By Alicia Buksar, IBM Communications
As a teenager parking cars at a Fort Lauderdale country club, IBM customer analytics consulting leader Mike Haydock picked up much more than just tips.
Take the life lesson he received one day from Academy Award winning actor George C. Scott. “He gave me a tremendous insight on how he got into the role of Patton,” Haydock said. “He told me he became that role. He became Patton. That’s how he was able to pull that performance off.”
Haydock says he applies that same philosophy to his own work with clients. “I start to think like them,” he said. “So I know everything about the problem they’re trying to solve and probably more.”
That immersive approach has made Haydock, known as the ‘Math Maestro,’ one of IBM’s most sought after analytics experts, a demand that is likely to grow now that he has been named an IBM Fellow. The Fellow designation acknowledges an employee’s important contributions as well as their industry-leading innovations in developing some of the world’s most important technologies.
From designing the most efficient way to butcher cattle, to creating an original dynamic pricing model for airline fares, Haydock has applied deep analytics solutions with clients across a broad set of industries.
A self declared “data geek,” Haydock’s quarterly, predictive retail forecasts have become a staple for predicting sales trends. Haydock regularly applies analytics to some 22 years of historical retail data, consumer confidence, disposable income, unemployment data, stock market information, and a long list of other factors. He even developed his own algorithms to account for seasonal peaks and patterns, resulting in an accuracy rate of roughly 97 percent – four times more accurate than retailers’ own forecasts. It’s no wonder that when last October’s shutdown prevented the government from reporting retail sales data, Haydock’s phone was ringing off the hook for access to his data.
Haydock has the uncanny ability to bridge insight into innovation for clients. His team, for instance, is currently using Big Data analytics to understand how weather affects the buying behavior of individual consumers. They correlate sales data with data from the U.S. national weather service. Using this kind of analysis, retailers can tap their loyalty program data to identify which customers react to weather in predictable ways. Armed with this information, they can offer them targeted, weather-triggered promotions.
“To me, it’s a bit of an adventure,” Haydock said. “Everyone has a data warehouse. That’s very different from doing something predictive with the data. That’s a huge opportunity – the intersection between physical and digital. If I’m a retailer, for instance, I can take this information on my customers buying behaviors and change my menu board or my display lighting or change my social media promotion strategy. At the end of the day, it’s not just about the data, but what actions you can put in place to drive better results.”
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