Shortage of Skilled Data Scientist
Businesses are increasingly seeking ways to take advantage of data science and AI, in order to build an enterprise-wide digital culture. The trouble is, there continues to be an acute shortage of trained data scientists. According to the research firm QuantHub, there are 250,000 more job openings for data scientists in the U.S. than there are data scientists to fill them. Nearly 40% of surveyed companies named data science as the most difficult skill set to fill.
There are currently 250,000 more job openings for data scientists in the U.S. than there are data scientists to fill them.
Elevate the Role of Operational Analyst
In the early days of AI, data scientists were solely in charge of building predictive models. While data scientists are still an important part of the AI process, they can’t – and shouldn’t – do it all. The best way to address the skills gap quickly and cost effectively is by elevating the role of operational analysts. Increasingly intuitive AI platforms are helping analysts inject important business insights directly into existing enterprise applications, such as Salesforce and Tableau.
That ensures that analysts can consider the business under different scenarios and conditions, greatly improving discussions with business owners about appropriate resourcing to drive KPI improvements. An increasing number of companies have already given operational analysts responsibilities that go beyond. according to a study by Ventana Research, 66% of analysts in major companies don’t just discover what happened and why – instead they also prescribe what should be done.
Data scientists are an important part of the AI process, but they can’t – and shouldn’t – do it all.
Add Value from Every Angle
CDOs are a key player in helping their organizations make the move from siloed work to interdisciplinary collaboration, where analysts in sales, marketing, finance, and operations work together to ensure a diversity of perspectives and prescribe necessary adjustments before they become problems. Every analyst and member of the business team must be given the tools to work in parallel and add value to AI without waiting for or blocking others. Elevating the role of analysts will help CDOs achieve what should always be the goal of any data initiative – sustained business impact and ROI.
Give more people a say in the creation and adjustment of AI. One size does not fit all. Find new ways to promote collaboration across business groups, IT and data science teams.
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