To paraphrase an old saying, if you torture data long enough, it'll tell you what you want to hear. And putting big data through that torture only lets us tell bigger lies. Marketing can justify crazy ad campaigns: "Sentiment analytics shows our latest campaign is actually a huge hit with the under-25-urban-vegan demo!" The supply chain team can use it to get more funding: "Our geolocation analysis shows if we invest in robotic warehouse automation, we'll reduce costs by 15%." Sales can explain why it missed its numbers: "We don't have an iOS app, and smartphone data shows that's what 87.4% of customers use. It's not our fault."

Don't get us wrong. The ability to collect and analyze data is a core IT value proposition. Companies such as Wal-Mart, FedEx, and Southwest Airlines gained strategic advantage by digging into their core business data long before it was labeled "big." And there's no question that more data is available than ever before, especially information from the Web and smart mobile devices. Our beef, though, is that most businesses aren't good at using the data they have now. What are the odds they'll get better at analysis by adding volumes without changing their strategies?

Our InformationWeek 2013 Big Data Survey shows that some companies are making progress. For example, most have built the required infrastructure and support various roles, in terms of primary data users; about one-third say they encourage wide access to information for business users. However, when it comes to data acquisition and use models, the wheels start to fall off. There are major gaps in data analysis, even for the most common types of information: transaction data, system logs, email, CRM, Web analytics.