McKinsey predicts that the gap of professionals focused on large volumes of data will reach 1.5 million by 2018 in the United States alone
Big data projects tend to maintain their growth momentum. An IDC report points out that big data analytics tools will grow 2.5 times faster than spending on traditional business intelligence (BI). In addition, the cloud-based analytics solutions market will experience an even faster expansion, according to the consultancy.
High demand on one side tends to generate shortages on the other. It is estimated that, in the United States alone, there will be no fewer than 181,000 positions focused on information analysis, and an equally large volume for people capable of managing and interpreting data. The certainty is that there is not enough labor to meet this demand.
Globally, the number is even higher. Gartner points out that the demand for professionals oriented toward big data projects created 4.4 million jobs in 2015. The consultancy estimates that only one-third of this total was filled.
This is because these roles require skills that go beyond using dashboards to monitor the flow of information. It is essential to have the experience to correctly adjust what is relevant and define parameters to establish filters and algorithms. This knowledge is rarely achieved through mere professional certifications. Often, the requirement reaches master's or doctoral levels.
A Burtch Works survey published in 2013 identified that approximately nine out of ten big data professionals have at least a master's degree, considering only the number of disciplines they need to master. The list includes topics such as statistics, applied mathematics, research methodologies, and/or economics.
The McKinsey Global Institute predicts that the gap of professionals oriented toward initiatives focused on large volumes of data will reach 1.5 million specialists by 2018 in the United States alone.
As you can see, the opportunities and challenges are massive. Therefore, if you are looking for talent for your team, here are four alternative approaches to find, develop, and retain great professionals.
1. Choose people who know your company's business/industry
“I agree that the required skills are incredibly difficult to find,” comments Nick Heudecker, research director for information management at Gartner. “Many companies don't know what to look for when they start a project, let alone where to find these resources. There are also doubts about which problems to face and what tools will be needed for the task,” he adds.
2. Develop your best talent
Min Xiao, head of the field engineering team at software provider Tamr, mentions that he has interviewed about 500 people over the last five years. Of those, about 50 were hired. He agrees that it is very difficult to find the right professional for big data projects. Therefore, he bets on his own methods for these challenges.
“I look for people who are not superstars, but who have the potential to become one. I try to hire many young people who have never worked as data scientists, but who bring the characteristics to perform this task well. I also look for mid-level or senior professionals who have never worked in these roles either, but who have high potential to perform well in the position,” he explains.
In particular, his goal is to find people with a background in statistics, computer science, or a physics-focused degree. “First of all, you have to be very smart to graduate in physics. In addition, they are people trained in mathematics who, during their studies, acquire an interesting basic layer of computer science.”
3. Excel Ninjas
Jason Chavarry, analytics manager at The Hershey Company, looks for big data talent in other unusual places: advanced Microsoft Excel users. “It's a good starting point. People gain certain data handling skills and tend to be asked to help with tasks in other areas of the company,” he comments.
“If someone demonstrates the ability to handle one tool well, they will likely be able to perform tasks in others,” he points out, reinforcing that some projects require more sophisticated tools than others.
4. Nurture and grow talent
The shortage causes many companies to try to nurture talent within their own structures. Ashley Stirrup, CMO of integration provider Talend, states that his company has been achieving good results in big data projects through mentoring programs, where young professionals are paired with more experienced specialists.
“There is a lot of knowledge that can be bridged by connecting business professionals and those who know new technologies,” he reflects, noting that often one side does not see the potential of the tools while the other does not identify practical applications for them.
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