From visibility to visualization

For as far back as there have been businesses, we have tried to get visibility – a better picture of what’s going on in our operations, or our competitors, that would give us one up on the other guy. Way back in 1815, the Rothschild’s scored a financial coup when their network of couriers delivered the news of Napoleon’s defeat to their offices in London 48 hours before the official dispatch to the British Cabinet. Legend has it that they made better use of the technology of the day – in this case, carrier pigeons – than their rivals. It gives you a whole different perspective on today’s controversy over fast trading on Wall Street.

We’ve been talking about supply chain visibility and dashboards in distribution and transportation ever since the visibility and event management solutions that emerged during the Internet boom. Based on the emails now showing up in my inbox, a session I attended at CSCMP last November, and a presentation on Big Data by Sam Madden, director of MIT’s Big Data Initiative, at last week’s Crossroads 2014 hosted by the MIT Center for Transportation & Logistics, I think we’re moving from visibility to visualization. It’s sort of like moving from those green screens we all worked with in the 80’s and early 90’s to getting images with a graphical user interface.

Madden talked about the realization that there is now data associated with almost everything we do. As an example, his team populated a map of the globe with all of the tweets posted on Twitter for a one month period, including the location of the Twitter account. It was in the neighborhood of 100 million tweets. The tweets were searchable – for instance, type the words Good morning into the search box and all of the tweets appeared in one box while the map lit up with origination of the tweets.

For starts, this was very cool to watch. As I was watching Madden demonstrate the fun you could have with Big Data, I thought of the challenge of omni-channel retailing. A retailer like Macy’s is filling orders from its network of distribution centers, hundreds of retail stores and drop shipping from suppliers’ locations. When an order comes in that needs to be filled, it needs to make decisions about the best location from which to ship the merchandise. Or, when Macy’s wants to replenish its stores, it has to figure out the best way to allocate its inventory. Or, when an item is being returned, it has to figure out the best place to position it in the network for the most profitable resale.

Wouldn’t it be useful if the retailer could take an item – say men’s blue golf shirts – and quickly get a visual representation of where they’re all located, and in what quantities, across the network. If I was doing replenishment or routing a return, wouldn’t it be great if I could see a visual representation of where blue golf shirts are selling best in order to make decisions about how to allocate the inventory?

These are powerful tools that appear to give us capabilities we’ve been talking about for years. Of course, there’s always carrier pigeons.