3 Enterprise Data Roles and How They Can Drive Business Impact

Screen showing data

By Eric Wise

The following post contains an excerpt from our enterprise ebook How to Become a Data-Driven Organization. Download your free copy.

According to the Data Literacy Project, organizations with strong corporate data literacy exhibit up to 5% higher enterprise value. So I’m not surprised when I hear from an increasing number of company leaders who want to democratize data inside their organization, or from employees with the desire to gain an understanding of common data and statistical terms and techniques to stay relevant at their company.

The path towards a mature data and analytics organization begins with a vision. Like most transformation, this is a continuous and dynamic process. A clear vision has a pretty broad definition in the business context, so let’s define what we mean by putting data and analytics functions into one of three roles.

  1. Utility

Treat your data like a utility service (power, water, etc.). You will be able to democratize data across all departments, and individuals and teams will have the ability to self-service their data needs for the most part (or might call on more advanced skill sets on the data teams as necessary).

  1. Enabler

Target operational excellence. Direct your data capabilities towards measurable ROI. You often see this vision in retail or manufacturing where the data vision is used to minimize production costs and maximize process efficiency.

  1. Driver

This vision is all about innovation. Apply tools and techniques to identify new trends, products, and opportunities.

There are aspects of each of these types of roles that might be contradictory at a detail level, but do not make the mistake of thinking that having a blended vision is bad. It’s not only likely, but it’s preferable!

A fully mature data and analytics function requires all three types of roles, although they are not equal since every business (and business unit) has different capabilities and measures of success. The amount of effort and investment in each of the three visions will depend on your type of business and its overall strategy.

When implementing a data and analytics strategy, business leaders need to reach agreement on the role of the data and analytics function. Without this agreement, you can end up with a mismatch of expectations, such as a technical team only focusing on making data available as a utility when other business units want to use data as a driver and aren’t seeing capabilities evolve. This type of mismatch can lead to dysfunction and dissatisfaction between teams in the organization.

A critical component of long-term success is the workforce’s ability to adapt its skills and knowledge to evolving business needs. Getting there is a mixture of seeking out employees who demonstrate a combination of technical acumen and open mindsets and then enabling a culture that celebrates and supports dexterity across business units.

The best way to drive employees across all business units to embrace data literacy and digital dexterity is
 to ensure that the effort is sustained and coordinated. The new world of data and analytics requires effective collaboration between technical, business, and hybrid professionals.

Download How to Become a Data-Driven Organization.


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