We talk incessantly about the importance of big data to drive better business decisions and outcomes. Marketers, managers, business owners, thought leaders -- just about everyone is spending inordinate amounts of time debating big data. Why? It's because companies engaging in data projects are doing better than those that are not. The proof is out there for everyone to see. For instance, a study by IDC finds that companies using diverse data sources, analytical tools, and different sets of metrics are "five times more likely to exceed expectations for their projects" than those that don't use these big data strategies.
Growing over the past few years, big data has been established by an obscene number of research, studies, and surveys as a holy grail for business success. But let me ask you this: Just because the data is there, does that mean we are using it correctly? Are businesses really benefiting from all that data they are painstakingly mining and trying to make sense of? Are they choosing the right data?
Which begs the question, can data steer us wrong?
Big data: the right signal or mere noise?
I believe the biggest challenge in the age of big data is that there is so much information that it's easy to make mistakes. One of the best examples of how data can lead us to totally out-of-context results comes from Harvard University professor Gary King.
This big data project, using Twitter feeds and other social media data, attempted to predict the unemployment rate in the U.S. With the help of keywords like "unemployment," "jobs," and "classifieds," the researchers drew a correlation between the total monthly mentions of those keywords on social channels, and the monthly employment rate. Then, the researchers noticed an incredible increase in the number of tweets having one particular keyword. There's a spike! Something must have shifted in society! Except, those tweets weren't talking about anything work related -- they were talking about the death of former Apple co-founder and CEO Steve Jobs.
That, my friends, pretty much sums up how precarious it can be to chase data without knowing if you're chasing the right data.
When you have a hammer, everything looks like a nail
The easiest and, at the same time, the most dangerous thing about data is it can be skewed and manipulated. With so much information -- especially unstructured data and numerous similar studies by known and unknown groups -- it's easy for us to take data and use it to prove what we want it to prove. So when you're using data sets that you think are important and relevant to build your strategies, but you aren't checking to see if they are well-aligned with your business objectives, you're inviting failure.
Yes, data can steer us wrong if we are not careful about how we use it. When we have so much data at our disposal and are able to benefit from it, there's an irrefutable temptation to use it to try and solve all business problems. What we often forget is that while data can present us with better insights, predictions, and decisions, it can be misleading and, at times, plain useless. We have to develop a better understanding of the power of big data. We have to be careful to make sure we use data to drive better results; we can't just use data to prove what we already believe.
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