Case Study Overview
A mid-sized biotech was implementing a new large-scale AI technology to optimize clinical trial operations, including site selection and enrollment forecasting. The Chief Technology Officer used the Capacity Check tool to understand if the organization was prepared for the new technology adoption.

Generated Insights
Using the tool, leaders saw that while teams were open to new tools and capable of executing, the pace of work was starting to strain the organization. Pushing AI adoption faster would likely increase burnout.

Recommended Action & Impact
Leaders paused-lower priority work and addressed staffing gaps before expanding AI use, stabilizing delivery, reducing attrition risk, and protecting key talent.

The Value
AI adoption stayed on track, delivery stabilized, and attrition risk dropped. The tool helped leaders address workforce risks early, avoiding costly rework and talent loss.

Case Study Overview
A professional services firm had low turnover and steady delivery, but growth had flattened. Senior leaders worked with Aktum Group to understand whether this was a temporary slowdown or a pattern that would persist.

Initial Results
The tool showed that strategy felt vague and feedback arrived too late to change outcomes.

Initial Recommendation
Leaders narrowed priorities, clarified ownership, and introduced regular, outcome-focused check-ins to provide actionable feedback.

Tracking Over Time
After the initial changes, leaders used quarterly pulse surveys to track whether clarity and feedback were improving. The pulses showed faster decision-making and clearer priorities, leading to improved utilization and revenue growth without adding headcount.

Case Study Overview
A healthcare system was preparing for a major organizational shift with new operating changes. The Chief Strategy Officer knew some clinical and operational teams could absorb change quickly while others would struggle, but didn’t want to rely on anecdotes without data.

How the Insights Helped
Leaders reviewed results by service line, role, and location to see where where gaps would slow progress or create unnecessary strain during the transformation.

Data-Driven Decisions
Rather than pushing change uniformly across the system, the CSO sequenced the rollout. Teams that were ready moved first, while targeted support was put in place for areas needing clearer priorities, ownership, or feedback before additional change was introduced.

The Business Impact
Change moved faster where it could, and more smoothly where it needed support. The organization avoided stalled initiatives and reduced disruption to patient care, and protected key talent, improving the return on its transformation investment.