Explore a selection of our most impactful circularity projects, from strategy to system execution. Contact us to explore potential for your company and sector.
A redevelopment project – combining renovated heritage structures and new high efficiency low impact housing – was undertaken by a Swiss construction company facing Switzerland’s 2050 net zero target. Clarity was required on which circular economy measures could cut operational and embodied CO2, preserve financial returns, and remain viable under changing incentives and carbon prices.
A stock and flow system dynamics “digital twin” was developed to model lifecycle emissions, material flows, circular supply chain loops, costs, and policy levers. Scenario simulations were run to compare interventions and quantify carbon reduction, resource limits, scalability, profitability, and sensitivity to incentives, tariffs, and carbon pricing for ranked, bundled strategies.
Clear scenarios, circularity KPIs, and investment cases were produced. Audit ready GHG evidence was provided for prioritizing interventions, de risking capital, and scaling net zero, low carbon, circular construction across the portfolio. Circular supply chain resilience was strengthened, and a repeatable analytics framework was demonstrated for Swiss and European built environment transitions.
Achieving Switzerland’s 2050 net zero objective in the built environment demands an integrated circular economy strategy that addresses both operational and embodied greenhouse gas (GHG) emissions across the full building life cycle. To support this transition, a Swiss construction company developed a portfolio of innovative measures to avoid, reduce, compensate, or substitute project related CO₂ emissions and applied them to the mixed use redevelopment of a historic commercial site with new residential buildings in the Lake Constance region—using the project as a real world testbed for circular value chain design in net zero construction.
To guide long term strategic alignment, the company sought to determine which interventions contributed most effectively to the 2050 net zero goal—and under what market, policy, and carbon price conditions. A secondary objective was to evaluate the profitability and risk profile of each intervention under defined scenarios.
A stock and flow system dynamics model was built to simulate material flows, energy consumption, lifecycle emissions (operational and embodied carbon), and carbon offset or generation pathways across the full building life cycle—from material sourcing through operation to eventual deconstruction. The model ran day by day over a 10 year horizon, tracking each stage in units of building components and energy flows. Demand and usage volatility were represented stochastically to mimic real world unpredictability. Parameterization relied on published industry benchmarks; no client data were imported. Indicative emissions and end of life circular pathways were represented where relevant—allowing sustainability minded users to view environmental signals alongside operational and financial metrics.
Graph 1: Multi Scenario Analysis of CO₂ Absorption vs. Reforestation Scale
Graph 2: Optimal Reforestation Scenarios for Each Standard
Taken together, these insights equip decision makers to identify, prioritize, sequence, and scale the most effective measures—accelerating the sector’s transition to a circular, low carbon value chain in Swiss construction. More broadly, this case demonstrates how tailored system dynamics modelling can transform fragmented lifecycle and energy data into strategic foresight, supporting the design, sequencing, and financing of circular, net zero systems.
A fictional global sports footwear brand faced a strategic dilemma: large seasonal demand swings lead to costly and unsustainable overproduction, while scaling back too far risked lost sales and shelf presence. The company sought to understand how overproduction could be halved over ten years without exceeding 0.5% unfilled orders—balancing product availability, inventory pressure, and sustainability goals in volatile markets.
Using MESH’s system dynamics approach, a stock-and-flow simulation was built to model global shoe production—from tier 2 component suppliers to final retail and e-commerce channels. The model ran day-by-day over a decade, capturing lead time delays, demand shocks, and service levels. Scenario levers included underproduction targets, replenishment speed, and circular recycling pathways for excess inventory.
Simulation results revealed that 50% overproduction cuts were feasible under select reactivity conditions, with service loss kept under 0.5%. Nonlinear trade-offs became visible, enabling more confident decisions. Inventory swings, cost exposure, and CO₂ trajectories were jointly analyzed. The demo supports sustainability roadmaps, risk reviews, and policy testing for circular inventory and low-carbon supply chains.
This publicly shareable case is an illustrative demonstration model, developed within the MESH approach, based on industry research in the global sports shoe sector. No proprietary client data were used; all results represent modelled potential rather than actual company performance. The scenario reflects a common strategic challenge: large seasonal demand swings drive costly overproduction yet simply cutting output risks unfilled orders and lost shelf presence. A planning tool was needed to explore how far production could be pulled back without eroding service levels.
A representative global sports shoe manufacturer sought to understand whether overproduction could be reduced 50% over a 10 year horizon while unfilled orders did not exceed 0.5%. The key strategic tension: maintaining high on time product availability in volatile markets while curbing excess inventory that locks up capital and resources. Traditional spreadsheet planning proved insufficient for testing interactions among demand variability, lead time delays, production freezes, and downstream channel dynamics.
To address this uncertainty, a stock and flow system dynamics model was built to capture the essential structure of a global sports footwear value chain. In the model, key shoe components (soles, uppers, midsoles, hardware) were assumed to flow from specialized tier 2 suppliers to a tier 1 assembly facility where finished pairs were built. Completed product then moved into a central distribution hub and was allocated to downstream demand pools representing branded retail outlets and e commerce orders. The simulation ran day by day over a 10 year horizon, tracking each pair of shoes through every stage to capture delays, inventory swings, and service outcomes. Demand volatility was represented stochastically to mimic real market unpredictability. Parameterization drew on published industry benchmarks; no client data were imported. In addition to production, inventory, and service behavior, indicative emissions and end of life circular pathways were represented where relevant, allowing sustainability minded users to view environmental signals alongside operational metrics.
Graph 1: Decision tree for identifying high-potential interventions
Several mitigation concepts were reviewed; the model focused on the combined strategy judged most promising under uncertainty: produce below forecast (disciplined volume reduction against the demand plan) paired with increased value chain reactivity (shorter replenishment cycles / faster response capacity) to cover upside demand and avoid stock outs. Scenario levers included degree of under production, achievable response speed, and demand volatility ranges. A later model extension allowed residual excess to flow into a recycling pathway for exploratory comparison.
Graph 2: Structural setup of the global sports shoe simulation model
Running daily simulations across the 10 year horizon made visible the non linear trade offs obscured in static analyses. Pulling production modestly below forecast dramatically reduced cumulative overproduction – but only when paired with sufficient reactive capacity to refill unexpected demand spikes. Excessively deep cuts without reactivity drove unacceptable service loss; minimal cuts delivered little benefit. The model helped isolate parameter bands where the 50% overproduction goal could be approached while unfilled orders remained below 0.5%. Inventory swings, cost exposure, and indicative emissions trajectories could be reviewed side by side, strengthening planning confidence for sustainability and operations leaders.
Specifically, the model identified two possible scenarios which enable the shoe manufacturer to achieve the 50% reduction in overproduction while ensuring that unfilled orders do not exceed 0.5% over 10 years.
In the first scenario, the shoe manufacturer implemented a reorder system where replenishment orders could be placed in between the regularly scheduled orders. This allowed the regular order amount to be set at 8.7% below the forecasted demand while still retaining the ability to fill 99.5% of all orders.
In the second scenario, in addition to the refill orders, the total lead time required to place orders was reduced by 7 days. This allowed the shoe manufacturer to order even more conservatively, with orders being set at 9.2% below the forecasted demand.
The impact of these two scenarios on the shoe manufacturer’s profits can be seen in Graph 1.
Graph 1: Profit impact of two reactivity-enhanced scenarios compared to status quo
While only one of the simulated scenarios is more financially attractive than the status quo, they both drastically improve the manufacturer’s CO₂ balance. Graph 2 shows that each of the two scenarios respectively would emit approximately 69% less CO₂ over 10 years.
Graph 2: CO₂ savings over 10 years under the selected scenarios
Because this is a demonstration model, results are reported directionally. Simulation experiments identified feasible combinations of “produce below forecast” settings and response times that met both the 50% overproduction reduction target and the ≤0.5% unfilled order constraint under a range of demand variability conditions. Where reactivity lagged, performance degraded; where responsiveness matched demand shocks, targets remained achievable. Recycling capture marginally improved end of life outcomes but did not replace the need for upstream volume discipline.
The demonstration shows how system dynamics modelling for fashion & footwear can be used to explore policy ranges before committing capital or reorganizing supply agreements. By surfacing the conditions under which volume reductions hold service, the approach supports more confident sustainability roadmaps, risk reviews, and executive alignment conversations – useful well beyond footwear for organizations evaluating circular inventory management or low carbon supply chain strategies.
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