What the research found
Larry Greiner’s Harvard Business Review analysis of how organisations evolve through growth, still widely taught more than fifty years after its original publication and republished as an HBR Classic with the author’s own updated commentary, describes growth as moving through distinct phases, each of which works well for a period and then produces its own crisis, requiring a different way of operating to resolve. Greiner’s central point, easy to lose in summary, is that the practices which enabled growth at one stage — a founder’s direct oversight, a single informal operating rhythm, close personal relationships across the organisation — are frequently the same practices that cause the next crisis when the organisation outgrows the conditions those practices assumed.
A related and complementary finding comes from Jay Galbraith’s research on organisation design, published in Interfaces, which explains organisational structure as a response to information-processing demand: as an organisation takes on more uncertainty and more coordination points, the volume of information that has to move through it rises, and structures that worked when that volume was lower start to strain. Applied to a franchise network, rapid expansion is, among other things, a rapid increase in information-processing demand — more sites, more local conditions, more variation to track — arriving faster than the organisation’s coordinating structures were built to absorb.
Why speed compounds risk in a franchise model specifically
A franchise model is, in effect, a hypothesis about how a business operates, packaged so it can be repeated by an independent operator. Every location added to a network is both an application of that hypothesis and, whether intended or not, a test of it. In a slow-growing network, each new location has time to reveal whatever the model got wrong before the next location is signed — problems surface, get noticed, and can influence how the model is refined before it is applied again. In a rapid-growth network, several locations may open in the time it would take to properly evaluate how the first one performed, which means each new site is built on a version of the model that has had proportionally less real-world testing behind it.
This is distinct from, and compounds, a capacity problem that is easier to see and more commonly discussed: whether the central team has enough people to support the sites it already has. Nelson Repenning and John Sterman’s research at MIT Sloan, published in California Management Review, describes what they call the capability trap — a pattern in which organisations under pressure default to working harder rather than working smarter, because the people who would otherwise invest in improving underlying capability get pulled instead into firefighting the most visible problems. Rapid franchise expansion creates exactly the pressure that trap depends on: more new sites needing more onboarding support, more variance to manage, and correspondingly less organisational slack available to step back and ask whether the model itself needs revising before the next site opens.
The result is a specific kind of risk that does not show up cleanly in financial projections, because it concerns the reliability of the model being scaled, not the capital behind the scaling. A network can be well-capitalised, well-staffed relative to its current site count, and still be accumulating operational risk if new sites are opening faster than the organisation can absorb what each one reveals.
Where this shows up differently by stage
Early in a network’s growth, this risk is often masked by favourable selection: the first locations added after a proven concept tend to be chosen carefully, in conditions close to the ones the model was originally built around, by operators the franchisor has vetted closely because there are not yet many of them to manage. Risk tends to become visible later, once growth has accelerated enough that site selection, vetting and onboarding are being handled at a pace that leaves less room for that same level of individual attention — precisely the point at which Greiner’s framework would predict the organisation is approaching a transition it has not yet built the structure to handle.
A further complication specific to franchising, rather than company-owned multi-site expansion, is that each new site represents a new independent operator with their own capital and their own learning curve, not simply a new location the existing organisation can staff and train directly. Rapid expansion multiplies the number of operators simultaneously going through that learning curve, which increases the volume of variation the central organisation has to track at precisely the moment its capacity to track variation individually is most strained.
This does not mean rapid expansion is inherently unsound — some networks scale quickly and manage the risk well, typically by building central capability ahead of the growth curve rather than in response to it. It does mean the pace of expansion is itself a variable worth examining directly, rather than treating operational strain, when it appears, purely as a resourcing or hiring problem to be solved after the fact.
A useful distinction here is between growth that is fast because demand and site quality allow it, and growth that is fast because a target — investor expectations, a funding milestone, a competitive land-grab — sets the pace independently of what the operating model has actually demonstrated it can support. The former still carries the risk described above, but the organisation is at least choosing its own pace in response to what it is learning. The latter decouples expansion speed from operational readiness entirely, which is where the risk tends to compound fastest and go least noticed, because the metric being optimised — sites signed, units opened — says nothing about how well any of them are actually running.
Where this shows up
The pattern described here is most recognisable in franchise networks, part of the wider Multi-Site and Franchise grouping. The same organisational questions appear, under different names, in other sectors.
Questions worth considering
- Has the organisation’s central support capacity grown in proportion to site count, or is it running further behind with each cohort of new locations?
- How much has been learned from recently opened sites before the next batch was signed — and did that learning actually reach the people making the next decision?
- If growth paused for a period, what would the organisation discover about sites opened in the last twelve to eighteen months that it does not currently know?
Your team is facing similar challenges?
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