How to grow the pool of talent for Data and AI

James Webb

Liz Norman recently wrote a piece on the new & ever changing skill sets needed within the ‘insight industry’. The blog article first appeared on Research World. 

3min read.

Increasing mobility is key to the future.

Finding talent for the ‘Insight industry’ has changed enormously over the last few years. There are new and different clients, there are different technical skills, and there is an increasingly diverse range of roles across a wide range of company cultures.

The job hasn’t got any easier; the recent growth of the industry has resulted in a shortage of skilled talent, large variations in salaries, unclear career paths and a lack of understanding from graduates on what a career in the sector can offer. It doesn’t matter where in the world we recruit, everywhere there is a shortage of talent across a very segmented industry.

We used to be asked for proven questionnaire writing skills, extensive experience of moderating groups – now it’s just as likely to be experience of programming languages like Python and R, or software like Hadoop. Once upon a time, we were looking for candidates with a first-class degree in any subject, today it is increasingly likely to be a degree in computer science or maths. Continuous and tracking data skills are gradually being replaced with the need for experience in machine learning or social listening.

What stays the same?

However, it isn’t all different. What remains the same is the need for ‘insight’ regardless of the intelligence or data sources. This means that whilst the technical skills have changed, many of the competencies remain the same; the ability to see patterns in numbers, a qualitative mindset, story-telling, influencing, seeing the big picture, commercial aptitude and the ability to analyse intelligence from a range of research approaches. These are all competencies needed for Insight regardless of data used.

It’s possible to teach skills and provide experience, but competencies are an innate ability, something you were born with. The research industry is not good at blowing its own trumpet, but many in the industry have the competencies needed to provide insight regardless of the data it is based on. This is important as other backgrounds don’t necessarily offer the competencies needed; data scientists are used to working with one very specific area of data and getting the detail right, which makes it harder for them to work across different intelligence sources, and see the big picture.

New competencies

There are some additional and different competencies needed by researchers wanting to transfer across to the newer areas. Data is a dynamic and fast-changing industry, it requires individuals who have flexibility, are fast-paced and are prepared to occasionally take a leap into the unknown. Not everyone in the industry will make the move, but many could. Increased mobility of labour between MRX and data would help ease the shortage of skills and it might also help even out the salaries.

Data scientists are in short supply and as a result command high salaries. Employees experienced in data and AI, who have the ability to work autonomously and support others are paid 30% more than researchers at a similar level are earning. The difference becomes even more pronounced at a senior level. This is a real problem for consultancies trying to attract applicants with the new skills, or insight departments basing strategy on both sets of data; how do you justify some people in the team earning more than other team members simply because their experience is of different intelligence sources?

To increase the supply of individuals with data and AI skills, it needs to be easier to transfer from one area of intelligence to another. There are a lot of researchers out there who have the competencies needed to forge great careers in insight based on data and AI, with additional training and experience.

Mind-set and mobility

In this new world, researchers need to be open to new methodologies, those recruiting need to be more open to different applicants, and there needs to be a greater understanding of what is required in the new world of Insight, noting that increased mobility is possible with the right investment.

Geographic mobility would also help as some parts of the world are perceived to be particularly strong at certain things, the US is very commercial, the UK creative, and India technical. Unfortunately, that sort of mobility is going to be a lot harder to get around in today’s world.

Increased mobility from research to data science roles isn’t the whole answer. Longer term, if the insight and research industry is to hang on to staff it has invested in and provided with additional data skills, it needs to address the salary discrepancies. It also needs to compete with the culture that purely digital/data organisations offer, many of whom work in a more flexible way, both in terms of location and hours.

Increased mobility would however really help an industry struggling to find people with all the necessary skills. It would certainly make my job easier, and I believe the MRX industry should be more confident about its strengths and what the individuals within it can offer in this exciting new world of data.

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