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The Analytics Skills Gap

No end in sight?

7May

A recent study by MIT Sloan Management and SAS found that there is a growing gap between the amount of data that firms are taking in and the ability of their staff to draw insights from it.

A talent shortage in data analytics is not a new problem. In 2011, McKinsey & Company found that there would be a shortfall of between 140,000 and 190,000 people with analytical expertise by 2018 in the United States alone. McKinsey also estimated that around 1.5m managers and analysts with the skills to understand and make decisions based on the analysis of big data would be needed.

One of the major difficulties that companies are finding is that as the value of data analytics becomes more recognized, the competition for capable analysts also increases. While companies looking to build an internal analytics framework may be able to draw talent using the lure that the data scientist would be a pioneer, it is likely that the prospective employee would be more attracted to companies with a pre-established analytics culture in place.

There are a number of ways that this issue can be resolved. Many companies outsource their analytics work, though this is increasingly something firms are moving away from as they look to those companies which have reported the most success in data analytics. Having data analysts internally allows for easier transformation of analytical insights into business actions, which is vital if a firm is to fully exploit Big Data to create a competitive advantage.

Education at grassroots level is also key. There are now in excess of 70 master’s degree programs in analytics and data science in the US, although this could be enhanced were more companies to partner with higher education institutions. This would allow them to help develop the courses in such a way as to be applicable to what they are specifically looking for.

Firms must also expand their recruitment pool. Those found to have successfully incorporated an analytics culture have done so by employing analysts with diverse range of talents, including musicians and biologists. In a similar vein, companies could also look more internally for talent and offer training to existing staff. This is particularly beneficial because they have existing insights into the business and have a better idea of how to apply knowledge gained from the datasets.

Some argue that fears of a talent shortage are misplaced. They argue that it is simply an issue of resource application, as the analyst is expected to source the data on top of providing analysis, reducing their productivity unnecessarily. This logic rests on the idea that were productivity to go up, there would be less need for additional staff. Although firms would still be forced to hire staff to do the data sourcing. If we do accept McKinsey's findings of a shortage, however, it could be argued that organizations should lower their expectation of what employees have to offer and appreciate the benefits of the skills that they do have, rather than focussing on those that they don’t and trying to force them to perform too wide a variety of jobs.

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