Technology Overview
Digital Twin
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How it Works
Over the past decades, supply chains have become increasingly global, with dispersed manufacturing facilities and extended logistics networks. This evolution has been driven by rising global trade and a continuous focus on lean operating principles to enhance efficiency. While these changes have optimized costs, they have also made supply chains more vulnerable to disruptions. Recent events such as the COVID-19 pandemic, Typhoon Halong in Southeast Asia, the Suez Canal blockage, and the Ukraine War have demonstrated that no global company is immune to low-probability, high-impact events, also known as Black Swan events.
Traditional risk assessment methods rely on estimating the likelihood and financial impact of potential disruptions. However, accurately predicting the probability of low-likelihood events is challenging, often leading managers to underestimate risks and overlook necessary precautions. As supply chains remain in a continuous state of flux, maintaining precise risk predictions becomes difficult. Instead, companies can assess their vulnerability to disruptions by leveraging a Supply Chain Digital Twin (SCDT)—a dynamic simulation model that mirrors the real (physical) supply chain.
In addition to simulation modelling with SCDTs, optimization modelling is another powerful technique for making critical supply chain decisions. Below, we discuss some of the most important supply chain decisions and how to approach them effectively.
Understanding the Impact of Tariffs and Optimizing Supply Chain Flows
In any global supply chain, raw materials and finished goods move across multiple countries. Changes in tariffs can alter the optimal flow of materials, impacting the cost-to-serve at various demand points. A Supply Chain Digital Twin (SCDT) can analyse these cost impacts under the existing supply chain configuration. Furthermore, an optimization model incorporating new tariff structures can determine the best material flows while minimizing additional costs.
For instance, if tariff changes significantly impact profitability, an optimization model can identify whether adjustments such as shifting production to a different facility, renegotiating supplier contracts, or adjusting selling prices are necessary. Long-term strategies, including investments in new facilities or closures of existing ones, can also be evaluated using these models.
Evaluating Reshoring and Nearshoring Strategies
While analysing tariffs is a relatively new challenge, the disruptions caused by the COVID-19 pandemic and geopolitical events have prompted companies to reassess their supply chain structures. Many firms are already reshoring (bringing production back to domestic markets) and nearshoring (moving production closer to demand centers) to mitigate risks.
Simulation modelling can help assess the cost implications of such shifts, while optimization modelling can guide strategic decisions on expanding capacity at existing sites or investing in new facilities. Additionally, greenfield analysis—which determines optimal locations for new factories and warehouses based on demand patterns and cost minimization objectives—can support market expansion efforts. Similarly, mergers and acquisitions often lead to redundant facilities, and optimization modelling can help determine the best consolidation strategy.
Cash to Serve: Optimizing Financial Flows in the Supply Chain
While the physical flow of goods often takes center stage, the financial flow—Cash-to-Serve (CTS)—is equally vital for supply chain success. CTS measures the total cost of delivering products or services to customers, offering a detailed breakdown of expenses across sourcing, manufacturing, warehousing, transportation, and distribution. Unlike traditional cost metrics, CTS provides a holistic view of financial efficiency, enabling businesses to identify inefficiencies and allocate resources more effectively.
By analyzing which customers, products, or regions drive profitability, companies can make data-driven decisions to reduce costs while maintaining service quality. This leads to improved profitability, enhanced customer satisfaction, and greater operational efficiency. Implementing CTS involves mapping the supply chain, segmenting customers and products, identifying inefficiencies, and developing targeted improvement initiatives. This alignment ensures that supply chain operations meet customer needs while keeping costs under control.
CTS delivers several key benefits: cost transparency, enabling savings without sacrificing service; improved profitability by focusing on high-value customers and products; strategic resource allocation toward high-return opportunities; and enhanced customer centricity, ensuring operations align with customer expectations.
Ultimately, CTS helps companies reduce unnecessary expenditure, improve cash flow, and achieve sustainable growth. By shortening the time between cash investment and revenue collection, CTS ensures supply chains are both resilient and financially sustainable, providing a competitive edge in the market.
Managing Demand Volatility: Building Agility into the Supply Chain
Demand volatility has become a defining characteristic of modern supply chains. Sudden spikes or drops in demand, driven by market trends, seasonal fluctuations, or unforeseen events, can disrupt even the most well-planned operations. To manage this volatility, companies must build agility into their supply chains.
Simulation modelling can help companies understand the impact of demand variability on their operations. For example, by simulating different demand scenarios, companies can identify bottlenecks in their production or distribution processes. Optimization modelling can then suggest strategies to mitigate these risks, such as:
Dynamic Inventory Management: Adjusting inventory levels in real-time based on demand forecasts.
Flexible Production Scheduling: Allowing production lines to switch between products quickly to meet changing demand.
Multi-Sourcing Strategies: Diversifying suppliers to reduce dependency on a single source and mitigate supply disruptions.
By integrating forecasting outputs directly into simulation and optimization models, companies can enhance their ability to anticipate demand volatility and respond with precision. These models leverage data-driven insights to create adaptive strategies, ensuring supply chains remain resilient and responsive in the face of uncertainty.
Stress Testing the Supply Chain to create a resilient supply chain
As highlighted earlier, companies must be prepared for future Black Swan events. Since these disruptions can have severe consequences, it is essential to have in place a robust risk mitigation strategy. Some of the most effective strategies include:
- Inventory Buffers: Maintaining sufficient stock to sustain service levels in case of supply chain disruptions.
- Capacity Buffers: Ensuring production and storage capacity redundancy to handle facility shutdowns.
- Flexible Supply Chain Structures: Designing supply chains where multiple factories can produce the same product to maintain service levels despite disruptions.
Each of these strategies comes at a cost, making it critical to determine the most cost-effective approach. SCDT-based optimization and simulation modelling can help companies design risk mitigation strategies that minimize costs while enhancing supply chain resilience.
Using an SCDT, companies can also estimate key metrics such as:
- Time to Survive (TTS): The duration a supply chain can maintain service levels after a disruption.
- Time to Recover (TTR): The time required to restore the supply chain to desired service levels.
- Performance Impact (PI): The financial impact of lost sales due to a disruption.
- Risk Exposure Index (REI): A prioritization metric for disruptions to which the supply chain is most vulnerable.
SCDT will help companies determine the most critical scenarios. For such high-impact disruption scenarios, optimization models can determine the best response strategies, such as reallocating on-hand inventory, activating alternative suppliers, or leveraging buffer capacities to minimize disruption impact at the lowest possible cost.
Conclusion
In today's dynamic and uncertain world, supply chain decision-making must go beyond traditional risk assessments. By leveraging Supply Chain Digital Twins and optimization modeling, companies can proactively assess vulnerabilities, respond to disruptions, and optimize long-term strategies. Whether dealing with tariff changes, restructuring supply chains, managing demand volatility, or preparing for the next Black Swan event, a data-driven approach ensures resilience and efficiency in global supply chains.
At SimWell, we help companies make these critical supply chain decisions with the help of tools such as SCDT and optimization modeling. Anylogistix is one of the most powerful tools in the market, enabling faster and more accurate analysis.
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About SimWell
SimWell Consulting and Technologies is a global company specializing simulation, optimization, and digital twin technology. Our core mission is to unlock simulation at scale. We empower leaders and operators to maximize their current resources, optimize their operations, and elevate their performance with simulation. We build models of our customers operation, test scenarios, and predict how it will perform in a risk-free environment.
With SimWell as your partner, your team will have the tools to make confident decisions, optimize your process, and press fast forward on your business.
Written by:
Amit Kumar, Director, India Operations at SimWell
Krishna Chaitanya, Senior Solution Owner, India
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