How Digital Twins Transform Supply Chains

David Petrucci, Managing Director Global Leader of Supply Chain and Operations
Lucas Manganaro, Managing Director Supply Chain Innovation Practice Leader

What’s new: Digital twins can optimize existing supply chains and help design new trade networks. Supply-chain digital twins are now being created faster with less expensive technology and fewer eye-popping 3D graphics.

Yes, but: Harnessing these opportunities starts with correcting three common misunderstandings.

How it works: The foundational building blocks of supply chain digital twins are surprisingly straightforward in nature.

The big picture: Their value lies less in their nifty graphics and far more in the tangible insights about business trade-offs and next best actions that they produce.

Go deeper: Read our insights below.

As business leaders grapple with uncertainties related to moving operations out of China, nearshoring and other supply chain overhauls, they should consider how digital twins can optimize existing supply chains and help design new trade networks.

While digital twins are widely associated with physical assets and products (e.g., graphics-intensive digital representations of manufacturing facilities), this evolving technology also can refine and enhance processes and collections of processes. Leading practitioners are creating supply-chain digital twins – faster and with less expensive technology and fewer eye-popping 3D graphics than you might expect – to run simulations and generate insights that help them upgrade existing networks and develop new supply chain capabilities (e.g., augmenting pharmaceutical trading networks with cold-storage capabilities).

Harnessing these opportunities starts with correcting three common misunderstandings about digital twins:

  1. Digital twins are about much more than creating futuristic-looking virtual models of products, factories and systems. That impression, promulgated by some practitioners and advisors, often makes digital twins appear daunting and more expensive than they need to be. In practice, if you overlay an accurate process map with an architecture diagram, you’re well on your way to creating a basic digital twin model that will generate tangible, detailed insights regarding substantial improvement opportunities.
  2. Digital twins can improve and enhance processes as well as tangible assets. This capability is not just about building the “factory of the future;” it’s also about designing more resilient supply chains.
  3. Virtual representations of real-world environments do not solve problems on their own. The essential value of digital twins does not reside in the digital representation itself, but in the information and insights derived from putting that representation through real-world simulations and modelling.

Many companies are hungry for these types of supply chain insights because most supply chain models have yet to adapt to 21st century realities. Relatively few organizations maintain sufficient visibility across their supply chains, from inbound inventory and manufacturing through outbound inventory and distribution. At any point in time, it can be exceedingly difficult to pinpoint where a customer order resides in the network.

This lack of visibility gives rise to two weaknesses. The first is operational ineffectiveness. Providing even a basic level of customer services with insufficient supply chain visibility requires numerous manual interventions and consumes time that is better invested in higher-value activities. An overreliance on manual interventions hinders a company’s ability to respond to new business conditions and challenges in an agile manner. These limitations make it difficult for organizations to pivot in response to demand spikes, supply shortages, cross-border snafus, and other common disruptions. The second weakness relates to cost. Many companies respond to customer inquiries and supply chain disruptions by throwing people at the problems, and those labor costs quickly add up.

Supply-chain digital twins provide two key benefits – optimizing existing supply chains and helping design new trade networks. A realistic, usable twin of a supply chain network enables business leaders to model different combinations of business conditions, constraints and risk events. By running these scenarios, organizations can observe the challenges that arise and then plan how to adapt, should a particular set of conditions become a reality. Doing so allows supply chain leaders to respond quickly and cost-effectively when similar scenarios and risks materialize in reality. Every supply chain leader, CEO and board member wants to know what next best actions should be taken when bad things occur. Digital twins identify those actions.

The second category of benefits is broader and just as timely, given the pervasive need to update supply chain models to the 21st century. For some pharmaceutical companies, that means equipping manufacturing and logistics networks with cold storage. For other companies that means finding sourcing alternatives to networks in China. For many manufacturers that means designing the factory – and supply chain – of the future.

Few, if any, traditional supply chain planning tools cut it when it comes to clearing the dynamic, multifaceted hurdles related to responding to 21st-century supply chain disruptions and constructing new networks. With that said, the foundational building blocks of supply chain digital twins are surprisingly straightforward in nature (though, at times, difficult to organize, primarily due to internal hindrances):

  • Data: Substantial amounts of data, including real-time data, are needed to drive the valuable analyses and insights that digital twins produce. This data-collection work is challenging in many organizations because data resides in a tangle of different supply chain systems – order management systems, ERP systems, distribution systems, transportation management systems and more – managed by different groups and individuals. Addressing this data-collection challenge tends to require just as much, if not more, emphasis on cross-functional communications than it does on data extraction.
  • Network Diagrams: Digital twins require a physical diagram of the supply chain network – as it functions in reality vs. how it was designed to operate on paper. In most organizations, supply chains function far differently in practice than they were designed to operate in theory. Few supply chain teams know that this theory-reality gap exists, and many do not have a sufficient understanding of what their colleagues in other parts of the supply chain actually do. Some planners have never stepped foot in a warehouse. Some warehouse teams have never visited manufacturing facilities. This lack of visibility and knowledge is exacerbated by the fact that different supply chain groups rarely touch the same systems. For these reasons, creating an accurate diagram of a supply chain network can deliver dual benefits: fostering greater internal collaboration and visibility and getting a crucial digital twin enabler in place.
  • Problem Identification: Collecting the right data and accurately mapping the supply chain – which together create a “digital thread of the supply chain” – helps organizations clarify the problems they need to resolve. The vast majority of these problems boils down to lack of visibility, inefficiencies, and an inability to respond quickly to unexpected disruptions.

Getting those three enabling components in place allows organizations to make the best use of cloud-enabled digital twin technology solutions from vendors like Microsoft and others. While these solutions are powerful, their value lies less in their nifty graphics and far more in the tangible insights about business trade-offs and next best actions that they produce.

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