CIOs are constantly urged to quantify IT needs in terms of ROI, cost savings and the bottom line these days, so that CIOs, CFOs and directors will understand. That approach no doubt beats vague requests, but it isn't without limitations. A fascinating post by William Byers, a mathematics professor at Concordia University, sets out the risks of always trying to describe reality with numbers.

Using mathematics to make a point appeals to our desire for precision and objectivity, but it doesn't allow for flexibility, Byers writes in a post at HarvardBusinessReview. While numbers give us a sense of security and control over our problems, they fail to take into account the totality of situations involving humans, and therefore can end up creating new problems.  

Byers sets out four issues that reveal the limitations of business and financial models. First, they leave little room for ambiguity, even though ambiguity is at the crux of most business problems. Second, they give us the false sense that everything is linear and that things can be compared, when reality involves all kinds of qualitative variables that are hard to rank.  

Third, most of the systems we deal with involve humans one way or another, and therefore they are self-referential, making them tricky to predict or control and chaotic, but models tend not to take this aspect of human behavior into consideration. Finally, models evidently are based on the concept of randomness, which cannot be predicted, so a "model of randomness is no longer true randomness," he writes.

CIOs know all too well that uncertainty is a fact of life and that the best statistical predictions can end up being way off. But uncertainty has a tendency to make things more complicated and expensive, which is why CFOs or CEOs may not want to hear about it. The next time you have to make a pitch to the higher ups, it might help to point them toward Byers' work. 

"Admitting uncertainty means facing reality--and our own needs for security," he writes. "But admitting uncertainty is not enough. We must learn to actively embrace uncertainty and work with ambiguity."

For more:
- see William Byers post at HarvardBusinessReview

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