DSV

DSV, one of the world's largest third-party logistics providers, faced a structural challenge endemic to the Warehousing & Distribution sector: serving a major health and beauty retail client whose order volumes spike sharply during peak holiday seasons. In 3PL operations, fixed labor and equipment commitments create a costly dilemma — overcommitting resources during slow periods to ensure capacity at peak, or understaffing and risking fulfillment failures when demand surges. DSV's warehouse infrastructure across multiple facilities lacked the flexibility to scale robotics capacity dynamically, leaving the company absorbing either idle-cost waste during off-peak periods or throughput constraints that threatened client service levels when volumes climbed.

DSV deployed Locus Robotics' autonomous mobile robot (AMR) platform across multiple warehouse facilities under a robots-as-a-service (RaaS) commercial model, allowing the active fleet size to expand during peak seasons and contract during slower periods without fixed capital commitments to hardware. The core of the implementation is Locus Robotics' swarm technology, which applies reinforcement learning and dynamic optimization algorithms to coordinate multiple robots simultaneously — routing each unit in real time based on order queue depth, warehouse layout, and live picker positioning. The system integrated into DSV's existing warehouse infrastructure without requiring significant facility reconfiguration, supporting flexible navigation across different floor plans. Staff training and IT coordination were treated as first-class deployment workstreams, with Locus Robotics providing a standardized onboarding framework that DSV customized per site, enabling consistent rollout across facilities while accommodating each client's operational profile.

The partnership produced measurable gains in warehouse productivity across DSV's facilities:

• 3–4 bot-to-picker ratio: Locus Robotics' swarm system consistently maintained this ratio, reducing picker travel burden and compressing time-per-pick by directing robots to carry items rather than having workers traverse full warehouse aisles.
• Improved throughput and labor allocation: Dynamic route optimization drove immediate gains in picks-per-hour and freed warehouse staff to focus on higher-value tasks.
• Elastic capacity: DSV scaled its robot fleet up during peak holiday seasons and down during slower periods, eliminating idle-infrastructure costs.

The deployment model proved repeatable — DSV successfully replicated the implementation across multiple sites, validating the framework's adaptability to different client environments and floor layouts.

• A RaaS model converts robotics from fixed capital expenditure to a variable operating cost, making elastic scaling financially viable for 3PLs with seasonal demand cycles.
• Swarm AMR deployments with a 3–4 bot-to-picker ratio can materially reduce pick travel time and increase throughput without requiring warehouse redesign or WMS replacement.
• Standardized-yet-customizable deployment frameworks are critical for 3PLs rolling out automation across multiple client sites — consistency accelerates replication while flexibility preserves operational fit.
• Training and IT coordination must be scoped as dedicated workstreams from day one; adoption quality at go-live directly determines whether efficiency gains materialize on schedule.
• Integrating AMRs into existing infrastructure, rather than replacing it, lowers implementation risk and shortens time-to-value.