“The biggest mistake we’ve seen is the assumption lot of company leaders have that they have made such massive investments in IT that they must have optimization all over the place,” Sashihara says. I interviewed Sashihara several months ago but only recently got around to finishing his book (I have my own business optimization issues, you see).
One of his most interesting arguments is that a great deal of the effort spent on information gathering and analysis is wasted — or, at least, used sub-optimally — when it’s used to feed business intelligence systems that produce reports that ultimately wind up with being fed into spreadsheets and PowerPoint slides. Managers then sit around in a conference room listening to presentations and debating what the data means and what decisions should be made about it — when, in many cases, good software could make the decision itself. The GPS in your car is optimizing when it says “turn left at Main Street” rather than presenting you with a list of possible routes.
“What makes a piece of software optimizing is that it makes a recommendation,” Sashihara says.
That’s not to say an optimizing system can’t be wrong. Sometimes your GPS gets confused and sends you down the wrong street. If you don’t entirely trust a corporate optimization system to make a decision, you may instead want to have it present a ranked list of recommendations. That’s essentially what Google does when it searches the web and presents you with a list of the pages it considers the most likely match for your keywords. The IBM Watson computer system that won on Jeopardy earlier this year also used an internal system of ranking the best matches for a given question, although it ultimately made it’s own best guess at the answer (see Computerized Jeopardy Champ Shows IBM What Is Analytics?). Some of the best optimization software gives users a way of seeing how it arrived at its conclusion so they know how far to trust it, Sashihara said.
Some industries have made extensive use of optimization software for specific business problems, such as supply chain optimization, transportation management, and price optimization for retailers. But Sashihara argues businesses have barely begun to tap the potential of the technology to be applied to any problem of limited resources — whether those resources are people, fuel, space on a shelf or in a truck, hours in the day, or dollars in the bank.
Sashihara uses the term “optimization” as one he thinks resonates with business leaders, but the discipline is more formally known as operations research. His book traces the beginnings of the field to military planning for World War II and the application of algorithmic approaches for iterating over many possible uses of resources to find the optimal combination. With computerization, these mathematical analysis techniques came to be applied to ever larger data sets. The airline industry applied these principles to yield management, allocating seats and calculating prices to fill planes and drive profitability.