Transforming research operations through design thinking

Problem

A high-volume research team had normalized operational friction so completely that inefficiencies were invisible—costing 35% of processing time and undermining research quality at scale.

Solution

Applied design thinking to operations: diagnosed pain points with data, designed an integrated system (tooling + processes + capability-building), and managed change as a design problem.

Impact

30% efficiency gain, 16% improvement in analysis speed, consistent quality across 200+ monthly interviews, and a scalable operation that transformed research from liability into competitive advantage.

Normalized friction, compounding cost

I inherited a high-volume research team delivering 200 interviews monthly — but the operation was chaotic. Inadequate tooling necessitated manual workarounds. Non-standardized processes produced inconsistent quality. The team had adapted to inefficiency so completely they’d stopped seeing it as a problem that could be solved.

The cost? More than 300 hours lost every month to inefficiencies. Analysts were spending hours on tasks that should have taken minutes. Most critically: the team couldn’t scale without burning out, and executives were losing confidence in research insights.

Treating operations as a design problem

I applied the same evidence-driven approach I use when designing a product or service strategy. First, I diagnosed: conducted team interviews, tracked efficiency metrics, and mapped pain points and workarounds. I built a data-driven business case that made the invisible visible.

Then I built a roadmap with workstreams to implement the following:

Integrated tooling that eliminated manual data transfer and painstaking tabulation
Standardized protocols and templates that reduced facilitation errors by 6%