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One of the biggest problems faced by organizations and technology companies today is addressing the shortage in the data sector - in both personnel and skills.
The issue is only going to get worse. Capgemini has predicted that the volume of data generated by businesses will increase 20,000-fold between 2000 and 2020 and IBM has predicted that the demand for data scientists will soar 28% by 2020.
Addressing the problem is almost as complicated as the role itself. A true solution would require a cohesive approach across education, government and industry. It would require engaging schoolchildren of both genders into studying STEM subjects, and providing careers advice and role models from an early age. And the industry itself would need look differently at how they attract and retain workers in the field of data.
I am just looking at the industry perspective – what companies can and should do to patch their data skills shortage beyond increasing salaries and “buying” workers.
Startups especially are uniquely placed to address this, in two ways. First, they can focus on recruiting like-minded entrepreneurial people who want to experience a different type of work culture; there are many more learning and growth opportunities and variation when working at startup stage and our many recruits will really value this.
Second, they can work hard to ensure they have a diverse, inclusive workforce. Many larger companies try and do this as a “check-box” exercise, so it understandably doesn’t feel authentic. By having a good split of women and men in data, it also means that female candidates will see a working environment that they can see themselves joining.
It’s a no-brainer that an organization needs a good blend of women and men to deliver the best, most creative results. Unfortunately, women are still very unrepresented. In the US alone, women hold only about 26% of data jobs. If you align this underrepresentation with the huge skills shortage it is, at the very least, a matter of good business sense to encourage women into this growing sector.
There are a number of ways that organizations can encourage female applicants. For example, there is an online tool, called textio.com, which strips gender-specific language to make job descriptions more appealing to women. Textio.com identifies certain words as “masculine.” It advises you to use words that are neutral, such as: “meaningful,” “stories,” “collaborative,” “supportive” and “contribute,” and phrases such as “unique point of view” and “work well with.”
Reducing the number of essential pre-requisite requirements can also encourage female applicants. This is because men are more likely to apply for jobs that they are only partly qualified for. Try limiting the must-have skills/experience list in job descriptions and listing the other potential skills/ experience separately as desirable, making clear that you would be happy to support people to develop these skills.
Retention is just as key as recruitment. Mentors can be allocated and new starters can be on-boarded by someone that they can easily identify with. If you have good employees working within your data division, they need to be revered and supported. Workers rarely leave for money – they leave because they don’t feel valued or aren’t being stretched. Make sure you have clear paths for development and that your staff feel that they are being invested in.
As the value and types of data continues to increase, businesses are stretching to fill data roles across every department; marketing BI, InfoSecurity data scientists and engineers to name a few. With intelligent recruitment practices, inclusivity and ongoing support, you will be one step closer to bridging your shortfall.
About the Author
Charaka Goonatilake is CTO at Panaseer