Data Leadership: What is the Reality?

As previously featured in Tech Exec Magazine

The data leadership market is in disarray. This is a point I’ve been making for a good 18 months now. In the UK right now, there are circa 48,000 people that span Head of, Director, VP, and CDO job titles. Yet, there are only a little over 700 live adverts for those titles.

That’s in stark comparison to some of the more technical markets, such as (modern stack) data engineering, with a little over 63,000 people, but close to 62,000 live adverts for those skill sets. Now factor in that even the smaller organisations have more than one Data Engineer, and simple maths tells you that something doesn’t add up.

The unfortunate reality of this situation can largely be boiled down to one challenge: most data & analytics initiatives begin as a major technological initiative, a challenge that the data & analytics community has been speaking about for years now. Yet unfortunately, things aren’t really changing, nor at the speed we need them to.

TECHNOLOGY VS. PEOPLE

Sure, technology is a super critical component to data transformation, but it’s not the only component and, arguably, it’s possibly the least important.

First of all, it’s worth noting that whether they realise it or not, most organisations are in the midst of a data transformation. There’s been a lot of press about the lack of value that most data & analytics initiatives generate when stacked up against the expectation of what was promised.

Ask anyone in the data & analytics community and most will tell you that you need to start with the business strategy and work backwards from there. Yet, that very rarely happens. Most data initiatives start with the building of ‘stuff’ (technology) – platforms, lakes, warehouses, models, dashboards, etc.

Despite the fact we know better, why does this continue to happen? Put simply, technology changes can be seen, felt and used, whereas the other components to data transformation – people, process, and maybe even data, are often invisible and intangible.

However, we’re slowly starting to realise that any data & analytics capability exists to support the business to be better at what it does. In the large majority of organisations the metrics to quantify success/impact are around how the decisions being made based on data are increasing revenue, reducing cost, mitigating risk, improving efficiencies, improving customer experience, etc.

For any commercial organisation, whichever way you slice and dice it, and when you strip all of that back, it comes down to commercial benefit. But the problem is that the starting point for most businesses isn’t aligned with that end-goal in mind in relation to the strategy of the business.

Sure, building a  data platform is probably an essential part of the process, but many do that in isolation, without a strategy as to why, and often without aligning to the business strategy. Fear of missing out plays a huge part in this situation. Many organisations understand they should be doing something (or more) with data, given all of the talk and hype around this ever-growing business asset. But, unfortunately, most go digging for value as opposed to making sure what they’re doing is aligned to the business goals.

The real challenge with most data & analytics initiatives is one of change management to tackle the all-important topics such as culture, adoption, literacy, etc.

THE ROLE OF THE LEADER

When you bring all of this back to the role of the data leader, it’s really easy to see where the gaps lie. Simply put, organisations are often prioritising the wrong skill set and experience, and focusing on the wrong activities.

Of course, there are certain businesses that require technical leadership at that point in time in relation to where they’re at on their data journey, but for the large majority, the challenge is NOT a technical one, it’s a people one.

Why, then, do most data leadership job descriptions ask for things like Python, for example, when the things that often make the difference are the so-called ‘soft skills’ (I use quotation marks because they’re by far the hardest to master) such as communication, storytelling, influencing, relationship building, commercial awareness, etc?

In reality, there are very few people who can do both sides of the coin in equal measure, and even if you found someone who was equally strong on the technical side as they were on the transformational side, it’s unlikely that they’ll have the time to be effective in both camps.

The interesting point I often hear from data practitioners is that they prefer to work for leaders who come from a technical background as they ‘get it’. However, at the same time they get frustrated by the fact their work isn’t being used in the organisation, meaning what they’re doing isn’t visible, valuable or impactful.

Ironically, the role of the data leader is to do just that: make sure it’s being used and having an impact where they can pinpoint to demonstratable commercial benefit. It’s not to be the best technical asset to the organsiation – they can appoint teams of people who can do that much more effectively than they can.

It’s like the old football analogy of how many legendary football managers (soccer for my US friends) played at the top level as a player? Very few. Yet, what we’re seeing in the data leadership talent market is the equivalent of a football team stating that the requirement to be their football manager is to have won the World Cup or Premier League, etc, as a player, as opposed to building a great squad that performs to achieve their goals.

The lack of standardisation across job titles and remuneration really doesn’t help either. Even in organisations of similar sizes/scale, the title and remuneration levels differ wildly. Hopefully, this is due to the fact we’re an immature industry in comparison to our colleagues in more established domains such as finance or marketing.

But, one company’s CDO is another’s ‘Head of’ – you see managers on better packages and with bigger teams than some Directors, even in organisations of similar sizes and sectors.

Given the sheer number of people at the data leadership level and the sheer lack of jobs by comparison, organisations should be able to hire easily for their data leadership roles directly, yet the large majority really struggle, and that’s because they’re often not sure what skills and experience are essential to drive value from their data & analytics initiatives.

It will change! It has to. Because there’s only so long that organisations will continue to invest in data & analytics without seeing the commercial benefits they were hoping for. The role of the modern day data leader is to drive change (despite all of the politics, red-tape, bureaucracy), and to ensure that data is viewed and used as a business asset to realise commercial benefit.

Kyle is hugely passionate about enabling organizations to drive decisions and obtain value from the use of Data, Analytics & AI.

The two biggest assets a business has are People & Data!

Kyle speaks to hundreds of Data & Analytics leaders every year and says every single one is facing similar challenges to you, in some way, shape, or form. That is what led him to create Orbition Group. Read more.