thumbnail-1Big data analytics is changing every industry. It’s a hard trend, and it’s spread is inevitable – the question is: how are you succeeding or failing at positioning your business to take advantage of it?

Let’s put it in simple terms. Big data refers to the use of very large amounts of raw data by businesses, ideally to create products and services that meet customer needs better than ever before.

Big data is amazing because it allows us to extract trends from giant data sets. For example, with big data analytics, we can find things that remain invisible when we look at 100 people or 1,000 people but then become glaringly evident when we look at millions of people or millions of data sets. This improvement in insight and scale helps change the recognized data patterns and opens the door to new growth.

A lot of people admire how Google, Amazon, and Facebook have shoved competitors to the side with their powerful models that are driven by their ability to collect and exploit data. And for good reason. Research shows that companies that integrate big data and analytics into their organizations demonstrate productivity rates and profitability that are 5%-6% higher than those of their competitors.

Keeping all that good stuff in mind, let’s be careful to distinguish the hype about big data (“It will solve everything!”) from the truth.

The Challenge of Big Data

How do you convert raw information into knowledge that can actually lead to significant action? Data on its own does nothing.

I won’t lie. At the moment, when it comes to big data, literacy at the C-suite level has been lacking. Recall that most big data tools are designed for data scientists, not managers. Which is why you need to choose the tools and services that ensure your leaders can easily access and understand the data. But in the long term, companies should have a plan to increase big data literacy across the board.

And once you’ve collected the data, what then? The days of rounding up some figures and throwing them on a colorful graph are over. A giant gap exists between what businesses actually need to make great decisions and what big data technology by itself can enable companies to do. Companies have to interpret the data in thoughtful, strategic ways so that it can be leveraged to move business forward.

It isn’t enough to just collect and aggregate. Your organization needs to have a plan for integrating and actually acting on the bounty of information that big data brings.

Getting the Big Data Gold: Go for the Need

Perhaps the biggest mistake that companies make with big data is… what’s the technical term I’m searching for? Well, they basically just stare at the datasource and then kind of ask what it can do for them.

You as the leader must decide on a desired business impact. What’s the endgame? Data sourcing should be the final, not the first, consideration in your game plan. Otherwise, you may be staring blankly for a long time.

Begin by asking what data you would need in order to make better decisions and improve service for your clients and customers.

For example, Kabbage, a startup that supplies working capital to online business asked itself what data it required in order to make faster, better decisions. It realized it needed data about the loan worthiness of businesses, and that it could get that data from unconventional sources. So now Kabbage accelerates the time it takes for it to underwrite loans by asking merchants to share their Facebook interactions. This data then gets processed and interpreted, and it allows Kabbage to make quick decisions about what online businesses are worth their investment.

In Conclusion

A lot of factors go into creating a successful plan for using big data to take your business to the next level. And it all comes down to how much work you’re willing to do, because big data is a hard trend. It isn’t going anywhere. It has changed the playing field forever. But the data is only as useful as your strategy — and ability — to leverage it.

Sooner or later you’re going to have to jump into the pool of big data. Will you sink or swim?

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