Why you should retrain your employees to become your data scientists

Why you should retrain your employees to become your data scientists

Why you should retrain your employees to become your data scientists

data science has become a hot topic this year, as data-driven campaigns help employees across the board perform better. From marketers to salespeople to consultants, data can enhance performance and help overall company productivity. Businesses agree that data can help, but one issue starting to arise is a talent gap when it comes to data scientists.

International Data Corporation (IDC) predicts that by 2018, businesses in the US will need 181,000 people with deep analytical skills and 5x that number of people with data management and interpretation skills. As of now, however, there are not enough skilled data scientists to meet that need. So how can companies find candidates that can fill these positions? To start, companies need to look internally and begin to realize the benefits of retraining their own staff to become data scientists.

Employees appreciate learning and development. Seven out of 10 employees say that training and development opportunities impact their decision to stay at a company. And 40% of employees who are given poor job training leave their positions within the first year. Without professional growth, an employee is more likely to be unhappy and leave, which means training and development must be a top priority.

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A few years back we saw a “coding craze”, where many companies trained their employees to become basic programmers. Companies had everyone, top to bottom, learn to code in order to enhance technical skills across the board and increase productivity. One company, FreeCause, performed a “Codinization Project” that brought together technical and non-technical employees to have everyone in the company learn to code.

It’s safe to say this idea worked and got hundreds of employees across all types of industries to learn to code. Now, what if the same strategy was applied to address the widening talent gap in data science?

Wharton management professor Peter Cappelli took a look at why some companies hire new employees and while others retrain existing employees. Cappelli looked at the impact each had on social capital, or relationships within a workplace and how well employees work together.

 



Data Science Congress 2017

5
Jun
2017
Data Science Congress 2017

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AI Paris

6
Jun
2017
AI Paris

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Chief Data Officer Summit San Francisco

7
Jun
2017
Chief Data Officer Summit San Francisco

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Customer Analytics Innovation Summit Chicago

7
Jun
2017
Customer Analytics Innovation Summit Chicago

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HR & Workforce Analytics Innovation Summit 2017 London

12
Jun
2017
HR & Workforce Analytics Innovation Summit 2017 London

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