Modeling and Supporting Decisions in Modern Supply Chains

Volatility, Uncertainty, Complexity, and Ambiguity (VUCA)

In today's volatile, uncertain, complex, and ambiguous (VUCA) environment, supply chain professionals are facing unprecedented challenges. Traditionally, supply chain leaders have relied on deterministic approaches to manage their operations.

The dynamic nature of the modern business landscape demands a shift towards a stochastic understanding of supply chains to thrive amidst uncertainty and complexity.

Network optimization is a great process to start modeling and guiding stakeholders into making better decisions. However, to face the challenges posed by a VUCA environment we have two recommendations that will help your organization to take advantage of uncertainty and complexity and turn them into your competitive advantage.

From a deterministic understanding of supply chain to a stochastic approach

Transitioning from a deterministic to a stochastic understanding of supply chains is paramount in navigating the VUCA environment. Supply chains are inherently complex systems with numerous variables influencing outcomes. From demand variability to production lead times, transportation delays, and unforeseen disruptions, there are multiple factors at play.

By engaging stakeholders and leveraging data analytics, supply chain leaders can identify critical sources of variability within their operations.

The objective of supply chain leaders should not be to interrogate stakeholders and data to find the perfect number that represent their supply chain. Instead, by leveraging a stochastic approach we can help our stakeholders to share what is the critical variability that we need to consider, those things that are hidden under the calculations of averages and point forecasts.

We need to enable stakeholders to answer questions with “it depends” and help them share what those things in the system are explain that variability. If we get one “it depends” for each critical component in our supply chain, we will start being in a great spot to go to step number two.

Modeling reality to support confident decision making by introducing variability and by decoupling forecast and demand.

Modeling reality to support confident decision-making is the cornerstone of effective supply chain management in a VUCA world. This begins with a comprehensive assessment of the supply chain system through stakeholder interviews and data analysis. By creating models that confidently represent processes and incorporate probabilistic elements, such as statistical distributions, supply chain professionals can gain insights to guide strategic decision-making. 

Leveraging the “it depends” identified in our first step for accelerating our supply chain decision support processes, we will use modern simulation and statics techniques to represent the complexity, volatility, and uncertainty of our system, and reducing the ambiguity of our supply chain.

The result should be a more robust representation of our network that allows us to differentiate noise from triggers and guide stakeholders into confident decisions. 

Examples of important modeling decisions that are often watered down in network optimization exercises are the inventory, sourcing, and shipping policies. Each supply chain has different characteristics and those could be effectively captured if we pay close attention to the inventory, sourcing, and shipping policies that our stakeholders use in their daily decisions.

Accurate solutions such as anyLogistix offer a wide range of these policies to better represent supply chains that are not only pull, but like most supply chains have to combine push and pull and balance inventory decision in the middle to be successful.

• https://anylogistix.help/tables/inventory.html#inventory
• https://anylogistix.help/tables/sourcing.html
• https://anylogistix.help/tables/shipping.html
  
  

Finally, a critical part of this approach is to distinguish between forecasted demand and stochastic demand in modeling supply chain dynamics. While forecasts provide point estimates, simulated demand captures the range of potential outcomes.

By decoupling forecasted and stochastic demand, supply chain leaders can gain a nuanced understanding of variability and uncertainty. This enables them to generate stochastic results that offer confidence intervals, empowering them to make informed decisions in the face of uncertainty.

Conclusion: 

Transitioning from deterministic to stochastic approaches and effectively modeling reality are essential steps for supply chain leaders to thrive in a VUCA environment. By embracing uncertainty and complexity, organizations can transform challenges into opportunities and achieve resilience and agility in their supply chain operations.

Through robust decision-making processes supported by robust modeling, supply chain professionals can navigate the uncertainties of the modern business landscape with confidence and agility.

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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.

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OR send me a note at ilinan@simwell.io

Isidro Liñan, PhD 
Supply Chain Practice Lead at SimWell | Helping companies achieve their supply chain vision