I stumbled upon this gem today on Harvard Business Review's site (http://blogs.hbr.org/cs/2012/09/will_big_data_kill_all_but_the.html?cm_mmc=SocialHub-_-3271-_--_-6807223796479021584). The article focuses on my area of expertise, business intelligence and data mining. To be very blunt it's a great time to be a math person. To be honest, I think the author is making a lot of fuss about something that is not particularly fuss worthy, the commenter Simon Karpen actually had the best observation, in my opinion, which was basically that if a retailer does nothing but sell stuff, it will lose to Amazon. My employer and a previous employer both use extensive data mining to match customers to products and help drive bigger basket sizes/orders/etc. Ultimately however, if a retailer does not provide something besides the widget in my basket, I am probably just going to order it off of Amazon, unless I need it now.
All of those key tags and club cards that every single retailer wants you to sign up for is basically a way to suck data into a database for mining. This mining goes beyond circulars and emails and starts to get into individualized coupons and other specials. For example, if a customer is consistently hovering around a $20 basket, most retailers will start hitting them with $5 off of $25 in an effort to try to force the basket size to drift up and stabilize at a new higher equilibrium point. These approaches to marketing eliminate the proverbial cherry picker and also help minimize cannibalization. Why give $5 off of $25 to the shopper that consistently hits a $25 basket when you could give them $10 off of $40?
The author seems to believe that "big data" will give big retailers even bigger advantages over small retailers and ultimately squash them. While small retailers can not directly compete with big retailers, since by the nature of the size difference the data would be more robust for large retailers, they can be fast followers in many cases. Since retail margins are very narrow, if the smaller (and usually more agile) little guys can successfully play the role of the fast follower they can emulate or recreate the insights provided by the big retailers data bases without having to foot the bill for the data gathering or analyzing. Furthermore, as stated above, if the only differentiation is price, then the lowest price merchant will usually win the business in the end anyway. Smaller retailers already have trouble competing on price anyway so it's not like the insights from data will widen the gulf between the huge retailers and the small retailers or add new axes upon which to compete.
What data can not do however is provide a different customer experience, and this is where smaller retailers can still attack the big guys, especially for goods that are less price driven. While Walmart, Krogers, Target, et al may be able to give me a $5 off of $25 coupon to entice me to buy more their staff can not provide the same level of service that smaller niche retailers can. Your local tailor can take the time to help you pick out a matching tie for your new shirt, the staff at Whole Foods will drop whatever they are doing to help you find exactly what you are looking for, the local bicycle shop will take the time to fit you for a bike and help you navigate the options, and so on. These are the kinds of user experience differentiators that larger and by consequence, more austere and impersonal retailers can not provide.
Take Away For Entrepreneurs:
This is a little bit of a stretch to tie into start ups, since a new company most likely will not have access to "big data" however, it does provide some perspective. The first is that the article touches upon the power of data and data-mining. Considering we just discussed Lean Start Up and the need to contemplate "pivot, perish, or persevere" being able to understand and utilize data effectively is invaluable. This article reinforces that notion, but from a different angle, as these firms are not necessarily facing "P-P-P". However the lesson to use data to add insights and solve problems is still here. The second lesson from the article is more so an awareness of the threat/advantage that large firms possess in their ability to acquire and mine enormous data sets. A start up, by its very nature, can not compete along that axis as the resources and infrastructure will just not be in place. This places an even greater need for sufficient differentiation from established firms, and while this article focuses on retail it is not a stretch to take this lesson into other markets and industries. It is this lesson that is most important to take away from the article. Since the course focuses on innovation, and difficult to copy strategies, value propositions, etc are all part and parcel to innovation and by extension differentiation, this article just reinforced how important these qualities are for start ups trying to get off the ground.
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