Big Data Profile: Tim Rey, Steelcase

Math kind of guy Tim Rey talks about combining business acumen with numbers smarts, unstructured data woes, and improving the supply chain.

Michael Fitzgerald, Contributor

November 15, 2013

4 Min Read
Tim Rey, Steelcase

Tim Rey, Steelcase

Name and title: Tim Rey, Director of Advanced Analytics for Global IT operations, Steelcase, Grand Rapids, Mich.

How long at current job: Four and a half months. I've been doing analytics for 34 years, previously at Dow Chemical Co.

Career accomplishment of which I'm most proud: The teams and our solutions I think are really the things that you remember most. There was a project at Dow called demand sensing, a central forecasting database that can be used in supply chain, HR, customer service, marketing and sales, strategy, finance. I have also written a book, Applied Data Mining for Forecasting Using SAS.

Why I do what I do: I've always been a math kind of guy. I remember in third or fourth grade we were sitting in the classroom and the teacher was trying to keep us occupied. She was going through sequences of simple arithmetic, we had no paper, you were supposed to keep up in your mind and give the answer at the end. It seemed like I was winning that every time and I thought, "Hmm, maybe this is something I should think about."

Decision I wish I could do over: Maybe not getting my PhD. I consider myself a blue-collar type, I still would've gone into industry. But I think a PhD may have helped me handle some of the problems that came up.

Most important career influencer: Really early on, Dr. Wayne Myer at Michigan State University. At Michigan Tech it was Dr. Gene Hesterberg. In the Dow environment early on, Dr. Gary Blau. You learn how to be a modeler from people like that, how to take problems apart and then piece them together.

Top initiatives: We're pulling together a demand center, to do things like demand forecasting, for supply chain optimization. We have numerous supply chain projects underway, from simple data mining up through complex optimization and network theory type problems. We're helping the company understand the cycles, like looking for those things buried in your distribution centers where you may be purchasing independently. You can potentially take and source that out of one place and reduce your costs. On the operations side, we're doing some discrete simulation work to help reduce inefficiencies here in the plants.

You have to think forward and not have data operating in islands. So we're bringing in some organizational change, hiring people in the business who have business acumen and are not afraid of technology, people with a detective nature and quant skills. We call them Business Insight Explorers. We're adding some iron to do analytics.

Most disruptive force in my industry: Unstructured data. Because people are having to redesign corporate data architectures to handle it. And yet if you don't start to consume it, you will definitely be at a disadvantage competitively.

What is big data? I like to think of big data as anything too big, too fast, too much variety or too much of a problem for your systems to handle. If you're systems aren't designed to handle them, then it's too big.

One thing I'm looking to do better: Unstructured data is one of the things. Steelcase is moving down a globally integrated enterprise path that has a lot to do with a new data architecture. Data governance, master data management, those are a complement to that core data infrastructure. People want to get that whole thing perfect before they start analytics and that's a mistake.

Hardest thing about what you're doing: Helping people understand that it is a team effort. The in-the-business data experts and content experts have to be involved in these problems. You have to have the business acumen alongside the analytics acumen.


Education: MS, master's in statistics (forestry biometrics), Michigan State University; BS Michigan Technological University

Person I'd most like to have lunch with: George Box, a statistician known for saying, "All models are wrong, but some are useful."

First job: Cutting grass and babysitting in the neighborhood. First time I got a paycheck was from Fraser Parks and Recreation, umpiring for 8-year-olds.

If I weren't doing what I do: I would probably have tried to be a professional baseball player. I played shortstop in the semi-pros for six years after high school.

Making decisions based on flashy macro trends while ignoring "little data" fundamentals is a recipe for failure. Also in the new, all-digital Blinded By Big Data issue of InformationWeek: How Coke Bottling's CIO manages mobile strategy. (Free registration required.)

About the Author(s)

Michael Fitzgerald


Michael Fitzgerald writes about the power of ideas and the people who bring them to bear on business, technology and culture.

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