Results
Our engagements are designed to produce measurable, sustained improvements. These are representative outcomes from completed engagements.
Case Studies
Challenge
A mid-size pharmaceutical manufacturer was missing batch release targets by an average of 4 days, creating downstream production delays and regulatory risk.
Approach
We installed a capacity model with workload leveling, redesigned the daily management rhythm, and introduced constraint-based scheduling to restore flow. Standard work was reframed around right-first-time controls. Visual management boards gave supervisors real-time line-of-sight into performance at the bench.
Results
Challenge
A hospital network was experiencing high variability in pathology turnaround times, with outlier samples regularly exceeding clinical thresholds and generating escalations.
Approach
We mapped the demand and capacity model across all three sites, applied workload leveling to smooth volume spikes, and installed a tiered daily management system with visual management boards. Shift handover protocols were redesigned around standard work principles. A digital performance dashboard gave site managers real-time visibility into flow and constraint status.
Results
Challenge
A large food manufacturer's analytical laboratory was consistently unable to keep pace with production, creating hold-time risk on perishable product and significant waste.
Approach
We built a demand-capacity model linked to the production schedule, applied leveling to smooth sample arrival patterns, and redesigned prioritization to restore flow. Standard work was installed for sample prep and testing sequences. A daily management rhythm with visual management boards connected lab performance to production outcomes.
Results
Challenge
A high-volume clinical reference laboratory had reached an apparent capacity ceiling. Headcount had grown 22% over three years with no corresponding improvement in throughput. Unplanned overtime was chronic, waste was embedded in every shift, and leadership was preparing a capital case for facility expansion. The constraint was not space or headcount — it was how both were being used.
Approach
We built a demand-capacity model mapping specimen arrival patterns by hour, day, and day-of-week across a 12-week baseline. The model revealed that staffing peaks were misaligned with actual demand by an average of 2.5 hours per shift, and that significant analyst time was being consumed by non-value-adding activity — redundant checks, informal rework loops, and handover reconstruction. We redesigned shift start times, stagger patterns, and skill deployment across pre-analytical, analytical, and post-analytical phases. Waste was mapped and eliminated at the method level. Standard work for shift handover was installed to eliminate the information loss that was forcing incoming shifts to restart work already in progress.
Results
Every engagement begins with a direct conversation about your operating environment, constraints, and objectives. No templates, no pre-packaged solutions.