What is a supply chain digital twin?
A supply chain digital twin is a working model of your real supply chain, fed with your own data, that you can use to test decisions before you make them. It represents suppliers, sites, stock, routes, lead times, costs and constraints, and it changes when the real operation changes.
The animation on our home page shows the idea: a port and its digital twin through a year of weather. The forecast warns of a storm hours ahead, the twin shows which cranes stop or lose power, and the plan adjusts before cargo is late.
What is a digital twin good for?
- Testing disruptions: a supplier fails, a route closes, a storm stops a port, demand jumps.
- Comparing options: more stock or a second supplier, near-shore or offshore, one site or two.
- Planning under uncertainty: running many possible futures and finding the decisions that hold across them (see decision support).
- Seeing the current state: one picture of stock, orders and risks instead of many spreadsheets.
How we build one
Start with the decision
We agree which decisions the twin must support and who will use it.
Model what matters
We build the model from your data and our operations research methods, at the level of detail the decision needs, no more.
Connect the data
Existing systems first; where information lives in documents, MaiMai can structure it.
Test and calibrate
We check the twin against what actually happened before anyone relies on it.
Hand over and support
Your team uses it for real decisions, with the assumptions visible and governance built in.
Why Building Resilience
Our background is optimization under uncertainty and practical implementation: stochastic optimization with genetic algorithms, early warning analytics, and procurement and supply work that delivered measured results. A digital twin is how we bring those methods into everyday decisions.
Talk to us about a digital twin.
Questions people ask
What is a digital twin of a supply chain?
A digital twin is a working model of a real supply chain that is kept up to date with real data. Because it behaves like the real thing, you can run "what if" questions on it, such as a supplier failing, a port closing or demand doubling, without risking the real operation.
What is the difference between a digital twin and a simulation?
A simulation is a model you run for a study. A digital twin is a model connected to live or regularly refreshed data, so it reflects the current state of the operation and can be used again and again for day-to-day decisions.
What do you need to start a digital twin?
Usually less than people expect. Start with the decision you want to improve and the data you already have, such as orders, stock, supplier lead times and costs. Missing data can be estimated and refined; document-heavy data can be structured with tools like MaiMai.