Your Data leader: A technologist but also the Strategist & Catalyst needed to realise value?

Businesses continue to make significant investments in data and AI, yet these investments often fail to translate into tangible business growth or operational efficiencies.

Traditionally, data leaders have built their careers by focusing on the efficient management and provision of data and analytics. They excel in responding to ‘transactional’ business requests.

However, efficiency alone is not enough. Business users often lack the knowledge and expertise to navigate how analytics can help them be more successful.

To truly unlock the power of data and AI at scale, data leaders must go beyond their roles as Technologists and Operators. They must also become Strategists and Catalysts—guiding the business in how to use data to drive real impact.

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At their core, data leaders are experts in sourcing, manipulating, analysing data. They understand how to apply data and AI technologies efficiently, designing scalable processes to automate solutions for the future. Building strong technical teams, fostering best practices, and ensuring robust data governance are core key responsibilities.

Yet, in today’s world, these skills should be considered table stakes for any high-performing data function. The real challenge is not just technical excellence but driving business transformation through data.

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Many business leaders don’t fully grasp how data and AI can pragmatically be used to improve decisions and actions. They need guidance—not just on using data, but on identifying the right problems to solve through data.

To play this role effectively, data leaders must develop strong commercial acumen. They must understand business dynamics, quickly assess where data can unlock the most value, and champion the simplest, most effective analytical approaches—resisting the allure of overcomplicated solutions.

For data leaders who have risen through technical ranks, this shift is a stretch. Many are accustomed to taking requirements from the business rather than being able to ask the right questions to elicit them. But if data leaders are not able to step into this strategic role, who will? Without a strategic and commercial mindset guiding the best use of data and AI, then the potential from data and AI will remain unrealised.

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Data and AI only deliver value when they lead to better decisions and actions—whether strategic, operational, or tactical. Achieving this requires more than just providing insights; it requires the ability to influence, build trust, and support changes in capabilities and processes.

To drive adoption, data leaders must help business users understand and trust data-driven solutions. They must navigate organisational politics, overcome resistance, and evangelise the potential of data and AI. Without this ability to influence, even the most promising data opportunities risk remaining ideas and not reality.

Many data professionals, by nature, are logical problem-solvers who focus on facts. However, business transformation is often driven by perception, trust, and behavioural change—areas that can feel unfamiliar or frustrating to those with of a logical, rationale mindset. How to engage stakeholders, address hidden sources of resistance, and gain buy-in is essential for delivering real impact.

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Whilst ‘Heads of Data’ have developed their management skills, the leadership capabilities needed to work the levers of influence, effectively communicate across all levels and create the belief and trust required to deliver change, are often less developed. Without these skills, the data analytics team risks remaining as ‘order takers’, unable to shape the conversations that that lead to transformative solutions.

Fortunately, data professionals are naturally curious, eager to learn, and driven to solve problems. The potential to bridge these capability gaps is there—but it requires intentional focus, coaching, and structured development.

With increasing pressure to deliver business transformation through data and AI, the question is: ?????? ?????? ???????? ???????? ?????????????? ?????????? ?????????????????? ???? ???????????????????? ?????????? ???????????? ???? ???????????????????? ?????? ?????????? ???????? ???????? ?????? ?????

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Adapted from 德勤 CDO Survey, 2024