How is Digital Twin Revolutionizing Supply Chain Management?

Digital Twin is making its mark across all industries. As a market set to reach 73.5 billion dollars in 2027, digital twins are transforming the way teams approach operations. Logistics are also tapping into this technology to refine their processes and maximize their profits.

Digital twins in supply chain management include warehouse management, supply chain mapping, and much more. If you are into logistics and lack this tech, you need to take a look at this.

It’s time to dive deeper into how logistics can help you in supply chain management. We’ll take a microscopic approach to the advantages, challenges, and potential growth of the industry in this blog.

Check it out.

Before we move forward-

For those who need a quick recap on what a digital twin is - it is a digital replica of real-life assets that you can maneuver according to your will right from the planning and designing phase. 

Now as that’s sorted, read on.

The depth of the supply chain management industry is breathtaking. Being a 22 billion-dollar industry, it's not a surprise. The complexity and range of supply chains extend across geographical borders and have a customer-centric operation.

So, when you look at it from an operations perspective, the sheer volume of data and documentation is humongous. The main challenge presented before you will be 

• Making accurate decisions and flexibility according to a live market. 

• Transporting and manufacturing conditions also pose an immediate threat to declining productivity.

• Companies find it difficult to monitor performance and detect risk factors on the go.

Here’s where digital twins make their entrance. 

It helps you create an analytic structural view of all these complex data points. In a snap driving a smooth end-to-end automation process. You are given the power to track and model activity throughout your network.

Include real-time events into your planning with the help of digital twins and model new situations and solutions. The confidence this tech gives to planners to implement changes effectively is immense.

Here are some digital twin examples to give you a better idea of how the technology is sweeping across industries. 

The scope and range of use case scenarios of digital twins vary from industry according to the needs. In logistics zeroing in on the metrics to model activity and real-time adaptations is the central need. Benefits include

Foresight 

Being able to see and predict problems before they arise is extremely useful for developing response plans and assessing risks.

A supply chain digital twin can warn of potential future issues, so logistics teams can take preventative measures before the moment arises or decide to take a different direction. Furthermore, this technology allows for the analysis of a huge volume of data and the prevention of the recurrence of existing discrepancies.

The impact of taking a risk can be seen ahead of time with digital twin models. Leadership teams can use modeling to monitor risks, test probability for emergencies, and test different scenarios to solve them. 

By modeling a situation, you can see how it will play out and impact savings, ROI, and other key metrics.

Suggested read: Preventive Maintenance vs Predictive Maintenance. 

Transport optimization

A digital twin in supply chain forecasting can assess how changes in supply and demand impact physical locations and design solutions for supporting systems.

Using real-time data collection, advanced transportation models can be developed, including where common shortages and disruptions occur. By using this software, managers are able to identify trends that they may not be able to see, which enables them to plan resources more effectively.

Instead of relying on guesswork and gut feelings for vital transportation decisions, logistics teams can model how deliveries will play out with this bird's eye view. For cold chain logistics shippers and carriers who depend on efficient transportation, this is particularly important.

Manage inventory and provide fast turnaround times 

E-commerce brands increasingly use a network of highly localized warehouses to manage inventory and provide fast turnaround times.

Supply/demand forecasting can be used with digital twins to balance backstock across a network of warehouses or to optimize inventory.

Response plan by simulating emergencies 

As natural disasters create headaches for international trade, maintaining a nimble supply chain has never been more important. 

Technology can help create plans for how to deal with a variety of disaster categories, including natural disasters and other catastrophic events, even though not everything can be predicted. 

By using digital twins, logistics teams can prepare contingency plans and scenarios before they're needed.

Before we move on to the next section, see how we help with reducing downtime with predictive maintenance.

The use cases of digital twins are many across the industry. The following are a few use cases of digital twins in logistics. Let’s take a look at what they are.

Supply chain coordination

Internal and external stakeholders, buyers, merchants, customers, finance departments, manufacturers, agents, etc., are some of the stakeholders involved in logistics. That’s a lot of hands in a cookie jar.

Managing these huge numbers of personnel for each project is hectic. One wrong move and things could go south fast. Relaying real-time information is the crux of the process. So digital twins create a single, unified view of the entire network to aid in planning and execution,

Agile planning and execution

Let’s take a look at the things that could go wrong-

• Transportation delay

• Rate changes

• Manufacturing problems

• Customer issues

These are situations where change occurs rapidly in supply chain management. Try integrating the data manually, you will mess up.

Manual information gathering and disparate systems can now be replaced with up-to-the-minute data that reflects on-the-ground conditions. How? Digital twins.

By sourcing data in real-time, and flagging threats and issues earlier gives the team a buffer time to react. It minimizes disruptions, costs, and potential stockouts by allowing plans to be adjusted.

In logistics, improvisations will be like knocking over a Domino. The need to explore a variety of options and find the optimum response is crucial. When teams receive information in advance, they can manage routing or processes to meet deadlines comfortably. 

Cost management and reduction

A change in supply chain conditions can result in extra costs, such as rebooking and D&D charges or charges for additional storage.

Teams can calculate the true cost of moving goods through the supply chain and quantify the impact of different stakeholders' actions by collating data holistically.

In the short run, you might use this view to evaluate the tradeoffs between different carriers, manufacturers, and routes to make better operational decisions. 

In the long run, planners, equipped with a fuller view of where spend is incurred, can more confidently optimize the overall cost structure of the business without harming lead times and inventory levels.

Discover the crucial role of digital twins in manufacturing.

Long-term optimization

It is difficult to build a view of past and present supply chain activities and results that can be compared when data is not captured in a structured way that facilitates proper analysis and review. 

As a result, supply chain issues go unnoticed and damage long-term performance as a result of the 'black box' that prevents progressive improvement.

A before/after analysis can be performed by standardizing historical data across suppliers, manufacturers, carriers, and internal processes.

In this way, it is easier to identify areas that may require process changes and distinguish them from one-time problems: for example, identifying a supplier that consistently delivers late or identifying a particular bottleneck from factory to port that creates inefficiencies, extra costs, and delays on a regular basis.

Improving sustainability

Businesses are under increasing pressure from customers, boards, and regulators to reduce their environmental impact. Although raw materials, manufacturing, and transportation will always produce emissions, teams can reduce any unnecessary impact by understanding the environmental costs of various suppliers and options.

By recognizing that stock levels in warehouses are sufficient to meet the demand for the next few weeks, the system can suggest ocean transportation for freight scheduled for air delivery, reducing carbon emissions and costs.

The system could reduce costs and environmental impact by rerouting goods from factories to ports instead of airports, tracking the availability of space on relevant ships, and possibly even combining goods from additional manufacturers into one container.

Even though there is a wide range of digital twin use cases, it comes with its challenges. Let's take a look.

Digital Twins are revolutionizing supply chain management by providing real-time insights, optimizing processes, and mitigating risks. However, implementing Digital Twins in supply chain management is not without its challenges. 

Following are some challenges and how you can overcome them. 

1. Data Integration and Management

One of the primary challenges in implementing Digital Twins is integrating data from various sources, such as IoT devices, sensors, and enterprise systems. Ensuring data accuracy, consistency, and security is crucial for the success of a Digital Twin.

SOLUTION

Invest in robust data management tools and establish data governance policies to ensure data quality and security. Collaborate with IT teams and data experts to develop a comprehensive data integration strategy.

See how digital twins enhance data security and privacy.

2. Scalability and Complexity

As supply chains grow and become more complex, managing and scaling Digital Twins can be challenging. Organizations need to ensure that their Digital Twin solutions can handle increasing data volumes and complexity.

SOLUTION

Choose a Digital Twin platform that is scalable and can adapt to the evolving needs of your supply chain. Work with experienced vendors and partners who can provide guidance and support throughout the implementation process.

3. Technological Expertise and Resources

Implementing Digital Twins requires specialized knowledge and expertise in areas such as data analytics, IoT, and simulation modeling. Organizations may face challenges in finding and retaining skilled professionals to manage and maintain their Digital Twin solutions.

SOLUTION

Invest in training and development programs to upskill your existing workforce. Collaborate with external partners, consultants, or vendors who can provide the necessary expertise and support.

4. Organizational Resistance and Change Management

Introducing Digital Twins in supply chain management may encounter resistance from employees who are accustomed to traditional methods. Overcoming this resistance and managing change effectively is crucial for successful implementation.

SOLUTION 

Develop a comprehensive change management strategy that includes clear communication, employee training, and ongoing support. Engage stakeholders at all levels of the organization to ensure buy-in and commitment to the Digital Twin initiative.

Also, take a look at how IoT is revolutionizing supply chain management

5. Cost and Return on Investment (ROI)

Implementing Digital Twins can be a significant investment, and organizations may face challenges in justifying the costs and demonstrating ROI.

SOLUTION

Develop a clear business case for implementing Digital Twins, outlining the expected benefits and cost savings. Monitor and measure the performance of your Digital Twin solution to demonstrate its value and impact on supply chain performance.

SOURCE: Digital Twin Market Size, Share & Trends

Digital Twins are already transforming supply chain management by providing real-time insights, optimizing processes, and mitigating risks. As technology continues to evolve, the future of Digital Twins in supply chain management promises even more.

Many emerging trends and developments are shaping the future of Digital Twins in supply chain management. 

Want to know how they will drive further transformation? Then don’t stop reading.

Integration of Advanced Technologies

The future of Digital Twins will see the integration of advanced technologies such as artificial intelligence (AI), machine learning (ML), and blockchain. These technologies will enhance the capabilities of Digital Twins, enabling more accurate predictions, automated decision-making, and secure data sharing across the supply chain.

Real-time Collaboration and Decision-Making

Digital Twins will facilitate real-time collaboration among supply chain stakeholders, enabling faster and more informed decision-making. By providing a shared virtual environment, Digital Twins will allow stakeholders to work together seamlessly, improving communication and coordination across the supply chain.

End-to-End Supply Chain Digital Twins

As organizations continue to adopt Digital Twins, we will see the development of end-to-end supply chain Digital Twins that encompass the entire supply chain, from raw materials to end customers. This comprehensive view will enable organizations to optimize their supply chains holistically, driving further efficiencies and cost savings.

Source: IoT Analytics

Enhanced Sustainability and Circular Economy

Digital Twins will play a crucial role in promoting sustainability and the circular economy within supply chains. By modeling the environmental impact of various processes and identifying areas for improvement, Digital Twins will help organizations reduce waste, minimize their carbon footprint, and transition to more sustainable business models.

See how digital twins can help with sustainable construction.

Personalized and On-Demand Supply Chains

The future of Digital Twins will enable more personalized and on-demand supply chains, driven by customer preferences and real-time demand signals. Digital Twins will help organizations respond to changing customer needs more effectively, enabling mass customization and reducing lead times.

Digital Twin-as-a-Service (DTaaS)

As the adoption of Digital Twins grows, we may see the emergence of Digital Twin-as-a-Service (DTaaS) offerings. This will allow organizations to access Digital Twin capabilities on a subscription basis, reducing upfront costs and making the technology more accessible to a broader range of businesses.

Also, take a look at the role of digital twins in automotive industry.

The future of Digital Twins in supply chain management is bright, with emerging trends and innovations set to drive further transformation. Digital Twins will continue to revolutionize supply chain management, helping organizations stay competitive in an increasingly complex and dynamic market.

While implementing Digital Twins in supply chain management presents challenges, overcoming obstacles is essential for reaping the benefits of this transformative technology. 

Save this write-up as your go-to guide on digital twins for supply chain management, and if you are looking for someone to help you with your digital twin, give us a call. We’ll patch you up with our experts.