Five Pillars for Levelling Up on Data Maturity
Hartnell Ndungi, Absa Bank Kenya’s Chief Data Officer, has developed a framework for assessing maturity and creating action plans to move up the data ladder
Inspired by a Gartner framework, Absa Bank Kenya CDO Hartnell Ndungi has identified five levels of data maturity that describe the state an organization is in: 1) basic, 2) opportunistic, 3) systematic, 4) differentiating and 5) transformative.
In this episode of Data Conversations Over Coffee, Ndungi talks about how to use this framework as a rough ‘data maturity’ guide. But he cautions that CDOs should apply their own approaches to move their organizations up the value chain. In practice, that means developing processes to ensure that all areas of data strategy execution – from data governance to data literacy and advanced analytics – are covered across the organization.
“Level 4 and 5 are where the whole organization is involved in data,” Ndungi notes. “And where differentiation from the competition is achieved and the organization is transformed into a data-driven enterprise.”
He concludes that an organization has reached Level 4 “once you start seeing the opportunities and your organization is ready to invest”. At this point, he urges data leaders to secure sufficient funding to invest in the right skills, tools and architecture to succeed.
- Use a top-down and bottom-up approach. Secure both executive-level sponsorship and company-wide support
- Make life easy. Be able to tell stakeholders how data analytics can make their lives and work easier
- Make data fun. Simplify the concepts of data to make people appreciate and understand it more