What Looks Like Inertia Is Often a Decision

The diagnosis nobody tests

An established firm is losing ground. Revenue in the core line is flat or sliding, a newer competitor is taking the interesting deals, and someone in the room — a board member, an advisor, occasionally the founder — says the thing everyone is thinking. They waited too long to pivot.

I have come to treat that sentence as a hypothesis rather than a finding, and the reason is a single study.

One embedded case study ran across eight companies in a mature industry undergoing transition, asking what actually explained the observed responses rather than looking for inertia stories. Its conclusion was that those responses were "the result of deliberate and justifiable strategic choices rather than path dependency and inertia" (Onufrey & Bergek, 2021). The authors then put the warning in terms that are hard to misread: "what might present itself as unwillingness, inability or resistance due to lock-in might very well be a deliberate — and justifiable — choice."

The spine: "They waited too long" has a rational-behaviour null, and almost nobody tests it. A firm that considered the pivot and rejected it on constraints you have not yet seen looks identical, from the outside, to a firm that was too slow to move. The remedies are opposite.

Why the collapse into one word is expensive

The deeper problem is that inertia is a single word covering at least four different things, and each has a different remedy.

There is the mental model — leaders who see the shift clearly but cannot re-frame what the business is. There is the investment pattern — the strategy deck changed, the budget did not. There is the process — money moved, but pricing, sales compensation, delivery and support still run the legacy motion. And there is allocation capture — where existing customers systematically starve the new business, and every "no" traces back to a named account.

I want to be careful here about what is established and what is merely named. Those four mechanisms are associated with a well-known literature — Tripsas and Gavetti on cognition, Gilbert on the resource-versus-routine distinction, Christensen and Bower on customer-driven allocation. I do not hold the full text of any of those papers, so I am naming the concepts and attributing them, and I am drawing no findings, numbers or effect sizes from them. That distinction matters more than it sounds: a claim sourced from a secondary summary of a paper is a claim about the summary.

What I can assert from held full text is that the investment pattern and the process are empirically separable. A multiple case study of six leading product manufacturers, built on 86 manager interviews, describes the shift to smart-solution provider as requiring three distinct realignments (Huikkola, Kohtamäki, & Ylimäki, 2022) — strategic capabilities, organizational routines, and dominant logic. That study needs three axes because a firm can move capability investment without the routines following.

The diagnostic tell is simple enough to use in a board meeting. The deck changed but the budget didn't is an investment problem. The budget changed but the calendar didn't is a process problem. Those two look the same in a status update and have almost nothing in common as interventions.

The evidence contradicts "move fast and decisively"

Here is where the held literature diverges most sharply from consulting reflex.

The same six-manufacturer study found that "overly rapid capability changes would not produce favorable outcomes" (Huikkola et al., 2022). Reconfiguration in those cases ran incrementally, and — this is the part that gets skipped — in parallel with the existing business, not as a replacement for it. Those manufacturers retrofitted the installed base first, because equipping only newly sold units would take too long to reach meaningful scale (Huikkola et al., 2022).

That is close to the opposite of the burning-platform advice a declining firm usually receives. It does not mean slow is safe. It means pace is an empirical question with an answer that ran against the prescription in the cases actually studied.

The governance evidence points the same direction. A matched-pair design on US manufacturing firms in decline, drawn from COMPUSTAT, produced the clearest governance result I hold (Mueller & Barker, 1997). Turnaround firms maintained a significantly greater proportion of outside directors across the entire comparison period. Board size was not significantly associated with turnaround in any year. And the top-team difference — recovering firms ended up employing a significantly smaller proportion of their pre-decline top managers — showed up at the end of recovery.

Read that ordering carefully, because it inverts the usual move. Replacing the leadership is commonly prescribed as the thing that causes turnaround. In this sample the replacement is visible after recovery is underway. The structural difference that held throughout was outside directors — decision structure, not personnel.

The harvest assumption the evidence will not carry

The most common plan for a declining core is to harvest it: run it for cash, and fund the new thing from the proceeds.

The eight-company study complicates this directly (Onufrey & Bergek, 2021). In those cases, new products were built from residual streams of the existing process — which means those new products depended on the old process continuing to run. Harvest the core too hard and you can starve the pivot it was supposed to fund.

There is a second problem, and I will state it as a gap rather than a finding: no paper I hold in full text measures whether a deliberately starved core declines at the rate a harvest plan assumes. The harvest plan's founding assumption is, in the held corpus, untested. That is not the same as wrong. It does mean that if your plan depends on the core decaying gently for three years while the new line ramps, you are relying on an assumption you should name out loud and stress-test, rather than on evidence.

The SME inversion — and I am labelling this one as mine

One study analysed 1,575 entries and 481 exits across 163 firms (Lieberman, Lee, & Folta, 2017). Its argument: relatedness between a new business and existing ones lets a firm redeploy resources back inward if the bet fails. That lowers the de facto sunk cost, which speeds exit, which in turn makes riskier entry rational in the first place. That result holds for internally developed entries rather than acquisitions (Lieberman et al., 2017).

Now the part that is my inference and not the authors' claim. Every study I have cited here observes large firms — multi-business diversified firms, leading manufacturers, listed companies. A single-business small or mid-sized firm has nowhere to redeploy a failed bet to. Its sunk costs are more genuinely sunk. Run the same model at that scale and it implies an SME should be more cautious about entry than a diversified firm — which means an owner's reluctance to pivot may be the model behaving correctly rather than rigidity Sagentix GTM Methodology, 2026.

I flag it as an inference because it is one. It is also, in my experience, the single most useful question to put to a cautious owner: is nothing moving because you cannot move, or because moving is genuinely worse for a firm your size?

The scorecard habit that biases the answer

One last thing, and it is the most immediately actionable.

When a firm finally does compare renewal options, it usually builds a scorecard: criteria down one axis, options across the other, weights assigned by the leadership team. The weighting is almost always done by handing people a hundred points to distribute.

A review of eight criteria-weighting methods used in multi-criteria decision analysis found an inverse relation between a method's complexity and its bias potential (Németh et al., 2019). Direct weighting is the cheapest — no software, no training — and, in that review's words, "can also lead to significantly biased results."

The cheap method is the biased one. If a decision worth years of a firm's future is being weighted by point allocation in a two-hour offsite, the arithmetic downstream is precise and the input is not.

Where this leaves the diagnosis

At Sagentix I build go-to-market strategy for established B2B firms, and portfolio-renewal decisions are where the evidence discipline earns its keep. Every deliverable runs a 16-point quality gate against a curated base of 727+ artifacts, on a 6–8 week delivery, and Phase 1 carries a money-back guarantee — because a diagnosis you cannot audit is an opinion with formatting.

The reason I am strict about held-versus-named sources is visible in this piece. Four of the most-cited papers in this entire field are ones I could not obtain in full text, so they appear here as concepts with attribution and contribute no numbers. That constraint made the argument narrower and, I think, more useful.

Three things you can do with this, only one of which involves me.

Test the null yourself. Before accepting that a firm waited too long, ask what was knowable at decision time, whether you would call the same behaviour prudence had the firm grown, and whether the pivot was already considered and rejected. If the inertia reading is being supplied by the outcome rather than the evidence, you have hindsight, not a diagnosis.

Fix the weighting. If you are running a renewal scorecard, stop using direct point allocation. The low-resource alternatives rate as less bias-prone (Németh et al., 2019), and switching costs you one afternoon.

Or bring in someone whose job is to be wrong in public. The value of an outside read on a renewal decision is not the framework. It is that an outsider has no stake in the answer being "you were right all along" or "you were asleep" — and the evidence says the board-level version of that, more outside directors, was the structural feature that separated recovering firms from non-recovering ones throughout the entire period (Mueller & Barker, 1997).

What is the last renewal decision you saw diagnosed as "too slow" — and was the rational-behaviour null ever actually tested?

References

• Huikkola, T., Kohtamäki, M., & Ylimäki, J. (2022). Becoming a smart solution provider: Reconfiguring a product manufacturer's strategic capabilities and processes to facilitate business model innovation. Technovation, 118, 102498. https://doi.org/10.1016/j.technovation.2022.102498

• Lieberman, M. B., Lee, G. K., & Folta, T. B. (2017). Entry, exit, and the potential for resource redeployment. Strategic Management Journal, 38(3), 526–544. https://doi.org/10.1002/smj.2501

• Mueller, G. C., & Barker, V. L., III. (1997). Upper echelons and board characteristics of turnaround and nonturnaround declining firms. Journal of Business Research, 39(2), 119–134. https://doi.org/10.1016/S0148-2963%2896%2900147-6

• Németh, B., Molnár, A., Bozóki, S., Wijaya, K., Inotai, A., Campbell, J. D., & Kaló, Z. (2019). Comparison of weighting methods used in multicriteria decision analysis frameworks in healthcare with focus on low- and middle-income countries. Journal of Comparative Effectiveness Research, 8(4), 195–204. https://doi.org/10.2217/cer-2018-0102

• Onufrey, K., & Bergek, A. (2021). Transformation in a mature industry: The role of business and innovation strategies. Technovation, 105, 102190. https://doi.org/10.1016/j.technovation.2020.102190