Imagine this–you walk into Costco, head over to the produce section, and grab a loaf of Kirkland Signature Split Top Bread. Then, you see some peanut butter and jelly and pick those up as well. You then make your way to the register, check out and leave. It’s a pretty simple process that millions of people go through regularly; but have you ever stopped to think about what actually went into getting that bread on the shelves? Why it was so easy to find those items near each other?
At IBM Insight2015 (#ibminsight) I had to the opportunity to sit in on a presentation from Kyle Wierenga, Costco Manager of Advanced Analytics. During his presentation Kyle shared a lot of factors that contribute to getting that loaf of bread, and coincidentally your peanut butter and jam, to the shelves at the right time.
When you’re managing thousands of stores across the world, providing rock bottom pricing, and getting all those products to the right place at the right time, it takes big data to make that happen. Costco, like many other businesses, needs to forecast months in advance how much of which products to stock their shelves. If they get it wrong, they might overstock and have Christmas trees on the shelves into early spring. And Costco doesn’t lower their prices to clear inventory, so it’s a precarious situation. This is why they turn to analytical data to get the forecasting right.
So what contributes to knowing when to get the bread, jelly, and peanut butter on the shelves? There are a lot of factors that they’re using to solve that question. It could involve the time of year, the average weather in the area, all the way to trending social analytics. Likewise, by using affinity analytics they can understand that when people buy bread, they might also want to purchase that peanut butter and jelly. Seems like common sense, but who knows when the next trend will make peanut butter and marshmallow fluff a hot snack again.
Suffice it to say, I found Kyle’s presentation very interesting, but it got me thinking about other forms of data used throughout a supply chain–what about shipping? When you see those 18 wheelers moving down the highway, you might look at it as a traffic issue or think of the 1978 film Convoy. The reality is, shipping is a highly orchestrated movement of products that involves its own form of big data called EDI.
EDI, or electronic data interchange, is the transfer of structured data between two organizations or “trading partners” using a set of standards that define common information formats to accommodate the exchange. It’s about managing big data, critical data in multiple message formats, different communication protocols and changing requirements and customer mandates.
With Rocket Software technology, our customers have the ability to take multiple digital message formats and match them to the right communication protocol with the right customer, partner or supplier – easily and efficiently. To learn more about what Rocket Software is doing with EDI, I encourage you to check out Rocket TRUedx to learn more.
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