving, visibly winning

Isn't this just agile or lean with a new name?

Fair challenge. The core insight is the same one Lean and Agile captured: small, fast cycles beat big, slow plans. But in our experience, those programs often stalled in portfolio companies for one reason. They were installed as company-wide programs, with training decks and ceremonies, instead of as habits. The Rate-of-Change Loop starts smaller and more human: a few people with suppressed drive, a handful of changed daily routines. Habits stick where programs fade.

What do you need in place before the loop works?

Two things, and neither shows up on a due diligence report: agency and habits.

The first is agency. In a company that has been in slow decline, most people have learned to stay in their lane and wait for instructions. That is not a character flaw - it is a smart response to the old rules. You do not need everyone to become a risk-taker. You need the handful of people who always had drive but were held back, and you give them room to move. They are your force multipliers, and they are already on the payroll.

The second is habits. Culture is not the statement on the wall. It is what people do at 9 a.m. on a Tuesday when no one is watching. Those habits are remarkably durable. They outlast strategy changes, leadership changes, even new owners. So you do not change culture by talking about it. You change the daily habits: a new meeting cadence, a new way decisions get made, a new definition of what gets celebrated. Change the Tuesday, and the culture follows.

Rate of change, agency, habits. None of the three shows up in diligence. All three decide whether the investment works.

Why do most AI pilots stall, and what gets them to production?

The same wait for perfect that stalls turnarounds stalls AI pilots. Teams hold out for the perfect AI strategy, the perfect data, the perfect platform. The pilot never ships.

The numbers are sobering. MIT's 2025 State of AI in Business report found that 95 percent of enterprise generative AI pilots delivered no measurable return, while a focused 5 percent captured real value. Gartner expected at least 30 percent of generative AI projects to be abandoned after the proof-of-concept stage. The studies point to integration, ownership, and adoption as the gaps, rarely the model itself.

The cure is the same loop, with one rule. Put a good-enough AI agent into one real, low-stakes workflow this month: a draft, a summary, an exception flag. Keep a person reviewing its output before anything acts on it. Good enough does not mean ungoverned. Watch what it gets right and wrong. Improve it next week.

The teams that win are not the ones with the grandest roadmap. They are the ones running the most cycles. You build that capacity inside the company by pairing a trusted operator with agents that carry the technical work. That person is the AI Integrator: not a data scientist or a new hire, but someone who already knows your operation and now owns the agent and its iteration loop. They are how a good-enough pilot becomes daily production use.

The bottom line

The takeaway is simple, and it is good news:

  • The rate of change is the best predictor of a turnaround, and it is the lever you control most directly.
  • Good enough beats perfect, because a shipped idea teaches you what a perfect plan cannot.
  • Fast and good are not enemies. Fast and high-quality decisions tend to travel together.
  • Find the people with suppressed agency, change the Tuesday habits, and the loop starts turning.
  • The same loop is how you win with AI: ship the good-enough agent, govern it, learn, repeat.

Pick one good-enough move you have been over-analyzing. Ship it this week. Then do it again.

FAQ

What is the Rate-of-Change Loop? It is Cold Iron Labs' name for the operating rhythm that drives a turnaround: pick the good-enough move, ship it, learn from what happened, and repeat. The power is in running many small cycles fast, which compounds faster than any single plan.

What is "rate of change" in a turnaround? It is how fast a company can run an experiment, learn from it, and run the next one. A higher rate of change means more learning cycles per quarter, and those cycles compound faster than any single plan.

Doesn't shipping "good enough" create quality problems? Rarely, when the moves are small and reversible. Fast decisions correlate with high-quality ones, per McKinsey, because quick cycles generate the feedback that improves the next call. Safety, compliance, and irreversible changes are the exception - build the guardrails there first.

Where do I start if the organization is stuck? Find the people who already have drive but were held back, give them room, and change one daily habit. Start this week, not next quarter.

How does this apply to adopting AI? The same way. Put a good-enough agent into one real, low-stakes workflow now, keep a human reviewing it, learn, and iterate. Most pilots stall waiting for perfect; speed of governed iteration is what separates the teams that win.

Sources

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