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Understanding analytical talent
Short takes...on analytics
A blog by Tom Davenport, Independent Senior Advisor, Deloitte Analytics
When it comes to big data strategies, a lack of analytical talent is constraining businesses from realizing their full potential. This is a key finding from “Benchmarking Analytical Talent,” a recent survey of analytical professionals by Talent Analytics Corp, in coordination with the International Institute for Analytics. Some key survey findings follow.
Analytics professionals are heavily degreed, but few are working with big data
The majority of those surveyed were Masters or Ph.D. level analytics professionals with a high level of job mobility (most in their current roles for less than a year). Familiar with conventional analytical tools (spreadsheets and commercial statistics programs), few of those surveyed were working yet with open-source or big data technologies.
The analytics field is populated with data generalists
Based on their self-reported time allocation across eleven different analytical activities, the analytical professionals surveyed were clustered into four groups: generalists, data preparation specialists, programmers and managers. Every participant indicated they did a little of each activity; however, managers mostly managed, programmers mostly programmed and data prep folks mostly worked on data acquisition and preparation. The generalists do all these activities, of course, but focus more on analysis, interpretation and presentation than other activities. Across all four categories, the least amount of time was spent on data mining and visualization.
“Quants” are creative, curious, and detail-oriented
The survey identified some widespread characteristics of analytical professionals. Quantitative analysts are often characterized as detail-oriented, rational and emotionally restrained. The study found that they are also intellectually curious and creative—whether they have “creative” educational degrees in fields like art or music, or a more traditional statistics background. The study suggests that IT professionals overall seek learning and growth over other job compensation factors and also suggests this is true of quantitative analysts as well.
The key take-away for your business? View analytical talent as individuals
If you are hiring or managing analytical professionals, you should not think of them as a monolithic entity. The widely-held belief that data scientists—with strong computational, analytical and business skills—are difficult to find in one person holds true. In fact, that same difficulty seems to apply to all analytical professionals. It’s unlikely that you’ll find someone who is equally good at all the tasks necessary to accomplish analytics successfully. It may even be that the terms “quantitative analyst” and “data scientist” are too broad to be useful.
The analytical professional is one of the most sought-after roles in the organization of the 21st Century. The key is to establish what that role means in practice and how to hire, manage and retain the most effective practitioners in ways that are of the highest value to the business.