What Happens When You Assume?
(you make an “ass” out of “u” and “me”)
(you make an “ass” out of “u” and “me”)
Last year a K-8 charter school hired us to solve their problem. They wanted to build their own new campus and expand into K-12. The school is well-performing, popular locally, and there’s a clear need for another high school option in the area. All makes sense so far.
But one of the conditions they gave us – the problem – was a hard limit on how much they could finance for the new campus. We’ll just say it was a low number for purchasing land and building a brand new construction K-12 campus for 700+ students. For context … the number would only cover about half the cost.
Whew. That’s a very large gap. We got to work (utilizing one of our basic Nonlinear Rules: “Don’t Panic”) and began exploring how we might bridge the huge gap and feasibly develop a great school. New revenue streams, partners, transferrable development rights, alternative construction methods – anything we could devise to bridge that huge gap.
This was a major challenge. We did a lot of research, experimented with space programming, modeled different financing schemes, and pulled at threads that went nowhere. The gap we were trying to solve just felt too wide.
But then it occurred to us – we had failed to follow our own advice.
We’ve written about it before and it’s something we practice in just about every project we work on. When you’re looking for the way forward and it feels impossible, it’s important to question your own assumptions.
In this case we had assumed that all the conditions we were given at the outset were truly accurate. So we started to wonder, where exactly did that cap on their financing ability come from?
We then started the whole thing over from scratch and ran all the numbers ourselves to test that limit.
We built a financial model of the school’s operations, projected enrollment and revenues, staffing and other expenses, current liabilities – everything. We conceptually designed the project, programmed the uses and spaces, reasonably estimated its capital costs, plugged in what we know to be realistic finance terms, and made some other necessary assumptions.
And all of a sudden it didn’t look so bad … our model was suggesting that the school shouldn’t be this limited in their access to capital for the new campus.
Really? It works? Immediately, we had to wonder – did we miss something? Were we wrong?
We took our model to two different charter school lenders, as well as to a capital advising firm with extensive experience in the education sector. Everyone agreed – there was no clear reason the school should be limited to that initial financing number. They were performing well enough to carry a much larger (and more realistic) project.
There really was no financing gap.
With some new confidence in our numbers, we went on to create a feasible model for an outstanding new K-12 campus. It’s bankable, realistic, and could absolutely be accomplished.
And it’s sustainable – the school would get everything they wanted, plus a couple special features, some new revenue streams, and would actually be putting money in the bank every year.
We’ll never know exactly where that one false condition came from – simple miscommunication, modeling error, or wherever. Ultimately it doesn’t matter. The lesson this whole experience reinforced was: always question your assumptions.
Sometimes the starting line simply isn’t where you think it is.
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