Scaling Research Across a Large Enterprise: What Worked and What Didn’t

By Philip Burgess | UX Research Leader

Scaling research in a large enterprise is a complex challenge. Many organizations struggle to maintain quality, consistency, and impact as they expand their research efforts across multiple teams and departments. This post explores practical lessons learned from scaling research in a large company, highlighting what strategies succeeded and which ones fell short. Whether you lead a research team or collaborate with one, these insights can help you build a more effective research function at scale.

Teams collaborating in a large open workspace

Building a Centralized Research Function

One of the first steps in scaling research is deciding how to organize the function. Many enterprises start with decentralized research, where individual teams run their own projects independently. This approach allows flexibility but often leads to duplicated efforts and inconsistent methods.

Creating a centralized research team helped improve coordination and quality control. This team acted as a hub for best practices, tools, and training. They also managed a shared repository of research findings accessible across the company. Centralization made it easier to:

• Standardize research methods and documentation

• Share insights quickly across teams

• Allocate resources efficiently to high-impact projects

  
  

However, centralization also introduced challenges. Some teams felt disconnected from the central group and worried their specific needs wouldn’t be prioritized. To address this, the centralized team established clear communication channels and regular check-ins with individual teams. They also embedded research liaisons within key departments to maintain close collaboration.

Investing in Scalable Research Tools

Scaling research requires tools that support collaboration and data management. Early on, the company relied on spreadsheets and shared drives, which quickly became chaotic and hard to navigate. Investing in dedicated research platforms made a big difference.

The chosen tools enabled:

• Central storage of research data and reports

• Tagging and search features to find relevant insights fast

• Integration with project management systems to track research requests and progress

  
  

These tools reduced time spent on administrative tasks and helped maintain a single source of truth for research knowledge. Training sessions ensured all researchers and stakeholders could use the platforms effectively.

Training and Developing Research Skills Across Teams

As research expanded, not all teams had experienced researchers. To maintain quality, the company launched a training program focused on core research skills such as interview techniques, survey design, and data analysis.

The program included:

• Workshops led by senior researchers

• Online modules for self-paced learning

• Mentorship pairing for hands-on guidance

  
  

This approach helped raise the overall research competency and empowered non-researchers to conduct basic studies independently. It also freed senior researchers to focus on complex projects and strategy.

Balancing Speed and Rigor

Large enterprises often face pressure to deliver research insights quickly to support fast decision-making. Early attempts to speed up research sometimes sacrificed rigor, leading to unreliable results and poor decisions.

The company learned to balance speed with quality by:

• Defining clear research goals upfront to avoid unnecessary work

• Using rapid research methods like guerrilla testing for quick feedback

• Reserving in-depth studies for critical questions that require thorough analysis

  
  

This balance ensured research remained trustworthy while still meeting business needs for timely insights.

Researcher analyzing data on laptop with charts and notes

Encouraging Cross-Team Collaboration

Scaling research is not just about expanding capacity but also about connecting insights across the enterprise. The company fostered collaboration by:

• Hosting regular research sharing sessions where teams presented findings

• Creating cross-functional research projects involving multiple departments

• Encouraging open feedback and discussion on research outcomes

  
  

These practices helped break down silos and ensured research informed broader company strategies.

What Didn’t Work

Some strategies did not deliver the expected results:

• Over-centralization created bottlenecks and slowed response times. Teams needed more autonomy to run quick, targeted studies.

• One-size-fits-all processes failed to account for different team needs and project types. Flexibility was necessary to adapt methods.

• Ignoring cultural differences across departments led to resistance. Tailoring communication and involvement helped increase buy-in.

  
  

Learning from these missteps was crucial to refining the approach.

Moving Forward with Scaled Research

Scaling research across a large enterprise requires a mix of structure, tools, training, and culture. Centralized coordination combined with team autonomy creates a strong foundation. Investing in scalable tools and skill development supports quality and efficiency. Balancing speed with rigor ensures insights are reliable and actionable. Finally, fostering collaboration connects research efforts and maximizes impact.