Top 10 attributes of a true data leader

Data fuels innovation and business value in most businesses today, but what makes a data leader succeed? Information Age profiles the top 10 attributes

Whether you’re a CDO, a marketing executive, or another kind of data leader, enabling the organisation to make the best possible use of assets is now crucial to business success. Data showing customer needs and behaviours is no longer a nice-to-have, but a key tool, the absence of which will leave a company playing catch-up with the competition.

With this in mind, we provide 10 attributes that a truly successful data leader needs to possess in today’s landscape.

Data is no longer confined to technical departments. Successful projects must be partnerships between lots of different groups with different goals, mindsets, levels of understanding and ways of working. Breaking down silos is vital to collaboration and innovation.

Data leaders must have a strong understanding of the business, their industry, their data and what their data represents. They must be able to direct teams which encompass data scientists and analysts who can understand the data, business people who can frame the problems that need solving, IT people who can put it all to work, and domain experts to ensure that the insight is clearly presented, while making sure that everything links back to the business’s objectives.

“The best data leaders will be able to act as translators to bridge the gap between these different parties – speaking the language of the business and the data scientists,” said Matt Jones, head of offer development at Capgemini Engineering.

A true data leader is not an IT director in the traditional sense; nor do they need to be an expert in advanced data analytics. The infrastructure and technology are necessary elements, but the core challenge in becoming a data-driven enterprise lies outside this scope.

Instead, a data leader should be a manager who is capable of doing one crucial thing: merging science with business. Integrating new types of data analytics into business requires significant changes in the usual approaches. Existing processes and organisational structures are often not tailored to work with automated and truly data-driven decisions. The role of a data leader is to enable this.

When these are algorithms making the predictions and recommendations, the only way to demonstrate and measure their effect is through experiment, carried out in accordance with all formal requirements.

“This approach may be well known to a scientific facility, but is quite unusual for a commercial organisation,” said Jane Zavalishina, former CEO of Yandex Data Factory (now Yandex.Cloud) and faculty member at Singularity University.

“Establishing the environment and processes that would allow for such experimentation is crucial to actually derive business value from data-related initiatives. Only with a rigorous, scientific-based approach and by having clearly articulated success metrics in data projects can the organisation learn to trust the black box predictions instead of PowerPoint presentations and gut feeling.

“This requires overcoming existing organisational boundaries, such as deciding how responsibilities are assigned and data is shared between departments. This urges for the ability to lead the dialogue with business owners to convey the meaning of the technology and identify the best data use cases that could actually be carried out in the existing company environment and bring directly measurable effect.”

A true data leader should have a clear understanding of business needs, have a solid knowledge of tools and technologies, and be an excellent manager and communicator to align the two.

Big data is an area of work in which there is so much to ingest and discover, that you need a certain level of ‘guts’ to be involved full-stop.