Big data analytics can have a powerful impact on your business. From digital marketing intelligence and social network and relationship analysis to supply chain monitoring and fraud detection, today’s sophisticated applications offer new ways to understand and interact with virtually all dimensions of the global marketplace.

As I’ve said before, there is infinite value in the vast resources of exponential data, and already, companies that have started to leverage big data insights are gaining significant competitive advantage.

But, please, remember this one essential point:

The system is not the entire solution.

Technology alone will never cure all that ails your business. Instead, you need to engage with today’s complex tools, making them do what – exactly what — you NEED them to do. If you don’t, then you’re mixing good data with bad analytics . . . and that’s a recipe for disaster.

Have you heard of the example made famous by Harvard University professor Gary King?

As explained at SearchCIO, one of Prof. King’s favorite examples of “analytics gone wrong” concerns a big data project that set out to use Twitter feeds and other social media to predict the U.S. unemployment rate. As you might expect, this sentiment analysis by word count involved searching for words that pertained to unemployment, such as jobs, unemployment and classifieds and then looking for correlations between those terms and the monthly unemployment rate. At one point during the project, there was a spike in Tweets containing the relevant words. Were the researchers on to an exciting analytical finding?

No. According to King, the researchers simply hadn’t noticed Steve “Jobs” died.

In other words, the data was good, but the analytics were flawed.

And of course, your approach to effective analytics will need to continuously evolve, as well. Why? Because there’s no stopping the constant progress of technology and its impacts on the customer experience. We all listened to music on the radio until Internet radio came along; we rented videos at Blockbuster until Netflix. Technology continues to evolve to create a better user experience, and in turn that creates consumer needs and interactions –and data! — which didn’t exist before.

Earlier this month I profiled a handful of companies that are using data analytics to successfully find the insights needed to improve efficiencies, bolster compliance, cut costs, ramp up innovation and increase revenue growth. The business leaders at these companies know technology is the enabler of innovation, but can never be the entire solution.

Are you ready to launch a big data strategy so you can start putting analytics to work for you?