The Pluses and Minuses of a Big Data Blind Spot

by   |   March 22, 2016 5:30 am   |   0 Comments

Bernard Marr

Bernard Marr

I have written many times about the exponential growth of big data, in jobs, applications, and scale. But in fact, there is one huge stumbling block that may limit big data’s growth and potential: math.

Too few adults in the Western world are proficient at basic mathematics. And by basic mathematics, I am not referring to advanced statistical analysis or algorithms. I am talking about basic, primary school numerical skills.

A study done by the UK government in 2003 that found that 47 percent of working-age adults in England lacked basic mathematics skills and, by 2011, that figure had risen to 49 percent! In the United States, a study found that only 16 percent of children of parents with a low level of education were deemed proficient in mathematics, and that the percentage barely eclipsed 50 percent for children of parents with college degrees.

When such a large percentage of the country’s population lacks basic mathematics skills, the current shortage of qualified data scientists begins to make sense. Clearly, people with insufficient math skills are not prepared to be data analysts.

But what about the people to whom data analysts report? Retail, sales, human resources, manufacturing, customer service – big data is sure to touch every corner of every industry within the next few years, even more than it has already. But a major stumbling block to implementing data-driven strategies may be explaining data-driven strategies to the employees on the ground who must implement them.

What Low Math Skills Mean to the Data Analyst

Obviously, math skills do matter. (In addition to improved economic prospects, many studies show that more advanced mathematics skills also lead to better health and wellness.) But as a data analyst, it’s certainly not your job to teach math to your audience.

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Instead, we must be aware that it’s highly likely that a large percentage of our audience – yes, including even C-level executives – may not have good basic maths skills. And that can change the way you approach a problem.

And that’s OK, because the fact is that big data is rarely about only the mathematics. But it will affect your job and how you approach it in several ways:

First and foremost, big data jobs will remain in high demand. Because advanced mathematics skills are indeed mandatory for jobs in big data, and a high percentage of the population is lacking in these skills, my basic numerical skills tell me that the demand for qualified candidates to fill big data-related positions is not likely to dry up any time soon.

The upshot of this is that those people who are qualified for data science positions will continue to find good paying work – and the good salaries that come along with these positions may motivate more individuals to study mathematics and develop the skills that are required for them to enter the big data workforce.

In addition, the fact that it’s likely that many of a data scientist’s co-workers will lack advanced math skills underscores the need for data scientists and data analysts also to have business experience. This will enable the data scientist to communicate better with those who don’t have the mathematics background to understand technical, math-based explanations. And it’s also possible that a data scientist’s supervisors and bosses may not have the necessary skill with numbers to be able to determine the right questions to ask.

Data is useless without analysis, and analysis is useless if you are attempting to answer the wrong questions. Understanding where the mathematics and the business case intersect is the invaluable ingredient for a winning data strategy.

Finally, the most important thing to remember about data is that it provides context, conveys meaning, and tells a story. The analyst, therefore, must excel at going beyond the numbers to tell the greater story. We must be excellent storytellers. From every bank of numbers or point plotted on a graph, we must be able to extrapolate meaning and relevance for our audience.

Because they may not have the required skills to do it for themselves.

Bernard Marr is a bestselling author, keynote speaker, strategic performance consultant, and analytics, KPI, and big data guru. In addition, he is a member of the Data Informed Board of Advisers. He helps companies to better manage, measure, report, and analyze performance. His leading-edge work with major companies, organizations, and governments across the globe makes him an acclaimed and award-winning keynote speaker, researcher, consultant, and teacher.

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