2017: The Year of Big Data?

Will 2017 be the year of Big Data? Here are some trends we’ve been seeing that could make that prediction come true.

I love this time of year. The lingering glow of the holidays mixed with the promise of a new year filled with potential. Potential to learn, grow, and become a better person, business leader, parent, you name it.

There are seemingly endless possibilities. And that goes for the business world too.

But with all of these opportunities for improvement and growth, how do we determine which ones we should pursue? An increasing number of companies are looking to big data for the answer.

How Big Data Supports Business Growth: An Example

Look at Under Armour – a relative newcomer and underdog in the $80 billion sports apparel industry. On Friday, January 7, Kevin Plank, Under Armour CEO, delivered a keynote speech at the 2017 Consumer Electronics Show, where he noted Under Armour’s long-term strategy to leverage data and information technology to compete with Nike, whose $34.8 billion in estimated annual sales is 7 times larger than Under Armour’s $4.9 billion.

Plank has stated that health and diet related data gathered from users is crucial to Under Armour’s research and development and product segmentation. Plank has also talked about Under Armour’s acquired apps (MapMyFitness, Endomondo, and MyFitnessPal), and how data can lead to brand differentiation.

All this begs the question: Will data be the “stone” that Under Armour needs to slay their Goliath? I hope so. But, only time will tell.

Unbiased Models: Most Urgent Challenge for Big Data

Many lessons can be learned from the most recent U.S. presidential election, not the least of which is that biased models cannot make accurate predictions.

Robert Hetu, research director at Gartner, astutely noted in a Nov. 10th blog post Lessons From The U.S. Election On Big Data And Algorithms, the criticism heaped on big data after the failure to correctly predict the most recent U.S. presidential election is erroneous. He goes on to state that the data wasn’t the fail point, “[t]he real issue is failure to build unbiased models that will identify trends that do not fit neatly into our present understanding.”

Some of the most brilliant data scientists in the world built models and analyzed the results of numerous algorithms to predict the election. If they can fall victim to unconscious biases, how can the rest of us hope to overcome this challenge? Hetu stresses that we should go “where the data leads” regardless if the outcome is what we were expecting or not. As challenging as that sounds, we can take the first step by establishing an organizational culture and environment that is open to exploring new ideas and challenging established ways of thought.

Getting people to be open to new ideas is only one step in the process. For companies to gain the full benefits from big data analysis, they will also need to develop smarter algorithms to automate data responses and enhance their analysis.

The Rise of the Chief Data Officer

Another data related trend we’re likely to see in 2017 is the growing number of companies looking to leverage a new leadership role: the chief data officer.

In 2015, Gartner estimated that 25 percent of large global organizations had already hired a CDO, and by 2019 Gartner expects that number to reach 90 percent.

Given the ever increasing focus on data-driven business decisions, it was only a matter of time before data leaders were given a seat at the C-suite table. But the question remains as to what this corporate shift will mean for organizations?

Ted Friedman, research vice president at Gartner, and summit chair for the Gartner Data & Analytics Summits suggests that “[a]s silos are broken down, and professionals in this area work in cross-functional teams more than ever, it was clear that coverage of both data and analytics in one place was needed”

These new leaders have a unique opportunity to transform organizations through a clear strategy to overcome “data science skills gap, modernize data infrastructure and analytic platforms, govern and take advantage of diverse information sources, and spearhead data and analytic projects that have high-value payback,” said Friedman.

While there is no denying the many benefits that having a C-level presence will afford, the real challenge for these new data leaders will be to derive meaning and value from the myriad of data at their fingertips. Important to consider: internal (budgets, governance requirements, culture, etc.) and external constraints (market forces, competition, and social pressures).

Looking Ahead

Back to our original question: Will 2017 be the year of big data? Let me finish building my unbiased analytical model and get back to you. Until then, happy analyzing.

What are your big data predictions for 2017?