Operational Digital Twin: see how the operation creates or loses value
A data-informed model of selected business operations: people, workflows, systems, costs and volumes. It has two roles. During the Margin Leakage Diagnostic, it supports decisions when a finding spans several processes or resources. After it, it can serve as an operational model for planning and control. Either way, the sequence is the same: see how the operation creates or loses value, simulate the economics of a change, and fund it only where justified.
What an operational digital twin means
An Operational Digital Twin is Aigenrix's working model of how a business actually operates — the people, workflows, systems, costs, volumes and constraints involved — built from actual operational evidence and data to test likely causes and simulate changes before implementation. It is not a real-time 3D simulation of the company: it is a structured model scoped to the decision it needs to inform.
What it does not mean
It is not a universal, always-on platform, and not every engagement needs one. It is not a replica of physical equipment or an IoT/sensor platform either — the object being modeled is the operation, not a machine. Depending on the client, the model can range from a focused process-and-cost map of a single workflow to a more sophisticated multi-workflow simulation. We scope it to the decision it needs to inform, not the other way around. Its simulations are scenario estimates under stated assumptions: not predictions, and not proof of a business case.
What the model is built from
Business process modeling
The actual sequence of steps, handoffs and decision points in the workflow — as it runs today, not as the org chart describes it. We combine that process model with cost and volume data to show how the system behaves, not just how the process looks on a diagram.
Cost mapping
Labor cost, tooling cost and overhead allocated to each step, so the model can price a change before it happens.
Capacity mapping
Volumes, throughput and where the workflow is constrained — the bottleneck that actually limits output.
Questions the model can help answer
What happens to capacity and cost if a workflow is redesigned?
Which bottleneck appears if lead or order volume grows by 50%?
What happens to unit economics if a pricing, policy or process rule changes?
Which change addresses the constraint that actually limits output?
Where would automation, if anywhere, change the economics, and by how much under stated assumptions?
What payback period do those assumptions imply?
Where could a change create new operational or security risk?
The model keeps informing decisions after the Diagnostic
Where an operational model is useful beyond the Diagnostic, it becomes a planning and control tool. Candidate changes (pricing, policy, process or automation) are compared by expected economics, implementation cost and risk, so the first change funded is the one with the strongest evidence-supported case, not the one that is easiest to demo.
AI & Workflow Automation →Not sure if your operation needs a digital twin?
Every engagement starts with the economics. The Review establishes whether there is a case worth analysing — and whether modelling the operation would ever be justified.
30 minutes, free and without obligation. We look at your situation and decide together whether a paid next step makes sense.