Creating A Data Culture: Tips From The Pros

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.

Culture change requires both a push and a pull

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 of 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.

  • Bring business-line data leaders into the central data analytics group to serve as push-pull channels with business units.
  • Embed data leaders from the central office in the business units.
  • Build data literacy and promote push-pull collaborations with rotational assignments of data support teams.
  • Form an advisory council to demonstrate value delivered, ensure accountability, and keep the CEO and board of directors informed of the often disparate, yet strategic, long-term initiatives.

Finance is a great first customer

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. “To create a data-driven organization, we’ve found that Finance is a great place to start,” said Sandeep Davé, Chief Digital & Technology Officer at CBRE.

Finance teams are swimming in data and constantly seeking to reduce paperwork, lower costs, and drive efficiencies. In their drive for transformation, CFOs are especially predisposed to seek opportunities to engage data specialists to streamline operational reporting and manage and understand the data they generate. Accounting teams, internal audit, and tax departments are also ripe for automation. For such scenarios, “We give them tools,” says Potukuchi.

I believe that the business planning process is another great opportunity for boosting data literacy and changing the culture of the company. To this point, Ravi Prasad, Global Head of Data and AI Strategy and Operations at Novartis, noted that CIOs have been partnering with CFOs to reinvent business planning—especially in organizations where the planning process is especially complex. CDOs, then, have an opportunity to get in the game. Indeed, Ballew noted, CDOs increasingly report to CFOs.

But CBRE’s Davé adds that it is also important to look beyond Finance: “You have to expand your reach to serve all constituents—people and operations—to improve data availability and accuracy.”

Consider these high-return practices for building data literacy and a data culture in the finance arena:

  • Pay attention to time horizons. Creating a data culture, like any transformation, is a long-term journey. But business units work in the context of quarterly reporting and P&Ls. Multiyear, multimillion-dollar big data projects will be cut back if they aren’t seen as delivering at the speed of business. Instead, undertake practical near-term projects to build trust and momentum, says Prasad. “It doesn’t have to be extreme AI or rocket science.”
  • Speak the language of business. Potukuchi put it this way, “Big data, small data, who cares?” Instead of talking about your technical wizardry, tell stories about business outcomes in terms of operational productivity, cost reductions, consumer contentment, and revenue growth. Sponsors and partners need to clearly understand what they are gaining from their investments.

Leverage your burgeoning data culture as a talent magnet

Data on the Great Resignation shows that part of the upheaval is due to workers’ desire for more engagement and impact at work—what Mike Clementi, EVP of Human Resources at Unilever, has termed “The Great Exploration.” But gaining one or both doesn’t necessarily require leaving one’s job or company, especially if the company is digitally native. If it isn’t, the company will struggle to attract and retain tech talent, because young workers don’t want to be saddled with old-school methods. They want to work with the latest tech platforms and rich data. And they want to make a difference.

Since talent is one of the most challenging pain points for CDOs, data leadership presents great opportunities for aspiring and entrepreneurial workers to get engaged and transform the business. When data leaders tell interesting stories—in team meetings, town halls or newsletters—they can engage with and reel in entrepreneurial talent from across the enterprise.

For CEOs and boards, fostering data literacy and creating a data culture should be thought of as a means of long-term value creation. That said, data-driven transformation need not require the hiring of large teams of expensive data scientists. Instead, retain the talent you already have through upskilling programs. Constantyn Chalitsios, the CDO at Westlake Chemical, recommends fostering “citizen data scientists” across the firm through experiential learning.

To attract talent, data leaders can use these high-return practices:

  • Adopt a clear and compelling data literacy mission that connects with people’s desire for impact. CBRE’s Davé said, “We’ve declared that our objective is to ensure our clients and service professionals have the right insight at the right time.”
  • Use every opportunity to talk about your mission—such as in team meetings, in company newsletters and at town halls. “Engage people and create a spark that makes them think: ‘Hey, this is something I want to be a part of and where I can contribute,’” said Chalitsios.

For years, CDOs have struggled to awaken their organizations to the criticality and power of data to transform business. The tricks they have learned along the way can help us all.

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