Creating a Data-Driven Culture in Organizations
When we talk about data usage, many institutions rely on dashboards and reports. However, not all of them can demonstrate how these insights genuinely influence decision-making.
The key factor here is the culture within the organization. A strong data culture becomes evident when leaders prioritize data in discussions about outcomes. This leads to frontline teams feeling accountable for data quality, ensuring that decisions are based on solid information rather than mere instincts.
This theme emerged during a recent panel discussion featuring Jeremiah Lotz from Credit Union Services Organizations, John Sahagian, a chief data officer with BCU, and Richie Cotton from Data Sample. They all urged banks and credit unions to move past basic data strategies and cultivate a more impactful data culture.
“A healthy culture is connected to utilizing reliable data,” Lotz shared. “We track information and make decisions based on it. It’s about understanding how to make data a part of ongoing decision-making.”
The panel agreed on a simple principle: data strategies should be intertwined with business strategies, and it’s crucial for business leaders—not just data teams—to trust and understand how to leverage data. A significant red flag is when organizations use data merely to justify pre-existing decisions while ignoring contradictory evidence or punishing those who present inconvenient truths. Such practices do not foster the curiosity and accountability essential for a robust data culture.
BCU’s Journey Towards a Data-Driven Culture
Sahagian outlined how BCU underwent a leadership reset, emphasizing listening and collaborative work. He candidly explained the state of credit unions, noting that in 2018, BCU faced a data overload without a clear strategy. This led him to spearhead an initiative to establish a deliberate data strategy focused on building a trustworthy data culture through conversation.
“We reached out across the organization and asked, ‘What are your goals? What’s happening in your business?’” said Sahagian. “Our business leaders realized that simply hiring a data team wouldn’t solve everything. They needed to engage with the data themselves and take ownership.” This realization highlighted a shift, with leaders becoming more invested in verifying the integrity of their data.
Lotz agreed that changing mindsets requires redefining the roles of investment and data functions. The data team should act as guides, connecting insights across departments to enable the organization to thrive as a whole. It’s in this alignment that companies start to see returns on their data investments.
The panel also provided practical evaluations for executives to assess their data culture. They suggested asking leaders how they gauge success and the trustworthiness of their data. In a strong culture, leaders should be able to articulate their problem-solving approaches and justify their insights clearly. Conversely, in a weaker culture, data can become an afterthought or merely a tool used to validate predecided choices. Lotz observed that the most successful organizations view data as an asset linked to clearly defined business outcomes.
Establishing a Solid Foundation
Sahagian cautioned that having a basic structure in place is essential; without it, rapid growth can lead to compounded issues. Effective governance is necessary to ensure that processes are documented and knowledge is well-managed. He pointed out that as barriers to entry lower, the risk of errors increases without proper understanding and control.
Lotz discussed the ambassador model, designed to cultivate a culture of curiosity across the company, emphasizing the necessity of providing training and a shared language for employees to incorporate data into their work habits.
Cotton highlighted the importance of simple terminology, suggesting that understanding basic data representations can lead to more useful outcomes.
The panelists offered practical advice on nurturing data literacy throughout the organization. Cotton advocated for democratizing data, starting with a shared vocabulary to facilitate productive discussions between business and technology teams. Given the fast-paced evolution of tools, ongoing learning is essential.
When asked how data and AI might transform operations, Lotz first pointed to fraud detection. With significant losses annually in the sector, he believes fostering curiosity is key to developing new ways to detect and combat fraudulent activities. He also mentioned that AI can enhance customer experience and drive product growth, such as in digital wallets and installment plans.
BCU is tackling initiatives across three fronts. First, they revamped chatbots to handle around 40% of customer queries more effectively. Second, their personalized approach to next-best actions has shown 2-3 times higher engagement compared to traditional offerings. Lastly, a risk modeling strategy helps to streamline outreach, distinguishing between members in urgent need and those who are habitually late, allowing BCU to manage rising delinquency efficiently.
Embracing Change as a Process
Beyond fraud, the panel framed data adoption as a sequence. The results from this mapping can help establish safe procedures that automate certain tasks while ensuring human oversight in complex or uncertain areas.
Panelists noted that this approach also addresses AI hesitancy, encouraging small, manageable victories and promoting transparency around human input. Sahagian and Lotz emphasized that a grounded, high-quality system is easier to trust when monitored by knowledgeable individuals.
When participants were asked for immediate steps to enhance their data culture, they provided several actionable suggestions:
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Lotz suggested appointing “data ambassadors” with natural curiosity and allowing them to share best practices across teams. Select a modest use case to demonstrate value in real life and build momentum.
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Sahagian emphasized the need to document business knowledge and processes to create reliable, searchable contexts. He also recommended making data discussions standard in meetings and clarifying ownership of data among business leaders.
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Cotton advised using meetings to track progress with data and fine-tune the culture towards evidence. Automating tedious tasks can provide quick wins and encourage feedback from team members about their challenges.
All three leaders agreed that a strong culture is what transforms tools into tangible results. By teaching employees how to align data with business goals, organizations can build trust and drive success.
As Lotz remarked, the data team’s role is catalytic. “We are not just here to be data experts. We aim to guide and facilitate change, helping the company in meaningful ways.”
