The Biggest Mistake Companies Make in Big Data

The Biggest Mistake Companies Make in Big Data

How many times have you heard someone comment, “the data says this…” in support of their argument? It’s a common enough phrase, pre-dating the rise of big data, but what many companies don’t realize is that it can be detrimental to their business to rely on such a phrase.

IBM reports that 2.5 quintillion bytes of data are created every day. That’s a mind-blowing amount of data, but even more astonishing is the fact that 90% of all existing data has been created in the last two years. But at the end of the day, data is just data. It tells us what is and nothing more. Big Data may be a buzzword in the business world, but the smartest leaders know it’s not the ultimate resolution to all their problems. Yes, big data can be extremely powerful, but true business intelligence goes beyond the hype. The biggest mistake companies make in big data is in giving it too much power.

The Goals of Big Data

A recent Gartner survey of IT and business leaders revealed the top three goals of big data are enhanced customer experience, optimized process efficiency, and more targeted marketing initiatives.

As consumer habits evolve with the growing digitization of the marketplace, customer experience becomes ever more influential in the success or demise of a company’s brand. Targeted marketing goes hand in hand with this notion, as companies recognize the need to cater to individual customers and personalize every step of the customer journey from brand awareness to buying decision. As these initiatives grow in complexity, process efficiency is vital in maintaining consistency, timeliness and cost-effectiveness.

Big data certainly plays an instrumental role in reaching those objectives, and companies know it; 75% are currently investing – or planning to invest – in big data in the short term future. Interestingly, the Gartner survey also reports that big data projects are being spearheaded by an increasing number business unit heads, an equal number, in fact, to those being initiated by CIOs. It’s testament to the realization that business leaders need to take a more proactive role in IT as it relates to the core elements of the business.

Understanding the Limitations of Big Data

Chances are you’ve heard the phrase, “correlation does not imply causation” an annoying number of times in your career. Yet it’s still one of the easiest mistakes to fall into, especially in regards to big data, where the simultaneous complexity and subtlety of information makes it highly tempting to draw conclusions of causation based upon sophisticated patterns in the data.

It’s human nature to seek out root causes, but it frequently prevents us from seeing the big picture. Correlation is intriguing when identifying trends, but it will never be enough by itself to make effective business decisions. That’s because all that correlation tells us is what is, not why it is. It’s simply a simultaneous occurrence of two or more factors, but it doesn’t reveal if one of those factors leads to the other or vice versa.

As such, big data, as big as the hype is across industries, is not a cure-all. It reveals correlated patterns, but it doesn’t not provide insight. It identifies trends, but it cannot uncover gaps. It can suggest what’s broken, but it cannot deliver a solution.

Asking the Right Questions

Big data is often the fast track to analysis paralysis. With so many thousands of data points, you could be left connecting the dots forever without ever reaching a valuable conclusion. Thus, big data is only as good as the questions you’re asking. Every big data initiative must be aligned with a company’s business goals and objectives; that alignment alone will set the foundation for the types of questions your business needs answering.

The trickiest part of data analysis is almost always the fact that you won’t know if you’re asking the right questions until you get the answers. So there has to be a regular feedback loop that helps reinforce the framework of queries. It’s critical to understand why you’re asking the questions you’re asking and how they will support your business goals. Furthermore, it’s vital to ensure that the questions you’re asking cover all your bases; be aware of any gaps, otherwise you run the risk of missing the big picture.

Hiring the Best Big Data Talent

We come to the conclusion that big data by itself can’t do much alone, and therefore should never be given the power to drive business decisions. No matter how many algorithms a company puts in place to automate the work of big data, you still need big data scientists and analysts to generate meaningful queries and make accurate interpretations. Big data can be a powerful informer and influencer of business decisions – but it should never be the autopilot driver. That’s what top talent is for.

If you’re looking to make more informed decision in your business and need a data scientist or analyst on your team, let us know. We can help you make the right connections.

For an example of our work in big data, check out our Big Data Solutions success story.

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