Breaking Silos: Lessons Learned from Cross-Functional Collaboration

The Challenge: Bridging the Gap Between Teams

When I first took on the challenge of leading cross-functional initiatives in Provider and Enrollment, I quickly realized that technical expertise alone wouldn’t be enough. Aligning teams with different priorities, bridging communication gaps, and maintaining momentum was tougher than I had expected. Some things worked, some didn’t—but every challenge brought a valuable lesson that shaped my approach to collaboration. This is the story of what I learned and how I transformed these challenges into opportunities.

Lesson 1: Align on a Shared Vision

One of the biggest roadblocks in cross-functional collaboration is misalignment. Each team has its own objectives, and without a common vision, efforts become fragmented. This became evident when I led the strategic transformation of the Marketplace Enrollment and Billing platform. The legacy system struggled to handle growth, and while engineers wanted to improve scalability, the business team prioritized new feature development.

To overcome this, we brought together engineering, business, and DevOps teams to define a North Star vision—a scalable, efficient platform capable of processing 5.6 million members seamlessly. By aligning priorities, we eliminated bottlenecks and created a system that improved throughput and member satisfaction.

How to Influence and Align Priorities

• Speak the language of different teams: Engineers focus on scalability, business teams on revenue, and operations on stability. Tailoring the message to address their concerns helps build buy-in.
• Use data to drive decisions: Performance metrics, cost implications, and user impact keep discussions grounded in facts.
• Find common ground through OKRs: Aligning on Objectives and Key Results (OKRs) ensures everyone contributes to overarching goals.
• Build coalitions of champions: Identifying key influencers within each team can drive decisions forward more effectively.

By implementing these strategies, we created alignment across teams, setting priorities that balanced both technical feasibility and business impact.

Lesson 2: Build a Culture of Open Communication

Cross-functional collaboration thrives on clear and structured communication. In my role leading the Provider Architecture team, we needed to modernize our provider data pipeline, but teams were struggling to understand each other. Engineers were focused on performance, while business teams were more concerned with regulatory compliance.

To bridge this gap, we introduced:

• Regular sync meetings with defined agendas to discuss progress, risks, and dependencies.
• Structured documentation to ensure that architectural decisions and business requirements were easily accessible.
• A transparent decision-making framework where trade-offs were openly discussed, fostering trust between teams.

By prioritizing open communication, we reduced friction, accelerated decision-making, and delivered a scalable provider data pipeline without delays or misunderstandings.

Lesson 3: Embrace Agility and Iteration

Perfect solutions don’t exist—only evolving ones do. A great example was the development of WorkQueue, a task lifecycle management system for handling fallouts in the EMBARK platform.

Initially, we explored Red Hat PAM for workflow management, assuming its rule-based approach would streamline exception handling. However, as we delved deeper, we realized it was overly complex, adding unnecessary layers of configuration and maintenance.

Rather than forcing a tool that didn’t fit, we pivoted to a simpler, API-driven solution using Go, Kafka, and MongoDB. This allowed us to build a system that was lightweight, scalable, and easy to integrate. The iterative approach also meant we could quickly validate assumptions, collect feedback from business teams, and refine the system before scaling further.

Key takeaway? Being agile doesn’t mean rushing—it means continuously assessing, adapting, and improving based on real-world feedback.

Lesson 4: Foster Trust and Psychological Safety

During my time at WellCare, I was part of a pilot machine learning team with eight members. Coming from an enterprise web services background, I understood the data well—80% of applications at WellCare relied on our services. However, I was new to machine learning, and the lack of familiarity could have been a major barrier.

Instead of hesitating to ask questions or fearing that I’d slow the team down, I took a different approach:

• Leaned on the team’s expertise and recorded knowledge-sharing sessions.
• Engaged in continuous learning, reading ML resources and discussing challenges openly.
• Developed an application that could determine handwritten text in prior authorization requests using a predefined TensorFlow model.

By creating an environment where I felt safe to learn, I was able to contribute meaningfully, reinforcing a critical lesson: Psychological safety fuels innovation. Teams that feel empowered to ask questions and seek collaboration unlock new levels of problem-solving and creativity.

Lesson 5: Metrics Matter—Measure and Celebrate Success

Collaboration without measurable outcomes is just an exercise in goodwill. When leading the Marketplace Enrollment migration to OpenShift, we didn’t just track project completion—we measured impact:

• 23% reduction in infrastructure costs by optimizing containerized workloads.
• 40% increase in system efficiency, allowing faster transaction processing.
• 99.5% straight-through processing success rate, reducing manual interventions and errors.

How to Effectively Measure Success

• Define KPIs early: Establishing key performance indicators at the outset keeps teams focused.
• Use dashboards for transparency: Real-time monitoring helps stakeholders track progress.
• Celebrate small wins: Recognizing incremental achievements keeps teams motivated.
• Conduct retrospectives: Analyzing what worked and what didn’t ensures continuous improvement.

By embedding data-driven decision-making, teams not only deliver successful outcomes but also foster a culture of accountability and innovation.

What Didn’t Work: Challenges in Cross-Functional Collaboration

While successful collaboration can drive transformation, some things didn’t work:

1. Misaligned priorities stalled progress: Engineering wanted scalability, business wanted features—without alignment, execution suffered.
2. Over-engineering slowed us down: Initially choosing Red Hat PAM for WorkQueue added complexity instead of efficiency.
3. Lack of ownership caused bottlenecks: The Marketplace Enrollment migration faced delays because ownership wasn’t clearly defined.
4. Ignoring cultural differences led to friction: Teams in different regions hesitated to push back on decisions, causing misalignment.

Each of these challenges taught me valuable lessons about how to navigate and course-correct collaboration pitfalls.

Final Thoughts: The Power of Cross-Functional Teams

Breaking down silos isn’t just a buzzword—it’s a necessity for delivering scalable, high-performing systems. Whether it’s transforming legacy platforms, optimizing DevOps pipelines, or architecting next-gen cloud solutions, the most successful projects are those where teams align on a vision, communicate openly, iterate rapidly, trust each other, and measure outcomes.

The biggest lesson? Technology moves fast, but collaboration moves faster.

What are your experiences with cross-functional collaboration? I’d love to hear your thoughts!

This article was originally shared on Medium. Here is the link: https://medium.com/@rajkumarjayabalan/breaking-silos-lessons-learned-from-cross-functional-collaboration-9d001a5e1201