The Art of Financial Modeling

The problem with most financial models is that they either make just a few overly generalized assumptions or they try and break down everything to its most basic element. While neither is wrong, the level of assumptive detail is often decided based on faulty logic. Financial models should always be created with one major question in mind: can you manage the model so it is both flexible and meaningful?

The last major model that I reviewed was for a medium sized service company in a very basic industry, but the problem was that they had built a workbook with a whopping 77 worksheets! There will always be a place for companies with financial models well above 77, but not a medium sized company with only a handful of financial people to keep the wheels turning. With all the cross-calculations going on and no clear structure, the model is completely useless. Like all systems, the level of complexity rises exponentially with each additional element.

On the other end of the spectrum, I recall working on a complex supply-chain case competition in business school, and using simple graphical charts to forecast supply-chains. Sure we did all the complex calculations, but in the end we realized that managing the system was entirely too complex, rendering all our hard work useless. Essentially, we just started graphing the data and adjusting the model based on what we saw on the graphs. We shot from dead last in the competition to second place by simply modeling something that we could understand.

There will always be those people who want to break everything down to the financial periodic table, but when the rubber hits the road and the landscape starts to change, it will be those people who actually understand their model, as simple and modest as it may be, that will quickly adapt their models and make good decisions because they we working with good models.