A Supply Chain digital twin is a virtual representation of your Supply Chain

A Supply Chain Digital Twin

Optilon Crew
Optilon
Team

Optimizing Supply Chain strategies and network designs keeps getting harder. This is where the Supply Chain digital twin comes in handy. The luxury of time has disappeared. Supply Chains must be capable of turning on a dime to match changing customer preferences and needs, disruptive competitors and economic fluctuations. In other words: Supply Chain professionals are forced to manage complex multi-network operations in a state of constant flux. In this blogpost we will describe what a digital twin is and how you can benefit from having one.

Ad-hoc tools are typically not sufficient
While most global Supply Chain reliant companies have already embraced the power of data and advanced analytics across their organizations, the vast majority have been working with out-of the box tools, cobbled together in-house applications or spreadsheetbased solutions. These approaches are often inadequate for Supply Chain managers who need to handle real-time data and complex business requirements across multiple networks or systems – all while balancing risks and trade-offs. 

What if you could instead empower your team of analysts with a fully living and breathing digital representation of your Supply Chain. A so-called digital twin, which can easily be understood and utilized for any number of functional and technological advances.

A Supply Chain digital twin – a virtual representation
Gartner refers to the Supply Chain digital twin as:” A digital, dynamic, real-time and time-phased representation of the various associations between the data objects that ultimately make up how the physical Supply Chain operates.” 

A Supply Chain digital twin is a virtual representation of real-world operations. Investments made in creating and building digital twins will pay off again and again. The live data being captured can be used in everything from quality control to inventory management. Supply Chain digital twins are also valuable because they can be analyzed and explored by various stakeholders using different types of tools. They can be used by engineering, production, and maintenance teams to experiment with new approaches and what-if-scenarios without disrupting actual production.

The data captured by Supply Chain digital twins is available to feed Machine Learning predictive models. In general, the larger and more varied the dataset being analyzed, the greater the likelihood machine learners will discover previously unknown operational patterns and aberrations. However, for machine learners to be effective, they need to be analyzing relevant data. Modern streaming architectures can dynamically filter incoming data to focus on the right data points and levels of granularity. Data from Supply Chain digital twins can also be automatically input into decision models, which capture the range of operational choices that could be made at key control and intersection points within the business. Optimizations can then be run to mathematically identify the best sets of choices – among thousands of possible decision combinations for achieving specific goals within specific operating constraints.

Easily create and test scenarios
Given that Supply Chains need to be redesigned to treat disruptions as the norm and Supply Chain Resilience, we believe that the use of Supply Chain digital twins will increase. Supply Chains can use them to create business process simulations that can be updated in real-time as circumstances change. For example, this could include finding the best way to shift production to alternate locations, move inventory to different warehouses, increase or decrease safety stocks and be better prepared overall.

Summing up, we could say that a Supply Chain digital twin allows companies to recreate their Supply Chain in the virtual world and quickly test scenarios in a risk-free manner to learn how decisions will impact the network operations. As digital twinning becomes increasingly commonplace, optimization will be widely adopted as one of the biggest prerequisites. Data availability and readiness will already be taken care of. In addition, better tools for digital twin visualization will help teams explore and understand the key drivers and trade-offs in optimized plans and decisions.

Looking for more resources on the Supply Chain digital twin?

Checkout this whitepaper – free to download.

Optilon’s Fredrik Jersby did in this webinar give a detailed description of a digital twin. Check it out here.

Our client SKF has worked with and won a gartner award for their work on the digital twin. Check out the webinar here.
You can also read about their results right here.

We had the pleasure of having Joachim Lindquist from Arla Foods join one of our webinars on Supply Chain resilience and digital twin.
Check it out here

 

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