pressmaster - Fotolia

Data storytelling techniques can help sell governance efforts

In addition to explaining analytics results, data storytelling can help sell business executives on the need for strong data governance and management programs.

Data storytelling is typically associated with analytics applications. But data leaders should also use storytelling techniques to win internal support and funding for data governance programs and broader data management initiatives, according to experienced practitioners who spoke during a recent Dataversity webinar.

In this context, storytelling isn't about explaining data and analytics results to business executives. It involves convincing them that effectively governing and managing data is strategically critical to the organization.

"If we want to get executive support, stakeholder engagement and ongoing funding for the work we do, we've got to tell a story about the data," said Scott Taylor, principal consultant at MetaMeta Consulting and a frequent public speaker under the moniker The Data Whisperer. "And I will tell you, there won't be very good stories you can tell with data if you don't [first] tell the story about the data."

Data leaders should emphasize both the business benefits of strong data governance and management and the potential consequences of failing to implement effective processes, Taylor added. For example: "Why are three of the five things your CEO put in the annual report letter not going to happen unless you have good-quality data?"

Taylor also recommended applying journalism principles when creating data stories. Like news stories, he said they should start with a headline, a subhead and a lead to give senior executives key information at a glance, then go into more detail on the importance of data governance and management efforts.

Merrill Albert, an independent data consultant and advisor, said good storytelling brings data governance and management problems to life for business stakeholders in practical terms. "You have to find a way to make it relate to them," she said. Otherwise, even a well-put-together presentation is unlikely to get their attention and win them over.

Highlight potential pain points

A memorable storytelling message lets executives "feel the pain that they could go through if they don't listen to you," said Ajay Mathur, data and AI enablement manager at financial services firm Jupiter Asset Management in London. Ideally, he added, that sparks an emotional response in them -- for example, if they think data governance shortcomings will put their reputation, and the organization's, at risk.

Mathur, who speaks regularly at industry events, also said adopting a shift-left governance approach that builds controls into data architecture design both reduces post-deployment data issues and eliminates the need to convince business leaders to bolt on governance after the fact. A single well-told story about incorporating governance upfront is enough in such cases. "You've already shown the value," he said. "You've already built the foundation."

AI: Data storytelling sidekick

Taylor said AI can help craft effective data stories "if you use it as a tool and not as the end result" -- and if you can ensure you're feeding accurate and complete information into a standalone AI chatbot or one built into a data storytelling tool.

Mathur described AI as a useful sidekick that can provide guidance on structuring different stories for different executive audiences and then polish them for users. These capabilities are especially helpful for people who aren't confident presenters. But he said the onus is still on data leaders to know what they need to focus on to sell data governance and management programs in their organization.

Craig Stedman is an industry editor at TechTarget who focuses on data technologies and processes. He has covered enterprise IT for more than 40 years.

Next Steps

Data and AI governance must team up for AI to succeed

Shift-left governance brings data controls upstream for AI

Data governance for AI requires a cross-functional approach

Data governance metrics: Measure success, identify issues

Dig Deeper on Data Management