Warehouse Co. is evaluating a $6M AI-powered automated crane system with $1M annual maintenance costs. Analysis shows annual labor savings of $2.8M, yielding a 3.33-year payback period with $1.8M annual net savings post-payback. The case requires candidates to identify labor as the key driver and assess both economic and non-economic risks.
Key Insights:
- Filter noise: Most cost categories (supplies, utilities, support staff) show minimal changes; labor cost reduction is the primary value driver
- Payback calculation must account for ongoing maintenance costs, not just gross savings
- Recommendation requires balancing quantitative ROI against qualitative risks: labor relations, technology maturity, competitive response, and reputational concerns
- The technology’s newness creates both opportunity (competitive advantage) and risk (unknown reliability, single-source dependency)