Sector context changes what productivity means
A productivity lever that works in a distribution centre rarely works in a claims operation. Our sector leads keep a living library of benchmarks, regulatory constraints and workforce patterns so recommendations arrive already adapted to your environment.
Productivity means something different in every industry, and a recommendation that ignores sector reality is worse than no recommendation at all. A workload model that works in a distribution centre can be actively harmful in a regulated claims operation. Each of our sector practices keeps its own benchmark library, constraint list and pattern catalogue.
Healthcare systems
Clinical support, scheduling, revenue cycle and care coordination. Constraints include licensure, shift patterns and patient-safety rules that cannot be traded away for throughput.
Financial services
Claims, underwriting support, servicing and back-office processing. Heavily regulated, audit-trailed and often burdened by legacy workflow tools nobody wants to open.
Manufacturing
Plant operations, maintenance planning, quality and supply coordination. Shift-based, unionised in places, and unforgiving of designs that ignore the physical reality of the line.
Logistics and distribution
Site throughput, driver and equipment utilisation, planning and customer service. Volumes move daily, so baselines must be built on distributions rather than averages.
Technology and SaaS
Engineering throughput, support operations and go-to-market coordination. The main friction is usually coordination overhead rather than raw capacity.
Professional services
Utilisation, engagement delivery and administrative load in firms whose product is billable time. Here the metric that matters is recoverable hours, not headcount.
What changes by sector
The unit of measurement changes first. Healthcare measures clinical minutes and cycle time. Logistics measures movements and dwell. Financial services measures touches per case and exception rate. Professional services measures recoverable hours. Manufacturing measures takt adherence and downtime. Getting the unit right is half the battle, because a metric nobody recognises as meaningful will never drive a decision.
The constraint set changes second. Regulation, union agreements, safety rules and technology debt all limit what can be redesigned, and pretending otherwise produces a plan that quietly dies at implementation. Our sector leads maintain a live list of constraints per industry so the first design session does not waste time rediscovering them.
Sectors we decline
We are deliberately not generalists. We decline work in sectors where we cannot bring a benchmark library and a practitioner who has actually operated there, including most public-sector bodies, early-stage companies below our size threshold, and industries with licensing regimes we do not know well. Saying no early is better for everyone than learning your sector on your budget.
How we build sector knowledge
Sector knowledge is not a slide we reuse. Each practice keeps a living library that we update after every engagement: benchmarks, regulatory constraints, common failure patterns and the specific vocabulary of the industry. New joiners spend their first weeks inside that library before they touch a client, because using the wrong term in a review session costs credibility faster than a wrong number.
We also decline engagements when the library is thin. If we have not worked in a sector enough to know where the traps are, we will say so, and we will either team with a specialist who does or recommend a firm that already has the depth. Expanding into a sector we do not understand would grow revenue and destroy the thing clients pay us for, which is judgement that comes from having seen the problem before.