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Data leaders discussing their challenges regarding people for the year ahead.

There are four separate key challenge areas; last week we delved into the extent to which foundational issues are pain-points for data leaders, reporting on literacy, culture and strategy: catch up on that content here. Join us on the research journey as we shake down the biggest challenges for the biggest leaders in data.

The information in this report was pulled from data leader responses to the question: What are the key challenges to your data function that you are facing as its leader? 

 

PEOPLE 

 

The second key area referenced by data leaders when they detailed their challenges for 2024 falls on the people side of leadership, though it only surfaced in a minority of responses. This is most likely because HR and recruitment teams have the greatest responsibility here; as is made evident in the quotations referenced below, leaders are looking outside of immediate issues and are concerned instead for what it means for the industry at large – the bidding war for talent, the rife headhunting. This suggests that in 2024 tackling the wider issues in this space is of greater importance than ever before. The role of diversity, ethics and inclusion is not to be understated here. 

Increasingly, data practitioners and business practitioners alike must have solid interpretation skills to draw conclusions from a variety of results. It is only through constant upskilling that organisations can ensure this happens.  

AI skills fall short in many industries; a new challenge that has led salaries in this area to skyrocket. Businesses are tasked to look inward and exemplify the benefits of why new talent will want to work in their team above others inevitably hiring; a third of leaders are actively working on new initiatives to tackle this head on. It remains clear that strong networking, cross-functional collaboration, and a sharp eye on culture will interest better talent. 

 

Upskilling (31.3%) Data leaders discussing their challenges regarding people for the year ahead.

Around a third of data leaders identified the growing challenge of upskilling data practitioners; 31.3% mentioned this explicitly in their response. Some clarified that rather than just making elements of training mandatory, they are starting to position upskilling as a strategic move to connect analytics outcomes to actual actions and evaluate team performance in the process.

Shreenivasa Rajanala, Vice President of Data Science and Analytics, Bayer, explained the nuances of this challenge in light of the rapidly evolving world of AI: “Upskilling people in this is not to make everyone an analyst, but to instil an understanding of the questions to ask and how to interpret results; this exists for business users as well as data professionals. The changing and rapidly evolving world of AI has brought a lot for data professionals to also upskill and adapt.”

Data leaders frequently mentioned concerns around a shortage of AI skills in the workplace; upskilling may be one solution that confronts this issue.
 

Data leaders discussing their challenges regarding people for the year ahead.Hiring talent (31.3%) 

In most cases, those who mentioned upskilling as a challenge also mentioned the challenge of hiring talent initially; this may be because in the data and analytics industry there is a lack of title standardisation. What a Data Scientist may be differs from company to company and is exacerbated when considering seniority and titles. Renumeration, responsibility, and expectations further differ sector to sector.

DataIQ has found that a sizeable number of leaders express their issue about hiring capable talent to join their data teams (31.3%). The importance of data and analytics to better organisational decision-making is fast gaining traction; training initiatives, upskilling, and a collaborative and innovative culture all help this matter. More specifically, this DataIQ article details some of the ways leaders can secure AI talent and succeed in AI recruitment through tailoring the hiring process.

The skills shortage not only affects the supply of new data talent, but it means retention is trickier as career paths open across the market. This also means salaries are swiftly rising as talent is poached from competitors.

Esther Munyi, Chief Data and Analytics Officer, Sasfin, discussed the people problem as a key challenge for the year ahead: “There is a huge demand for data skills in the market. It is creating a bidding war, and the organisations with the deeper pockets are throwing money at the problem. We need to address the shortage in the medium- and long-term, not just short-term”.

 

The next instalment of this article series will examine another aspect keeping data leaders up at night in 2024: Threat.

Sign up for upcoming exclusive DataIQ events to improve your foundations. 

Read part one here.

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