Creating A Data Culture: Tips From The Pros

Building a data culture is mission-critical for business transformation, but how do you drive this change — especially with limited resources, talent shortages, and a loosely defined mandate?

Ferrazzi Greenlight partnered with the Data Leadership Collaborative to host a roundtable of chief data officers to see how some of the smartest and most progressive CDOs have driven change. I am sharing some of their high-return practices we can all apply to integrate data analytics and create a vibrant data culture.

To create a data culture, some executives have championed centralized, top-down models that entail substantial investments in data analytics talent, datasets, and software that are deployed across the enterprise. Others have encouraged decentralized approaches in which business units are encouraged to pursue their own initiatives, with the expectation that their success stories will encourage emulation around the company.

CDOs have navigated both of these worlds — with mixed results. With centralized models, business units can be slow with take-up, so data initiatives risk losing executive sponsorship. With decentralized approaches, the success stories are often seen as insignificant or not relevant to other parts of the business. “Centralization and decentralization is something I struggle with every day,” said one CDO at our roundtable.

What I learned in our workshop is that creating a data culture entails boosting access to and demand for data — both a push from the center and a pull from business units. NFL Chief Data and Analytics Officer Paul Ballew argued for a push and pull model that essentially serves a human resources function: Corporate funding and executive support back a central team of data science and process experts that serve as internal consultants who coach and nudge. Similarly, Caroline Nealon, Vice President, Product Data Management & Analytics at Ameriprise Financial, views her team as an enabling organization that promotes new behaviors across the enterprise.

In this model, business units — not the CDO — are accountable for showing financial results from investments in data analytics. That means all key departments must have at least a basic level of data literacy, said Sreeram Potukuchi, Enterprise Data Director at Republic Services, to ensure robust collaboration with the central data team and ensure the data projects’ business relevance. At a minimum, departments at least need to know what kind of assistance to pull from the center so they can pursue more transformational projects as they build their data literacy muscles.

Here are some high-return practices data leaders can use to foster a push-and-pull data culture.

CFOs repeatedly tell me that data is essential to business planning and success while also relating their challenges of building data literacy and a data culture. Push-pull collaboration can address that.