During my drive back to Tucson from the Gartner Supply Chain conference in Palm Desert, CA I was provided with a few quiet hours to more deeply consider some of the accomplishments of those companies that made up The Gartner Supply Chain Top 25 . While those companies came from a range of industries, there were more than few common denominators regarding their business performance and supply chain focus.
First, and perhaps foremost (in my mind anyway) was their “outside in” demand driven focus, or as the CPG companies refer to it, from the shelf backwards. In particular, Amazon.com (#2 on the list behind Apple), was recognized for their ability to not only help shape the demand, but to deliver it virtually overnight. This demand driven focus on the ultimate consumer requires not only staggering amounts of data, but the analytic tools to make sense of it. Anyone who has purchased from Amazon knows that while you shop for what you think you want, Amazon is both subtly and overtly attempting to influence your purchasing decisions by exposing you to accessory options, package deals, and competitive alternatives they also offer. In addition, they are analyzing your purchase and product search choices to expose you to other things that you might be interested in. These aren’t random suggestions, and without knowing all of the details, you can be sure that with continued investments in the analytics, the precision of those suggestions will progress.
As I contemplated what "big data" has done for those that are capturing it and effectively analyzing it, I wonder what kind of computing horse power Amazon has applied to this effort. I do know that the costs for computing are continuing to drop as a bit of research led me to learn that a PC version of a Cray computer is now available on the market for mere $25,000. I wonder what I might do with that kind of horse power at home?
Perhaps I could distill the product reviews from across all of the store front sites to provide a more comprehensive picture of consumer satisfaction for the products I’m interested in. Still, I suspect that there is an area of opportunity that even Amazon has yet to tap. I speculate that Amazon is only analyzing the consumer habits of the purchases and inquires that flow through their store front.
What if all of the purchasing data could be analyzed for a given consumer or class of product and the factors that influenced those purchasing decisions? As with most statistics, the volume of data does contribute to providing a clearer picture especially when trying to segment the data into something more actionable.
Now we are probably talking about computing needs on the order of the department of defense, but the potential rewards are staggering. I believe what Amazon has already accomplished is reasonable proof of that fact. At a somewhat scary end of this spectrum, I can imagine logging into Amazon a few years from now and being presented with a list of the latest electronic and sports oriented toys that are perfectly matched to both my habits, budget, place of residence, and fashion style. Furthermore, perhaps these toys will be manufactured within miles of my home using 3D printers rather than the traditional manufacturing and distribution supply chain (If you are not familiar with 3D printing technology you need to check it out).
One thing is for certain, properly leveraged, big data has the potential of transforming our shopping experiences and the companies who best leverage it.
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