Digital Twins Help Burg Group and Brenntag Explore Supply Chain Scenarios

Digital twins could help supply chain teams test operational choices that are difficult to assess using disconnected planning tools. At Supply Chain Media’s first Digital Twin Demo Day, five suppliers showed applications ranging from production scheduling to network design. Participants from Burg Group and Brenntag came looking for ways to make better use of data and examine more scenarios without overloading their planning teams.

The demonstrations also showed that “digital twin” covers different capabilities. Some tools focus on specific operational decisions; others support network design or connect process performance to its underlying causes. For companies considering the technology, matching that scope to the questions they need to answer may matter as much as the ability to run scenarios.

Five approaches to planning

Sophus demonstrated a tool for production planning. It can help users assess which products to make on each production line and when, whether an extra shift makes sense, and how to keep that shift fully used. The questions connect production schedules with capacity and utilization decisions.

4flow showed a different application: planning responses to supply interruptions. If a supplier has production problems or a port closes because of a strike, the tool presents options such as waiting, using air freight or changing suppliers. An AI agent can carry out a selected scenario without human intervention, according to the demonstration.

Optilogic’s digital twin began as a network design and optimization tool, but is also being used for tactical and operational questions. Its agentic AI capabilities let users build scenarios and stress-test plans. One example asked how a 30% rise in Brazil’s coffee purchase price would affect sourcing, and when supply from Ethiopia might become worthwhile.

Konekti, a start-up rooted in process intelligence, examines both supply chain performance and the processes that produce it. A stock shortage, for instance, might trace back to a late delivery, while the delay could result from systems calculating an inaccurate delivery time. The twin can show the potential effect of using the actual delivery time in future planning.

Hack and Craft presented a model that draws on computational biology methods instead of operations research optimization. The company developed it at pallet supplier Chep’s request and worked with Germany’s Max Planck Institute. Chep used the tool to optimize its European network, achieving a reported 17% cost saving.

Burg Group weighs production trade-offs

For René Nota, group supply chain manager at Dutch vinegar and syrup producer Burg Group, the main appeal is the chance to examine planning options more efficiently. The company operates seven production sites: six in Europe and one in the United States. Most vinegar is bottled or canned for major retailers across Europe; the remainder goes in bulk to food industry customers. Syrups are also bottled at the company’s Ter Aar site in the Netherlands.

Burg Group mainly produces private-label goods, so operating efficiency and cost control are central to its planning. Growth and repeated supply chain disruptions have added complexity. The company uses Oracle’s JD Edwards ERP system and is considering an upgrade to its sales and operations planning tool, but much of production planning still happens in separate systems.

That fragmentation makes it time-consuming to bring together the data needed to compare alternatives. Planners must balance production sequence, batch size and changeover time. Longer production runs can reduce changeovers, while shorter runs may lower storage costs. Nota said the team can work through these choices today, but linking data across systems takes time that planners don’t have.

The demonstrations showed Nota that digital twins can combine information such as production speeds, storage costs and output per shift, then run scenarios and propose options. He saw differences in emphasis across the suppliers: one tool focused mainly on transport networks, while others addressed practical operational questions. One appeared to fit Burg Group’s requirements particularly well because it could also support strategic planning.

That strategic use includes deciding which factories should make which volumes. Burg Group serves retail and industrial customers with multiple locations across Europe, giving the producer some flexibility in assigning production. Nota said the company wants to make better use of that flexibility and reassess its production network more often. The aim is to keep growing with the current planning team by equipping it with tools that can handle more of the analysis.

Brenntag examines its 600-site network

Brenntag, a distributor of chemicals and ingredients, is also looking for ways to get more value from its network. Its 600 sites worldwide blend products and fill them into intermediate bulk containers, drums and cans. The network is fragmented, with many locations operating mainly at a local level.

Bastiaan Jonkhoff, senior director of supply chain services programmes at Brenntag, said the company began a supply chain transformation at the start of the year. One goal is to improve how it uses its existing facilities. Historically, the organization has focused more on procurement, sales and product management than on managing the flow of goods. Jonkhoff said Brenntag lacks tools to analyze how products should move through the network and has work to do before it can make those decisions consistently using data.

Brenntag runs several ERP systems around the world and prefers to avoid moving everything into one global system. The planning question is how to divide responsibility between central and local teams: which decisions should be made centrally, which belong closer to individual sites, and where decision-making should sit. Jonkhoff sees digital twins as a way to help explore those questions alongside operational scenarios.

Putting scenario analysis closer to operations

Jonkhoff found all five demonstrations interesting, but said Brenntag will need time to determine which tool best fits its needs. He was particularly struck by how users could interact with the models and examine many scenarios with a few clicks, compared with traditional advanced planning systems.

The technology also raises an organizational question: who should develop the scenarios? Jonkhoff described a conventional model in which a central team of specialists formulates optimization questions and translates the answers into recommendations. But staff close to daily operations may have a clearer view of actual bottlenecks and could frame more useful questions themselves. Giving them access to a digital twin could change how planning work is shared, though Brenntag has yet to determine what that would mean for its supply chain organization.

For both companies, the next step is to connect the technology’s scenario capabilities to specific planning decisions. Burg Group is weighing production runs and factory assignments; Brenntag is examining how to use a geographically dispersed network and locate decision-making. The demonstrations suggest that the practical value will depend on whether the tools can bring together usable data and help the people closest to the work test choices at the right level.

Source: Supply Chain Movement