What gaps exist in your supply chain planning?

How can you strategically manage supply chain disruption – and make the right decisions to create a more robust plan for the future?

The Covid-19 pandemic has had long-lasting supply chain implications, leading to ongoing issues with supplier capability, fulfillment capacity, transportation capacity and labour availability. A December 2022 survey found that 71.8% of companies continue to face global supply chain disruptions, with 57.7% trying to work through ongoing transportation capacity shortages.

These issues can’t all be solved immediately – they’re fundamental challenges that require focused and considered change over a period of time. However, predictive simulation provides vital tools that can be exploited now to drive that change.

Let’s look at 4 ways predictive simulation and related analytics are helping business leaders make evidence-based supply chain decisions that reduce risk, optimise resource allocation and deliver greater operational control.

Use case 1: Building agility through supply chain partner collaboration

A crucial Covid-19 supply chain lesson is that agility is as important as resilience.

OneWeb Satellites is a perfect example of how predictive simulation helps you build that agility into your planning. OneWeb's mission is to mass-produce a satellite constellation to provide high-speed internet access worldwide. However, running the world’s first satellite serial production line involves complex processes and supply chains. Supplier rate optimisation is crucial to meeting targets and managing costs.

OneWeb Satellites uses Twinn Witness predictive simulation software to accurately predict current- and future-state supply chain and production requirements. Through dynamic simulation of their supply chain, OneWeb can tell suppliers how soon to get ready and what rates are needed at specific times. They can evaluate different rates by month, week and day, even factoring in a learning curve (because production efficiency increases over time).

This visibility has allowed OneWeb Satellites to collaborate successfully with its supply chain, meaning there’s a genuine partnership approach. As a result, they’ve effectively forward scheduled, planned subassemblies and ensured the right level of buffer stock ahead of time. It’s foresight and collaboration-powered agility in action.

Use case 2: Scaling logistics to meet growth targets

This ‘twin of the future’ gave them a visual roadmap for their intended logistics operations, helping maximise efficiencies in the process while minimising the overall cost implication. The result for NeroGiardini was a robust investment case for scaling their logistics footprint, which has ensured they can continue to meet performance targets as they expand.

Use case 4: Managing trade-offs across the supply chain

A key benefit of predictive simulation is that it gives clarity on trade-offs between seemingly conflicting processes, such as purchasing, production, inventory, distribution and sales. For instance, should you pursue a strategy focused on local production with lower transport costs? Or one with lower-cost overseas production and higher transport costs?

Mars Chocolate North America used predictive simulation to drive a Sales and Operations Planning (S&OP) tool to answer questions like these. The company has 6 US sites, each with different production mixes, chocolate consumption requirements and bulk storage constraints. Using a digital twin deployed using Twinn WITNESS software, they predicted supply chain performance achievable from various configurations across the sites. For the first time, they achieved detailed insight into these dynamic supply chain processes.

This helped Mars understand the impact of key trade-offs. For example, would it be better to make all chocolate types where they’re required or build fewer, larger facilities and ship regionally? And what’s the best way to factor in the Mars corporate principle that it’s important to manufacture as close to customers as possible? As demand changes, where are future bottleneck going to appear and how can they be resolved?

The S&OP simulation asset helped quantify the optimal way to work within these parameters. It provided deep insights into existing and planned operations, identified supply chain risks, and highlighted opportunities for cost savings and performance improvements. As a result, Mars developed evidence-based business cases for new capacity programmes, ensuring they make the right investments at the right time.

Is your supply chain optimised for the medium term?

‘Do we have the right facilities, processes and assets, in the right places, with the right control mechanisms, to ensure our supply chain can satisfy our business strategy?’

Predictive simulation and related analytics can help you answer that question. Contact us for more information.