Industry Analytics
Engineered decisions for complex operations.
We analyse constrained operational systems, formulate them as computational problems, and build the software that puts better decisions into production.
Most software records the world. Too little of it decides what to do about it.
Organisations usually already have data, experienced people and a stack of operational tools. What they often still lack is a way to turn constraints, uncertainty and competing objectives into a decision that can actually be executed.
Off-the-shelf products are strong at storing records, displaying status and routing forms. They are weaker when the work is allocation, sequencing, scheduling, routing, capacity or control — especially when the rules are specific to the operation.
Four kinds of work.
The same engagement can move through more than one of these. The point is not a catalogue of services. It is a complete path from problem to production.
01
Optimise
Find better decisions inside real constraints.
02
Model
Understand the system before changing it.
03
Engineer
Put domain intelligence into production software.
04
Improve
Measure what the system actually did, then iterate.
From problem to production.
Industry Analytics is brought in when the difficulty is not merely building an application, but formulating the operational problem correctly and engineering the system that solves it.
01
Analyse
Map decisions, constraints, incentives and data.
02
Model
Represent how the system actually behaves.
03
Optimise
Search for high-quality feasible decisions.
04
Engineer
Build production software around the method.
05
Integrate
Connect to the systems the operation already runs.
06
Operate
Measure outcomes and improve the system in use.
Representative problem types.
These are classes of work, not case studies. They describe the kind of operational difficulty the firm is built to take on.
- 01
Scheduling
Time, resources and rules that cannot all be satisfied by a spreadsheet.
- 02
Allocation
Assigning scarce people, assets or budget under competing demands.
- 03
Routing
Movement of work, goods or people through a constrained network.
- 04
Capacity
What the system can absorb, where it saturates, and what to change first.
- 05
Planning
Medium-horizon decisions that couple inventory, labour, production and service.
- 06
Forecasting
Demand, workload and risk as inputs to a decision — not as decoration on a chart.
- 07
Workflow
Processes whose structure, not only their interface, needs to be redesigned.
- 08
Operational control
What should happen next when the live system diverges from the plan.
- 09
Simulation
Testing a change in a model before spending it in the real operation.
- 10
Bespoke systems
Software the organisation must own because no product encodes its logic.
The method has to ship.
A model that cannot be operated is a briefing document. Industry Analytics builds the production software, interfaces, APIs and integration required to put computational decisions into the working system — and to keep them there as the operation changes.
If the problem is operationally hard, start there.
A useful conversation begins with the decision that is currently made by heuristic, spreadsheet or committee — and with the constraints that make it difficult.