In manufacturing, digital twins have become indispensable. A virtual replica of a physical asset—updated in real-time with sensor data—enables predictive maintenance, optimization, and simulation.
But what if you could create a digital twin of something more complex than a machine? What if you could create a digital twin of your entire organization's operations?
From Physical to Operational
A traditional digital twin mirrors a physical asset. Sensors capture temperature, vibration, position, and other metrics. The virtual model reflects the physical reality.
An operational digital twin mirrors something different: how work flows through your organization. Instead of sensors, it uses conversations and system connections to capture:
- Processes and workflows
- Decisions and handoffs
- Teams and responsibilities
- Information flows and dependencies
Why It Matters
Manufacturing digital twins provide value through visibility. When you can see what's happening inside a machine, you can optimize its performance.
Operational digital twins work the same way. When you can see how work actually flows through your organization, you can:
- Identify bottlenecks before they cause problems
- Understand the impact of changes before you make them
- Preserve institutional knowledge even as people come and go
- Enable intelligent automation that understands context
The Conversation Connection
Physical digital twins rely on sensors. Operational digital twins need a different data source: the people who do the work.
AI-powered conversations can extract operational knowledge at scale. When an AI interviews your team, it captures:
- How processes really work (not just how they're documented)
- The context and reasoning behind decisions
- The informal practices that make things function
- The friction points that slow everything down
This becomes the data source for your operational digital twin—continuously updated as conversations reveal changes and evolution.
Continuous vs. Point-in-Time
Traditional process documentation is a snapshot. An operational digital twin is a living model.
As your organization evolves, the twin evolves with it. New conversations reveal changes. System connections surface discrepancies. The model updates automatically.
This isn't just convenience. It's the only way to maintain accurate operational understanding in a dynamic organization.
The Business Case
The value of operational visibility compounds over time:
- Day 1: See how your organization actually works
- Month 1: Identify and address hidden friction
- Quarter 1: Make informed decisions about changes
- Year 1: Build institutional knowledge that outlasts any individual
Every insight builds on what came before. Every improvement compounds.
Getting Started
Creating an operational digital twin doesn't require massive upfront investment. It starts with conversations—AI-powered interviews that capture how work happens.
From there, the twin grows organically. Each conversation adds detail. Each system connection adds context. The model becomes more valuable over time, not less.
This is the future of operational understanding: not static documentation, but living models that evolve with your business.
