A warehouse digital twin is a working model of your warehouse operation. It is built using live operational data and can be used to test changes virtually before committing to them, and helps businesses make better, more informed decisions about operational changes within their warehouses.
What is a warehouse digital twin?
A digital twin is a like-for-like digital version of a physical environment, such as a warehouse.
How do warehouse digital twins work?
Warehouse digital twins combine a model of your warehouse with real operational data to create a working virtual version of your warehouse. All virtual behaviours and decisions mirror real-life ones, and this virtual environment can be used to test real outcomes for new processes and help optimise warehouse performance.
What data is needed to build a warehouse digital twin?
- Inventory and SKU data
- Workflow data
- Real-time signals/data
- Performance metrics
- Warehouse layout and dimensions
- Assets and equipment information and positions
- Order data
This data is used to create a working model of the warehouse operations that reflects its current and likely future performance.
How can digital twins be used in warehouse operations?
Digital twins can be used to test decisions virtually before you commit to time, cost, and disruption on-site.
For logistics teams, this matters because the “right” solution is rarely static. Volumes shift, SKU profiles change, customer expectations tighten, and what works today can become the constraint tomorrow. A digital twin helps you move from guesswork to evidence, by modelling how your operation behaves now and how it is likely to behave in future.
Through the development of a digital twin, warehouse operators can leverage their operational data using integrated Artificial Intelligence (AI) and Machine Learning (ML) algorithms to assess existing processes, impacts of possible supply chain and consumer demand changes, as well as trial new solutions for example, using automation or robotics, all in a virtual world with zero impact on operational downtime.
Core applications of digital twins
Digital twins can provide evidence-based solutions for warehouse operations, including:
- New SKU (Stock Keeping Unit) design layouts
- Workflow patterns
- New automation/robotics solutions
- Seasonal peaks
- Supply chain changes
- Processes to improve sustainability
Digital twins can be used on an ongoing basis, taking real-time data from daily operations and assessing these to provide accurate suggestions to tweak existing processes to improve efficiency and offer immediate notification of changes that could impact further. Thereby providing warehouse operators with the necessary information to remain agile and able to prepare for shifts in seasonal order processing, SKU changes or supply chain issues, as they arise.
Another valuable use of digital twins is connecting demand behaviour to the physical system sizing. The digital twin can analyse what is happening in the live order stream and split profiles where needed, instead of relying on a single blended view of demand. The split profile view enables products to be more accurately sized. This results in a more realistic understanding of capacity, throughput, and operational performance for future conditions before you commit to a design or automation route.
How SEC uses digital twins
SEC uses digital twins to bring clarity to complex automation and storage decisions, grounding recommendations in real operations and future demands, instead of vendor assumptions. Digital twinning reduces risks, improves decision quality, and ensures that your selected storage system is justified and sized against your actual operating model.
By using D.I.D.O., our data-driven AI platform, SEC can use your operational data to create a digital twin, to help provide the best solution for your business needs, and ensure that your warehouse is optimised for its current and future operations. Our case study on Professional Fulfilment Services (ProFs) provides more information about how we use D.I.D.O. and digital twins in our projects.
