Case Study: Oberweis Dairy

This is part 3 of 10 from the 2013 Data & Analytics Global Executive Study and Research Project.

Milkmen, glass bottles, door-to-door service.

In some ways, not much has changed at Oberweis Dairy, Inc. from its founding at the turn of the last century. Milk is still procured from local dairy farms. Dairy products are additive-free. Milk is delivered in glass bottles to customers’ doorsteps, although nowadays Oberweis uses refrigerated trucks rather than horse-drawn milk carts.

In other ways, everything is changing at the nearly 100-year-old company.

What started as an Illinois farmer selling his surplus milk to neighbors in 1915 is now an analytics-savvy company with revenues approaching $100 million. Oberweis Dairy has three distribution channels: home delivery, with thousands of customers; retail, with 47 corporate and franchise stores; and wholesale, to regional and national grocery chains like Target. In 2012, the company began looking to expand from its Midwestern roots to the Eastern Seaboard.

At Oberweis, the usual approach to regional expansion was to bring together operations executives to figure out the best configuration for these resources. This time was different.

This time, CEO Joe Oberweis brought to the strategy table an executive with just three years’ experience at the company, Bruce Bedford, vice president of marketing analytics and consumer insights. He had been brought on board in 2009 to inject some analytical thinking into the family-run company. However, he was a relatively unknown figure to the operations executives. According to Bedford, on the day of the strategy meeting:

The CEO invited a large number of operational decision makers — literally, people who manage the company’s drivers and transfer centers. When I got to the meeting I said, “Hey, there are some things I’d like you to consider beyond just operations. I’d like you to think about our customers, particularly the customers that we currently have, who are great candidates for our service. And then let’s also evaluate customers that we’ve spent a lot of money to acquire in the past, that didn’t ultimately turn out to be great customers.”

Bedford took the team through his analysis of Oberweis’s target customer segments using data sets based on community-level demographic information. Contrary to the company’s conventional wisdom, he had discovered that the so-called Beamer and Birkenstock group — liberal, high-income, BMW-driving, established couples living leisurely lifestyles — weren’t a good fit for Oberweis’s high-end retail dairy products. Analytics essentially shattered the company’s preconceived notions about its target market.

Once Bedford demonstrated the possibilities of utilizing data analytics to segment the customer market, the meeting shifted from tactical, focusing on operations — how many trucks and transfer centers would be required and where they should be located — to strategic, stepping back to define the target market. “From a marketer’s point of view, this seems to make perfect sense,” said Bedford. “But it didn’t necessarily make sense initially to people in that room. Because that’s not how they think.”

Oberweis’s expansion plans are now being driven by analytics. More importantly, Bedford says, the company’s decision makers are thinking about using data analytics within their own areas of expertise:

I’ve started to see people now say, “Wait a second, you know what, this analytic stuff, there’s some power here, and maybe I should take the time to learn a little bit more about what Bruce is doing that maybe I could do.”They’re saying, “I’m not sure what I should be asking about, but let me at least ask if there’s something that I should ask about.”

It comes down to having a number of people who don’t ordinarily use analytics stop and see the light bulb go off. The change is cultural, and to a point now where people want to acquire a better understanding of analytics tools because they can see that there is real benefit.

The Oberweis story calls attention to how analytics can transform even the most traditional of companies. Indeed, the dairy company lacks modern ERP systems (although it is planning a state-of-the-art ERP implementation) and continues to process much of its inventory by hand. Yet when its CEO gave analytics a seat at the strategy table and operations executives subsequently began using analytics to make business decisions, the company did not merely move on from its geographical roots — Oberweis reinvented how it would compete.