The best city in your base case is often the worst in your downside one.
There’s a seductive moment near the end of every location analysis: one city tops the model. The board sees a
winner. The decision feels made.
Be careful with that moment. A location that’s optimal is optimal for a scenario- and scenarios are guesses in formal clothing. The city that wins your base case usually wins it by being sharply specialised: the deepest pool in one skill, the lowest cost for one activity, the perfect fit for the plan as written in this year’s strategy document. Specialisation is exactly what makes it fragile. Change the plan -pivot the product, double the hiring, halve it- and sharply specialised locations reprice brutally. The fix isn’t a better forecast; it’s testing the shortlist against several futures, not just the one written down.
Robust locations behave differently. They rarely top any single scenario, which is why naive analysis discards them. But run five futures instead of one- faster growth, slower growth, a product shift, a cost squeeze, a talent war- and the same handful of locations keep finishing second or third in all of them. Broad talent bases. Diversified economies. Multiple industries competing to keep the ecosystem healthy. No single point of failure.
Ten years is a long time to live with a lease. Over that horizon, the question isn’t “which city is best if everything goes to plan?” It’s “which city punishes me least when it doesn’t?” Ask any operator who scaled through a downturn: resilience beat brilliance.
None of this argues for timid choices- emerging locations can be highly robust, and famous ones can be fragile. It argues for testing the shortlist against futures, not just the forecast.
Multi-scenario analysis is core to how our Locations Assessment & Facilitation practice builds shortlists -we
pressure-test locations against your plan and its plausible variations, then facilitate the government conversations in the ones that hold up.
Reach out to us zoe@nueconomy.co.
