Imagine one day you wake up with life-changing superpowers.

You can scale any building in a matter of seconds. You possess superhuman strength, speed and agility. You have a sixth-sense that alerts you to potential danger.

Would you choose to use these powers for the greater good or suppress your unique abilities because they overwhelm you?

Data scientists, people with deep educational backgrounds and applied business experience, are the superheroes of the big-data world. But like many fictional superheroes, they spend only a fraction of their days doing work that taps their exceptional abilities.

But what if that weren't the case? What if Peter Parker or Clark Kent didn’t have day jobs – and could focus 100 percent of their amazing abilities on saving the world?

Huge Demand

Big-data superheroes are in high demand. A widely cited 2011 report by McKinsey & Co. warns that by 2018 the US will have a shortage of up to 190,000 data scientists. In addition, it will need still another 1.5 million managers and analysts with data science skills to fill about 4 million big-data-related jobs.

While major universities and analytics businesses are working hard to produce more data scientists, educating these professionals takes time. With a limited number of data scientists and endless problems to be solved, the ones we have desperately need to be freed of basic tasks.

But the reality is that many of these superheroes spend 90 percent of their time solving repetitive data cleansing tasks, over and over again. They should be focused on driving disruptive business value, with their superpowers applied to problems that have never been solved before.

So how do we free them to do what they do best?

By empowering anybody – business analysts and users alike – to analyze and forecast with business data, without delay and on their own.

Learning Opportunities

This is what the democratization of advanced analytics and data science is really about. Business analysts take over day-to-day operations for data blending and modeling. Data scientists can then make the coding hacks only where necessary, instead of all the time. In this way, data scientists will become the next generation of superheroes – and business analysts will become their sidekicks, just as Robin and Alfred are to Batman.

Capitalizing on Talent

If you possess powers that others don’t, then channel those skills to drive innovative business change. That's how you create significant business value.

Otherwise, you’re Peter Parker taking photographs for The Daily Bugle when you could be protecting the city from a Green Goblin attack.

So how can we enable data scientists to make the most of their powers?

  1. Move table stakes to business analysts. Business analysts need tools that help them with the day-to-day business problems, like blending data and handling standard predictive models.
  2. Share strategies internally. Once a data scientist solves a new problem, he or she should hand off that solution to the data-driven business analysts and let them repeat that process. About 99 percent of the problems can be solved by data-driven business analysts, leaving data scientists to focus on the 1 percent of problems that truly move businesses forward. Standards and a common platform can support this collaboration.
  3. Create an analytics roadmap and develop a forward-thinking culture. It’s important to understand how to infuse analytics throughout your business. Too often, companies are given the gift of prediction but fail to act upon it because they don’t trust the analysis. To build trust in these forward-thinking concepts, companies should start with smaller projects to help learn the process. The more teams learn to trust the predictions, the more they will effect true bottom-line results.
  4. Don’t underestimate tools or the abilities of data scientists. Data scientists need tools that allow them to be productive, experiment and have fast-to-fail techniques, so they can try new innovative use cases, solving hard problems that have never been solved before and are hugely impactful for the business.

Make your choice.

Labor over Excel spreadsheets and charts, or become the big-data hero you should be – that you deserve to be – by focusing on areas of real impact.

That means putting your company on the growth track by reducing customer churn. For biotech, what if you could predict Alzheimer’s in patients? Or for a country struggling with jobs, what if you could seriously reduce its unemployment rate? The opportunities are endless, but only if you exercise your superhuman skills.

Creative Commons Creative Commons Attribution 2.0 Generic LicenseTitle image by istolethetv.