Reshaping Skillsets in the Age of AnalyticsReshaping Skillsets in the Age of Analytics
Automation and greater involvement by business managers with the analytics team are just a couple of the changes that are in store for data science.
March 15, 2018
Data analytics is entering a new era, propelled by two trends in data science. First, business leaders are more frequently being moved into data roles, fueling the emergence of citizen data scientists. Second, technologies are making certain data science tasks – particularly data mining – more efficient, freeing data scientists to focus on insights. As these two trends converge, data science teams need to reshape their skillsets to reach their full potential today.
Business users increasingly charged with analytics roles
While the majority of data science leaders have years of experience in analytics, math and statistics, I have been working with many companies that are placing people from the business side (like operations or sales) into insights leadership roles. Overall, this is a smart strategy, providing data teams with better direction as to what the business really needs. It also allows the business side to understand exactly how data analysis works. With this information, they can better understand which analysis requests are most time consuming and how jobs are prioritized. However, this convergence of teams requires a new approach to data analytics.
Communication is the most fundamental skill in analytics
It may sound simple, but communication is the key to making this convergence a success. If I had to choose the single most important skill for data leaders on my team, it would be strong communication. Upcoming data leaders need to have a deep understanding of the business goals and a good relationship with department leaders, and communication is the only way to achieve these objectives. Data science leaders that align their priorities with the eventual consumer of their insights – the business team – are seen as trusted partners. This gives them an edge in gaining a seat at the strategy table and securing funding for additional resources.
Insights – not data – are the future of data science
Gartner reports that more than 40 percent of data science tasks will be automated by 2020. However, that does not mean a decline in the role or number of data scientists. In fact, Gartner also anticipates the usage of data and analytics will surge. With this shift, though, the traditional role of the data scientist will evolve significantly over the next five years.
As artificial intelligence starts taking on more of the repetitive data cleansing and mining tasks, data teams stand to benefit greatly. Their most valuable asset – the mind of the data scientist – can more easily focus on turning data into insights faster. Then, these leaders can more proactively deliver insights to the business. That is why communication is an increasingly critical skill. Future data scientists will be empowered to spend their time communicating insights and driving value, unencumbered by the tedious tasks that previously consumed their time.
Education gives an early edge to business and data leaders
Universities must take heed of this shift and educate future business and data leaders accordingly. Those that integrate the latest business technologies into their curricula give their students an edge – providing the hands-on experience employers demand and allowing them to tangibly experience the types of insights and decisions they will develop in their careers. I have worked closely with schools, including the University of Notre Dame, Western Michigan University and The Ohio State University, to provide access to Prevedere’s software and to incorporate our methodology into class material. Notre Dame’s approach is particularly notable. Almost every student in the college of business – from marketing and management to accounting and finance – uses Prevedere. That means virtually every student uses analytics – bridging the gap between business leaders and data scientists for the future era of executives.
We are now in an age where computing power can truly analyze and monitor the entire globe’s data to deliver some truly remarkable insights. Data scientists and business leaders that embrace and reshape their skillsets for the fundamental changes that these insights can power will drive the future of tomorrow’s most successful businesses.
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