One of the biggest myths in business valuation, according to Prof. Aswath Damodaran (NYU Stern School of Business) is that "the more quantitative a model, the better the valuation." The first problem with such models is “input fatigue,” the professor said, during his recent three-day course on valuation for business executives (as reported in Business Insider). “What happens when it’s midnight and some beleaguered analyst has 76 inputs to enter? They might start to enter a few random numbers. If the model is big enough, it [the randomness] won't even matter to the final number.”

To demonstrate the second problem with quantitative models, Damodaran tells about the time he planned to value a stock at $35, then found that an equity research analyst had recommended the same stock at $85, based on an in-house valuation model. “What did it do,” Damodaran asked the analyst, “sneak into your office in the middle of the night, value the company, and leave it on your desk?" What the analyst was really saying: “I have this really complicated model, [and] it asks me for numbers. I feed it the numbers, it asks me to go get a cup of coffee, and by the time I come back there's the answer.”

“It’s amazing how with complex models you turn over responsibility,” Damodaran told his executive students. “Add detail to your model, but only if it adds value.”