Ever have an idea for a new product so good it could hurt your business?
It may seem far-fetched, but that's what happened to Wawa, the popular convenience store chain that operates more than 750 locations in six East Coast states.
The company had introduced a new flatbread breakfast sandwich. Everybody in the company was excited about it. Sales were taking off and it looked like a clear winner. Then Wawa killed it.
Because it was too good. It sold so well that it undercut products Wawa had already been selling. Specifically, it was cannibalizing sales from other, higher-margin Wawa products. More flatbread sandwich sales ultimately meant less money for the company. So it had to go.
The company behind Wawa's flatbread sandwich decision was Applied Predictive Technologies. APT's software takes in information from client companies — everything from sales data to local weather patterns — and produces custom reports to understand trends, improve efficiency and hit sales targets.
"In using big data and an understanding of trends, it was valuable to see not just the primary effects but also the secondary," Anthony Bruce, chief executive at APT, told CNBC. "What you need to do is find observations where what you've done is having halo effects, not cannibalization effects."
That's how APT's data-driven platform helped Wawa: It wasn't just showing what the flatbread sandwiches generated in sales, but how it affected the overall bottom line for the company. Data analytics, when applied correctly, can help filter out the "noise" from test results. Starbucks' global strategy officer cited APT as the "best source of industry comp intelligence" on a recent company earnings call.
APT is also the company behind McDonald's recent move to sell breakfast foods all day. The fast-food giant renewed its contract with APT in 2016 to gear up new food offerings and optimize menus. APT's "Test & Learn" software costs about $1 million per year for a typical three-year license, according to CFO Magazine.
See a full interview of APT's Anthony Bruce by CNBC's Eric Chemi here: