Accurate capacity planning is fundamental to Mars’ operations. Given its product mix, its sites have a range of chocolate-making capabilities and chocolate-consuming requirements. Its focus on quality prevents long-term bulk storage of chocolate products, which presents a fulfilment challenge when demand peaks. Plus, Mars has a corporate principle that it’s important to manufacture as close to customers as possible, which means efficiency is critical given this isn’t always the optimal approach from a purely commercial perspective.
When the business was considering significant future finishing line investments, they wanted assurance from the supply chain team that those investments would be satisfied from a chocolate-making perspective. To provide the required business planning confidence, the team launched an initiative to assess and refine capacity levels across the network.
The supply chain team had historically relied on spreadsheet-based modelling, but quickly identified that the scale, complexities and interdependencies involved in capacity planning across the 6 sites required more sophisticated capabilities.
“Static modelling works well in certain areas, but we needed a tool which could explore high volumes of ‘what-if’ scenarios and plot multiple answers / ranges to achieve an in-depth, contextualised understanding of our 6 sites based on variable capacity, demand and product mix,” said Paul Myler, Director of Supply Chain Strategy & Industrial Engineering at Mars Chocolate North America.
Paul had previously used Twinn Witness predictive simulation software (formerly under the Lanner brand) for modelling complex and dynamic processes. “We’d used Witness in a number of areas across our global operations – primarily for line level loading, supply chain and packaging process modelling. We knew it was the best solution to support this project.”
Working closely with our experienced business modelling team, Mars used Witness to drive a Sales and Operations Planning (S&OP) tool that could interrogate their “what-if” scenarios and provide an in-depth understanding of US-wide capacity.
A key focus for the model was understanding the impact of strategic trade-offs. For example, would it be better for the business to make all chocolate types at the location where they’re required? Or should they build fewer, larger chocolate-making facilities and ship products across the country? And what would be the best way to factor in the principle of manufacturing as close to end customers as possible?
The Witness-powered S&OP tool answered these questions by predicting supply chain performance based on different product mixes and chocolate-producing and consuming configurations across the sites.
“Witness models complex scenarios and delivers exceptional levels of clarity. If your model is well designed, it can effectively be future-proofed to be used again and again over time as a key strategic asset, extending the ROI substantially,” said Paul.
The S&OP simulation asset provided reliable forward visibility of supply chain performance and quantifiable terms of reference for accurate capacity planning. It gave the team deep insights into existing and planned operations, identified supply chain risks and highlighted opportunities for cost savings and performance improvements. As a result, Mars has been able to develop evidence-based business cases for new facilities and justify additional chocolate-making capacity – with confidence they’re making the right investments at the right time.
“The Witness model generated a 5-year view, and while the initial runs confirmed that capacity was fine for the next 2 years, after that point we would likely experience supply shortages,” Paul explained.
The model highlighted how to overcome those shortages with minimal additional investment. Mars now runs the simulation every 6 months, feeding the results into the company’s Capital Allocations Budget to assist with business planning.
The best example of how the Witness model has assisted long-term planning was when it was used to support a new production site in Kansas. A new facility represents significant capital expenditure, so Mars robustly interrogated their Witness model to ensure that exactly the right investment was channelled into chocolate-making assets to meet the new demand.
“Essentially, it means we always have visibility – over our long-term planning timeframe – of the timing and level of funding required for the new chocolate capacity needed to meet demand from current and future facilities,” Paul concluded.