WHAT HAVE THE CERN laboratory, big data and a bowl of soup got in common? In an occasional new series, The INQUIRER looks at how the concepts of business-to-business technology are being rolled out in everyday situations.
In this particular instance, we talk to EAT chief financial officer Strahan Wilson about how the firm uses business intelligence (BI) to ensure that everyone gets what they came for.
EAT, for the uninitiated, is a chain of food-to-go sandwich shops. The company opened in 1996, and has expanded in and around London with an emphasis on fresh produce.
The firm is currently running a pilot with Blue Yonder, a predictive analytics software company founded by ex-CERN researcher professor Michael Feindt.
EAT has been using Blue Yonder to analyse supply and demand and ensure that, when you walk in on your lunch break, you can find exactly what you expect, with no empty shelves and no waste.
Wilson explained that one of the key requirements of any BI solution was that the company didn't need to know how it worked. A partnership and a system-as-a-service option allowed EAT to keep making food while Blue Yonder took care of the technical stuff.
"The skills for predictive forecasting are very specific and very technical. We lacked the skills in house to build the model and, even if we paid someone to build it, we don't have the skills to maintain it," he said.
"But not only that, we don't have the skills to manage someone with those skills because they are so specific. So for a business of our size, it was important to be able to outsource the software and the ability to manage that tool.
"With a group of people who come mainly from CERN and have been on the cutting edge of theoretical physics, they are more than capable of building a model and maintaining it.
"But also because of who they are, they are able to recruit the best talent and motivate and maintain in a way that we just couldn't."
The result of the trial has already shown a 14 percent waste reduction in the pilot stores. Blue Yonder takes into account the existing sales data from EAT, and adds environmental factors such as public holidays, the weather and a little bit of old-fashioned whimsy to give a much more reliable forecast of which shops need which sandwiches and in what quantity.
"We gave them two years of our data, left them for six months, came back to them and asked them to show their predictions compared to our actual results in that period. The result they came back with showed this 14 percent reduction in waste," said Wilson.
But it doesn't stop with simple supply and demand of existing products. Once the data is in place, and already paying for itself, other departments can reap the benefits.
"I'm desperately trying to keep a lid on the excitement that this is building in the business. Everyone can see the possibilities and I'm just begging people to let me get to July when we go full rollout before we start to look at just how much it can actually do," Wilson enthused.
"It can even guide our product development teams in making products that are more profitable for the business, and of course more appealing for the customer.
"But the other aspect is labour scheduling. There are two things a customer wants when they come into our stores: to find the product they want and be served quickly. And if we know our anticipated demand, we can schedule the labour to meet that demand much more accurately."
Perhaps the biggest surprise of all, however, is the level of pay-off that a good predictive analytics suite can make to a chain like EAT. The full rollout is planned for July, and Wilson made a staggering prediction.
"Assuming we see the same result in our full rollout that we're currently seeing in our proof-of-concept stores, we can expect a four-month payback on our total spend," he said.
And for once, The INQUIRER has no witty retort. That's a phenomenal return on investment and a good demonstration of how big data analytics is working in the real world to make sure that, if you want ham, brie and cranberry, that's what you'll get. µ
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