Across the financial services sector, data silos remain one of the biggest barriers to growth, innovation, and AI adoption. Traditional, top-down transformation projects often stall under the weight of politics, legacy systems, and organizational resistance.
This article explores a different path: how a bottom-up approach, focused on quick wins and scalable practices, can unlock faster value and build momentum for lasting change. Drawing on the experience of 7N consultant Pawel Konas, it shares practical lessons from a European paytech that achieved a 360° customer view, reduced manual reporting by 70 percent, and turned data skeptics into advocates.
Starting small to build momentum
Systems like HubSpot, SAP, and Zendesk weren’t speaking to each other. Teams lacked a unified view of customers and even struggled to answer basic questions such as: How many transactions did we process this month?. Reporting lived in spreadsheets and took too long. Previous transformation attempts had left leaders skeptical and teams defensive.
Recognizing these challenges, Pawel found an alternative approach. Instead of launching yet another massive program, he started with a small, data-oriented team that had room to experiment. Their first step was to work with Zendesk ticketing data, because it was simple to integrate and low risk. “I focused on the team that had the lowest amount of existing maintenance and requirements… they had time to work on something new,” Pawel explains. Many members were new to the company, which meant less resistance to fresh approaches.
Early progress caught attention, and soon another division reached out asking to join. The shift from push to pull had begun.
Building trust with quick wins
To deliver results fast and build momentum among teams, Pawel avoided the most complex systems. The team began by combining ticket data from Zendesk with internal transaction events. On its own, ticket volume only showed complaints. Combined with drops in transactions, it revealed something more powerful: customers moving their payments to competitors.
The first dashboards were ready in a span of four to five months. Reliability was key. “We made sure to include observability monitoring and lineage history… the piece we wanted to show had to be good.” Even if the scope was small, people began to trust the numbers.
Before the change, multiple people stitched together spreadsheets by hand. Errors were common, and reports appeared only once a month. With automated pipelines, manual effort dropped by roughly 70 percent. Critical reports could run daily. As the platform matured, real-time processing meant teams could see live statistics as transactions happened.
“For a lot of technical stakeholders, it was fun just to work with a modern approach,” Pawel reflects. Motivation rose as teams saw their work directly improve business insight.
70% less manual reporting
The impact was immediate. Automated pipelines cut reporting effort by about 70 percent, reducing manual work. Teams no longer spent hours stitching together spreadsheets; instead, they could focus on interpreting insights and acting on them.
Scaling without chaos
As demand grew, the risk was creating new silos. The team avoided this by establishing naming conventions, documenting design choices, sharing reusable components, and offering peer upskilling sessions. It was not just about handing over documentation but about transferring understanding.
Navigating the human side
Some source teams were initially defensive, worried about scrutiny or losing control. “In some of those teams, there was a high level of insecurity and a defensive approach,” Pawel says. Quick, highly visible, practical benefits helped overcome resistance, and leadership support unblocked the toughest cases. Small wins became cultural turning points.
The solution integrated previously isolated data, and the organization gained a true 360° customer view for the first time. New behavioral patterns surfaced, which improved sales targeting and customer success interventions. Reporting time fell sharply. Most importantly, attitudes shifted.
"People finally understood that data is important and not just a side product of running applications."
- Pawel Konas, 7N Consultant.
Every organization is unique, yet the pattern holds. Work closely with the domain, tailor the tooling, respect the culture, and make the first wins undeniable.
Start small and stay focused. Big-bang programs rarely survive shifting requirements and politics.
Prove value quickly. Deliver something usable in months, not years.
Let demand pull. When results are visible, teams ask to join.
Scale with structure. Standards and reusable components prevent fragmentation.
Choose tools that fit the team and the moment. Favor platforms that reduce toil today and scale tomorrow.
Build the foundation before AI. Without a reliable data platform, AI adds little more than a demo.
If your organization is wrestling with silos, slow reporting, or stalled transformation, this bottom-up approach offers a proven way forward. 7N brings deep experience in partnering with clients to deliver value quickly, grow adoption responsibly, and avoid political deadlocks.
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