2013 doesn't have a moniker yet, so I'm dubbing it the Year of Big-Data. Big-data is saturating business news releases, is the topic of conventions and trade shows, and will turn the security and IT business on its ear, if the hype is accurate.
I don't mean to imply the hype isn't well deserved, and big-data is no doubt influencing many things I do day to day. It still may be too early to ask this question, but I'm going to anyway: If the data is so good, why are so many business decisions so bad?
Here's one example of big-data promotion, chock full of "majors" and "dramatics":
RSA, The Security Division of EMC Corporation (NYSE: EMC), today released a Security Brief asserting that Big Data will be a driver for major change across the security industry and will fuel intelligence-driven security models. Big Data is expected to dramatically alter almost every discipline within information security.
The new Brief predicts Big Data analytics will likely have market-changing impact on most product categories in the information security sector by 2015, including SIEM, network monitoring, user authentication and authorization, identity management, fraud detection, governance, risk and compliance systems.
Big-data is also thought to be the salvation of the supply chain. Real-time demand information and social media networking are supposed to give vendors the best possible information for forecasting. Yet, the tech industry -- which I'd expect to be early adopters of big-data -- missed the mark on fourth quarter PC demand; hasn't come up with any groundbreaking consumer technology; and hasn't been the salvation of the enterprise market yet. Both Hewlett-Packard and Dell are staking a claim in the data management/data security markets.
Toward the end of last year, IHS reported that semiconductor supplies in the channel were growing, in part because of deficient forecasting:
The result on the whole is that chip suppliers aren't running their manufacturing operations optimally, and also are manufacturing products solely based on historical demand. In some instances, projected demand also does not materialize, adding to the already slow-moving inventory pile.
Historical demand is a better metric than forecasting, I suppose, but only when demand cycles are following historic norms. That wasn't the case throughout most of 2012.
So I've been wondering whether Apple's decision to cut component orders is a signal that all of this data collection is working, or if it isn't. Apple reportedly cut orders because of softness in iPhone 5 demand. One could argue Apple's ahead of the curve by cutting orders rather than shipments. Then again, it could have anticipated a slowdown after the holiday season, and seen that competitors' products were selling pretty well.
I think the supply chain will learn more about how well data is being used as fourth quarter earnings get released. And maybe by the end of this year, we'll see evidence that big-data is making a difference. What do you think?