Challenge
A North American client was in the construction phase of a $4 billion battery manufacturing facility but was facing delays of three to five months against its target start of production. The primary bottleneck lay in the complex scope of process-equipment installation, which threatened to push back operational readiness and erode the business case for the investment.
The company asked McKinsey to assess the feasibility of the existing schedule and provide strategies to safeguard timely delivery. In particular, they sought to determine whether the current sequence and activity durations were realistic, to develop an optimized installation schedule that could accelerate delivery, to stress-test the plan with “what-if” scenarios and ongoing decision support, and to identify optimization levers that could mitigate risks and recover lost time.
Discovery
To address these challenges, we designed and deployed a generative scheduling model tailored specifically to the battery cell production process. This advanced-analytics approach made it possible to construct and optimize tool installation activities, dependencies, and resource allocations across all production areas, including Electrode, Assembly, and Formation.
Working closely with the client team, we developed a detailed construction sequence and dependency logic, underpinned by recipes that reflected the requirements of battery cell production at the equipment level—from tool move-in through commissioning. By mapping the project’s critical path and running a series of “what-if” scenarios, we were able to identify the most powerful optimization levers and test their feasibility under different constraints.
We also developed a 4D model that integrated time, space, and sequence, giving the client team a dynamic visualization of the installation scope. This tool enhanced execution planning, allowed leaders to anticipate challenges before they materialized, and provided a powerful way to communicate decisions across stakeholders. The combination of data-driven optimization and real-time visualization helped pinpoint the most effective pathways to accelerate delivery and reinforced the client’s ability to manage execution proactively.
Impact
The engagement generated substantial schedule and financial benefits. The generative scheduling model identified more than six weeks of potential acceleration through targeted optimization levers, allowing the client to bring production online significantly earlier. The financial impact was equally impressive, with estimated savings of more than $60 million from earlier monetization of output.
The model covered more than 3,000 pieces of production equipment and tested over ten different “what-if” scenarios, providing the client with a robust, evidence-based understanding of its options. Beyond the immediate savings and schedule acceleration, the new planning tools strengthened the organization’s ability to manage risks, make confident decisions, and sustain momentum as the project moved toward completion.