The Herman Trend Alert
January 31, 2018
Solving the Shortage of Data Scientists
Each of us is endowed with certain talents and abilities. We feel good, when we are able to put those unique characteristics to work for the benefit of our employers. Sadly, the body of knowledge for the field of Data Science is expanding so fast that it is virtually "unknowable" by an individual. In fact, the last person who knew everything was born in the late 19th Century.
What is data science?
According to Marie Clark, Founder and Chief Innovation Officer at Ambient Intelligence, Inc., "Data Science is the transformation of data into actionable insights". Her goal is to prepare organizations and individuals to successfully compete in "the business and professional ecosystems of the 4th Industrial Revolution". However, business leaders are still relying on their intuition.
Making decisions based on intuition
A study published by Gartner reports that through 2020, "over 90 percent of business leaders will keep making decisions based on their intuition, rather than science, and thus, they will significantly underestimate risks." Though this conclusion makes sense, we find it depressing.
Making decisions based on data
The most successful companies are making decisions based on algorithms. Amazon, Netflix, and Spotify all make recommendations based on your consumption history with them. Why? Because algorithms work. But to create those algorithms well requires mastery of many areas of expertise.
Multiple domains to master
The reason data scientists are in such short supply is that we expect them to have business acumen and domain knowledge, know how to manage data, have computational/programming skills, and be able to use visualization, and be good communicators. Is it any wonder that there is a critical shortage of folks with all of these skills and abilities?
The solution: Data Science without data scientists
When business leaders make data science a cross functional, collaborative effort, they ensure organizational success and exponentially increase their odds of ground breaking innovation.
Unintended, yet wonderful consequences
This type of collaboration helps to reduce the time to market (or efficiency), plus it has a number of other advantages, including retaining tribal knowledge by retaining people, painlessly training people to be data science professionals, and teaching them how to collaborate. Not only that, but it improves morale, grows productivity, and builds employee loyalty.
Outstanding opportunity for organizations
What's next is for companies to inventory the talents their people possess, especially before they are planning a reduction in force. It is likely that they will find the combination of talents they will need, just not in one person. When companies invest in retraining their people for 4th Industrial Revolution jobs, rather than tossing them away, they are taking powerful steps towards creating employment brand ambassadors who will work very hard to help them be successful.
Special thanks to Marie Clark of Ambient Intelligence, Inc. for her work in helping companies transform their cultures and in training data science professionals. For more information, visit http://ambientintelligence.global/ . Hear Clark in action sometime in June on Dr. Nilda's Foresight Strategies Radio Show
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