How to hire a data leader the right way

Despite increasing investment in data initiatives, organisations repeatedly misfire when hiring data leaders. One of the biggest mistakes companies make when hiring a Chief Data Officer is assuming that one person can do everything. They end up asking for both a visionary strategist and a hands-on executor, which is where things start to go wrong.

The tenure for a Chief Data Officer is striking, with most averaging around 2.5 years. Compared to other C-Suite positions, this is relatively short. And while the role is often still finding its footing, nobody can deny its importance since data has become so central to all enterprise operations. So what’s the real issue here?

Greg Freeman (Founder and CEO of Data Literacy Academy) and Kyle Winterbottom (Founder and CEO of Orbition Group) unpacked the root causes of this challenge on the Driven by Data podcast recently. This episode acts as the playbook for everything businesses need to know about data leadership hiring.

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What’s the problem with hiring a CDO?

Why is the CDO role so problematic? It all stems from the misalignment between what companies ask for versus what they actually need from the role. More often than not, companies don’t even seem to know what they want from the role in the first place.

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Right person, wrong brief

Most data leadership hires fail not due to the individual's skills or capability, but because the role itself is misaligned with the business's actual needs. There is a sense that CDOs are set up to fail as they are often hired based on buzzwords rather than actual business needs. There are often unrealistic expectations around the speed at which CDOs can deliver results, which puts pressure on the data leaders and also distorts results, making it appear as though the CDO has not achieved the goals set out. These common mistakes lead to short tenures, higher turnover and missed opportunities to derive real impact from the CDO role.

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“You’ll put someone into that role. They'll work for you for 18 months. They'll deliver exactly what you asked for, and then the chances of you firing them is very high. Not because they failed, but because you expected something else. You're putting someone into a job where the skills that are being sought are not necessarily the right skills for what you expect.” - Kyle Winterbottom

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Hiring briefs often focus on technical deliverables like fixing data quality, building governance frameworks, or setting up platforms rather than the bigger picture, like empowering a data-driven culture from the top down.  This is because the organisation lacks the understanding of what the CDO role should involve, which in turn can lead to scepticism and a lack of support for initiatives down the line. Successful CDOs lead from the front, acting as change agents who champion the value of data and the power of a data-driven organisation from the boardroom to the back office. However, if organisations lack an initial desire to create a data-driven culture, the job specification is likely to reflect operational firefighting as opposed to tasks which drive real transformational change.

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Lack of standardisation and role clarity

Chief Data Officers are managing one of the world’s most valuable assets, which is no small task, especially with the large amount of ambiguity regarding their role already. While supported conceptually, the role itself remains misunderstood in execution. The CDO’s role can be scoped slightly differently within and across industry verticals and companies. This lack of standardisation is another key reason why companies continue to get the role wrong. It is heavily related to the organisation’s maturity and baseline understanding of the importance of data as a strategic asset in the business world. Not only is there confusion around what the CDO is responsible for, but this quickly feeds into a difficulty in understanding how the role fits within the wider organisational structure.

Without understanding what a successful CDO hire looks like, hiring managers tend to base job descriptions on assumptions rather than their wider business goals. This lack of clarity is a sure-fire way to add to the confusion, and hire the right person but expect the wrong outcomes from them.

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Why do data leaders accept misaligned roles?

For starters, many suitable candidates never make it out of the interview stage because the poorly designed job specifications filter them out. Equally, many capable data leaders don’t even apply for the roles when the job description is skewed towards a more operational, delivery-focused role.

On the other side of the coin, some candidates may accept ill-defined roles for the prestige or out of necessity, even with the knowledge that the role is set up to fail. Economic conditions and personal career timelines can add pressure, which increases a leader’s likelihood to accept a role that they know is misaligned simply because it provides them with a CDO title, and the accompanying salary increase.

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The solution: The four-phase hiring framework

When tackling the issues that come with hiring data leaders, Kyle and the Orbition Group regularly refer back to their Discover–Identify–Engage–Assess model. It’s a comprehensive hiring methodology that flips the script from reactive hiring to strategic, consultative hiring. Let’s explore how implementing this approach can help solve the current CDO crisis:

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Phase 1: Discover - Define business objectives first

The discovery phase is simple: get to the root of what you actually need in order to move the needle. First, define your requirements. What are your organisation’s key business objectives over the next 12 to 36 months? If you don’t know these, then you need to stop and work them out, as everything should flow downstream from your key business priorities. Otherwise, tracking progress and impact is nearly impossible.

Once you have identified your business objectives and mapped out the relevant KPIs and use cases that tie your data initiatives to these goals, work backwards to define what type of data leader you require to deliver these specific outcomes.

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Phase 2: Identify - Pinpoint the right skills for the right outcome

Now you have established your organisation’s key objectives, the next step is aligning the job role with the appropriate skills, knowledge and experience to positively impact business performance. Keywords alone are a terrible proxy for suitability, instead, emphasis should be placed on experience. Stellar candidates are those who have the most relevant, hands-on experience working with similar problems and priorities required by your organisation. Simply having a long list of key competencies isn’t going to cut it.

“Identification is easy. I can give you a list of 300 names in 30 minutes. But finding the right 10% who will drive value? That’s hard.” - Kyle Winterbottom

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Phase 3: Engage - Stand out in a noisy market

Top data leaders receive 15-20 recruiter messages a week, so if you’re sending the same generic, vague cold emails, the chances of getting a response are slim to none. Position your organisation as the employer of choice, using persuasive storytelling and relevant examples to highlight:

• The strategic importance of the role
• Impactful projects you are working on
• Culture and leadership
• Opportunities for career growth and development

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Phase 4: Assess - A smarter approach to evaluating talent

Interviews are often unstructured and biased. These subjective evaluations, coupled with incoherent, misaligned briefs, are more than likely responsible for the poor decisions that occur when hiring senior data leaders.

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Throughout his long career in recruitment, Kyle concludes that:

“Hiring is the least data-driven process in most data-driven businesses.”

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Organisations should build a skills competency framework, whereby they identify, define, and measure the skills, knowledge, and behaviours needed for success in a specific role. This acts as a roadmap for employees, guiding them in their responsibilities and helping them understand what's expected of them. For organisations, it provides a clear understanding of what they expect from the role and helps in aligning personal performance with wider business objectives. Benchmarking candidates across technical and non-technical skills provides a valuable overview of their capabilities for the role. When hiring a Chief Data Officer or similar roles, this framework is crucial in tackling the recurring misalignment issue that businesses face all too often.

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Getting Data Leadership hiring right, for good

Hiring a Chief Data Officer should be a strategic act, not a checklist activity. Failure to acknowledge this and put the appropriate processes in place means organisations will continue to be disappointed with the impact of their hire. Not because they’ve hired the wrong person, but because you’ve provided the wrong brief.

The misalignment between what organisations think they want from their Chief Data Officer compared to what they actually need is a core pain point when hiring data leadership. Without a clear understanding of the wider business objectives and how the CDO role aligns with these, it is impossible to derive true value from the CDO position, regardless of how experienced and proactive the data leader is. Misalignment is costly, not only does it waste time and resources, it also diminishes trust and stunts org-wide transformation.

If you’re planning your next strategic hire in data, pause and reflect: What are you really solving for?

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