Insurers are losing the war to attract the data analysts they need to grow. But the challenges are surmountable, says Startupbootcamp managing director Sabine VanderLinden

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Insurers and brokers face a growing skills gap in the field of data analytics, for two key reasons. The first is they struggle to find young analysts with the right skillset. The second is that they struggle to attract and retain the top talent. These problems are not unique to insurance.

A study from McKinsey forecasts that by 2018 there could be 190,000 data scientist jobs in the US alone that will remain unfilled for lack of skilled candidates.

There is also the “celebrity effect” to contend with; many data scientists want to work with the likes of Google and Palantir not just because they pay extremely well and offer a dynamic working environment, but also because of their reputations. Data scientists want to work with these companies partly because they are seen as the best at applying data analysis in the business world.

Insurers don’t just have to compete with each other for a relatively small pool of talented analysts – they have to compete with everyone.

So insurers and brokers face several challenges when it comes to plugging the data skills gap. Yet the industry has a number of advantages it can bring to bear when finding, training or retaining the best data analysts. You too can solve this problem, as long as you take one or more of the following steps.

1. Think strategically, not tactically

Insurers must be clear on what they need their data analysts to do. The days of just using data scientists to answer specific questions are gone. Now, innovative companies are also building in time for exploration, freeing up the people who are closest to the data to discover new insights – and therefore more lucrative revenue streams that firms can tap into.

And it’s no longer enough to use big data for customer relationship management. The real money in your data lies in viewing that data itself as an asset, and actively seeking out more ways you can use your data to solve business problems for other companies and other industries. For example, many large health insurers have data on which drugs are most effective at treating specific conditions. That would be useful for pharmaceutical companies to know – and they’d be likely to pay handsomely for that insight. As would fund managers when they’re looking to decide which pharma companies to invest in.

But the question is not just whether health insurers have the technical skills to analyse their data in this way – do they have analysts who are asking those kinds of questions? Insurers who don’t ask these questions could end up leaving millions on the table in untapped revenues.

This means you need data analysts who are also able to look at problems creatively and come up with innovative solutions. You need to give them an environment in which they can experiment and thrive. This is a win-win situation: not only is creating such an environment good for your business growth, it’s also the kind of environment that the top data scientists want. So this should help make it easier for you to attract and retain the kind of people who will grow your business.

2. Widen your search

So the university graduates in your country or region aren’t making the grade? Fine – look further afield. Find out where the best graduates are coming from. Singapore? China? India? You need to know – and then you need to target graduates from those places, work out what they want, and offer it to them.

But widening the search doesn’t just mean looking to data scientists from other countries. Look to graduates from other disciplines too. A recent article in Computing magazine by Mark Ridley, the CIO of recruitment website, urges that firms struggling to find data scientists should spread their search to include graduates in disciplines such as sociology and economics. It’s not just technical skills you need: you need 

imaginative problem solvers who can think analytically and are willing to learn.

3. Make yourself more attractive to the talent you want

Every industry wants talented data scientists. And, as discussed, the likes of Google are paying top dollar. So make sure you’re offering salaries that are in line with what they can command in other sectors. In fact, this is crucial. According to research published in the Harvard Business Review, “the skills gap persists mainly because employers are unwilling or unable to pay market price for the skills they require.”

It helps to see the high cost of these wages as an investment with the potential to bring you significant returns. After all, if you’re encouraging your data scientists to think about how to make more money from your data assets (as discussed in point one, above), they have the potential to unlock millions in new revenues. That’s the very definition of adding value, and it’s worth paying a lot for.

You should also find out what else data scientists want, besides money. Ask them. Do a survey. Look on LinkedIn to see what companies the most talented new data graduates are drawn to, and then find out what those firms offer that you don’t. Do they want flexible working hours? Do they want the freedom to experiment with data? Or to run their own innovation projects?

And don’t be shy about selling the benefits of working in the insurance industry. Granted, insurance might not have the glamour or social status 

of digital agency, fashion retail, Apple, Google or Tesla. But compared to most sectors, insurance is a lot more stable – and a lot of talented people want stability in these uncertain economic times. On top of that, insurance is also global, and it has a direct impact on most people’s lives. And – certainly for the most part – insurance is beneficial to society and the economy. Something else that many job candidates find attractive.

4. Get involved with business schools and universities

If young graduates don’t have the skills the market needs, you can do something about it. Most business school courses on business and data analytics are modular, and many require their students to do their own hands-on research for dissertations about how to apply their skills in the market place.

Why not approach business schools or universities and seek to participate? Offer to partner with them in return for the ability to work with their students to help them learn about the challenges you face that you do want them to solve. Involve your business lines through this process, not just your talent management team.

The impact on the insurance market of telematics, wearables and other manifestations of the Internet of Things throws up a number of juicy challenges that talented and ambitious young data scientists would love to work on. Give them the opportunity early on and not only will they learn about how to use data to solve the business problems you have – they might just end up wanting to work with you once they’ve graduated.

5. Take advantage of the business ecosystems around you

The business ecosystem concept is an old one that’s gaining renewed attention now in the age of the sharing economy and digital disruption. First appearing in a Harvard Business Review article in 1993 written by James F Moore, a business ecosystem may be broadly defined as the network of organizations – including suppliers, distributors, customers, competitors, government agencies and others – involved in the delivery of a specific product or service through both competition and cooperation.

Today the concept also includes the idea that business ecosystems can be used to facilitate innovation, and to solve wider problems. Silicon Valley is one example of such an ecosystem – a network comprised of innovators, suppliers, financiers, distributors and others, based around the lynchpin of Stanford University.

InsurTech is another example, where our insurer partners – nominally competitors – come together to pool resources, share knowledge and support new innovations that could benefit the entire industry.

In the context of the data skills gap, you have options beyond having to go through the long process of hiring and developing new talent. You could partner with a startup that already has the skills in a certain market, for example. You could partner with other insurers to build a sort of insurance analytics academy, specifically to develop the skills the industry needs. Or you could outsource your data analysis to a company that specialises in this kind of work.

There are questions around this approach that need to be answered – how to ensure regulatory compliance and data privacy being perhaps the two most obvious. But, with the right safeguards and processes in place, this could be the best option for you – at least in the interim. Partnering with a skilled and trusted analytics company means you get people who are used to solving business problems like yours. And you can learn from them what skills you need to hire internally longer term – as well as finding out what you need to offer to attract the top talent.

Persistence and sensitivity will lead to success

With the data skills gap in insurance already acute, and growing worse, most insurers would probably benefit most by combining several of these approaches to solving the data skills gap. In the end, it’s worth remembering that there are few jobs that are easy to fill that generate high profits for a company. Whatever approach you take, you can’t afford to do it half-heartedly. If you are both persistent and sensitive to the demands of the labour market you are more likely to succeed. If you’re not, then talented people won’t want to work for you.