Global industrial manufacturer: Resource productivity transformation

1 min read

Automotive & Transportation Manufacturing

Workers in high-visibility jackets walking past an industrial refinery with large processing towers and pipelines at dusk.

A global industrial manufacturer, sought to unlock value trapped within its supply chain. Despite stable performance in a highly capital-intensive industry, profitability and cash conversion were constrained by structural cost complexity, portfolio inefficiencies and service models misaligned with customer value. Economic cost embedded across logistics, warehousing, inventory holding and customer service activities was largely spread across customers and products, obscuring true cost-to-serve dynamics. We developed an activity-based cost-to-serve framework to identify sources of economic cost and operational complexity that did not drive value to, or value from, priority customers and markets. The resulting resource productivity playbook defined targeted initiatives generating ~$60M of one-time cash uplift and $13M of recurring annual EBITDA improvement.

Outcome 1: Developed an activity-based cost-to-serve framework that created transparency into economic cost, operational complexity and the true drivers of resource productivity across customers and products

Outcome 2: Identified targeted initiatives that generated ~$60M of one-time cash uplift through reductions in excess inventory, improved dwell times and working capital optimisation

Outcome 3: Defined structural improvements across service models, SKU complexity and operational processes that are set to deliver $13M of recurring annual EBITDA improvement

The challenge

Our client faced a limited historical view of true cost-to-serve, with supply chain and service-related costs embedded in aggregated reporting that obscured material variability across customers and products. This lack of transparency prevented the organisation from understanding the primary drivers of logistics, warehousing, inventory and customer service expenses, reinforcing decisions that often led to over-servicing customers relative to their needs or willingness to pay. At the same time, a fragmented SKU portfolio increased operational complexity, dwell times and working capital intensity. Without an activity-based lens or structured customer differentiation, our client struggled to identify cost drivers, prioritise corrective actions, or align service models with economic value.

The approach

We designed and implemented an activity-based cost-to-serve model to decompose logistics, warehousing, inventory and service costs at the customer and product level. This created transparency into variability, dwell times, and the operational drivers of supply chain expense. Customers were segmented based on needs, service requirements and willingness to pay, enabling clearer differentiation between value-creating service and avoidable complexity. Regression and variance analysis isolated the behaviours and attributes most strongly linked to cost intensity. These insights informed a resource productivity playbook defining targeted initiatives across service models, SKU rationalisation, manufacturing batch sizes and inventory policies to improve cash conversion and margin.

The impact

Playbook actions delivered significant financial and operational benefits by improving cost transparency and resource productivity. Targeted initiatives generated ~$60M of one-time cash uplift through reductions in excess inventory, improved dwell times and working capital optimisation. In parallel, structural improvements in service models, SKU complexity and operational processes are set to deliver ~ $13M of recurring annual EBITDA improvement. Supply chain efficiency increased as resources were aligned more closely with customer value and demand patterns.