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Plan peak-season warehouse automation by starting with demand and operating data, targeting a measured bottleneck, and testing a solution that can work beyond the surge. Before committing to permanent capacity, compare options against your facility’s order profile, space, systems, staffing, safety needs, and ability to scale down after peak.

1. Build a seasonal demand picture

Start with historical peak, average, and quieter periods alongside the current forecast. Break the workload down by SKU count and velocity, inventory position, order profiles, and the processes that constrain fulfillment. MHI’s July 2025 seasonal-planning guidance recommends using WMS or ERP performance data to examine peaks, valleys, and averages; it is industry guidance, not a universal forecasting formula. MHI’s seasonal order-picking guidance quotes Ed Romaine, vice president of marketing and business development for ISD: “It starts off with the numbers and knowing the data, your forecast, and demand.”

Describe the peak in operational terms: when it starts and ends, which order lines or handling units dominate, where queues form, and which service failures are most costly. If your business has several seasonal surges, analyze each rather than assuming one demand curve represents them all.

  • Compare forecast demand with prior peaks, averages, and valleys.
  • Segment the workload by SKU count and velocity, inventory levels, and order profile.
  • Map queues, handoffs, and service failures to the process where they occur.
  • Check that inventory and order data are reliable enough to support capacity decisions.

2. Choose a bottleneck to pilot

Automation is most useful as a response to a defined constraint—not as a technology search in need of a problem. Identify a task with a measurable capacity, staffing, safety, or consistency issue. MHI’s 2025 implementation article describes a distribution center that struggled to maintain sortation staffing during peak periods and used that challenge as a reason to explore a pilot. It also discusses physically demanding or undesirable tasks. These are examples, not evidence that sortation or any other function is always the right target. MHI’s implementation account

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Record a baseline and agree on pilot measures before choosing equipment. Depending on the constraint, track throughput during the required operating window, accuracy or reject rate, labor hours, safety impact, and whether the automated process can run alongside existing operations. MHI’s account notes that organizations use different success measures, including throughput, labor-cost effects, errors or rejects, and safety; choose measures that reflect your own service requirements.

3. Compare automation options against your peak pattern

Peak capacity does not have to mean buying a single permanent system sized for the busiest weeks. MHI’s July 2025 guidance discusses automated storage and retrieval systems (AS/RS), putting more existing pick stations into operation, adding temporary pick stations, leasing automated equipment, adopting technology in phases, and considering equipment that may also support returns. The MHI article quotes Romaine saying, “The system can also be dialed up or down to meet peak and non-peak requirements.” That observation applies to the systems discussed in the article, not to every automation installation.

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Other technologies address different jobs. The Association for Supply Chain Management (ASCM) describes autonomous mobile robots (AMRs) for transport, AS/RS for storage and retrieval, and Internet of Things (IoT) monitoring for operational visibility in its warehouse technology overview. These categories are not interchangeable: compare them against the work causing your constraint.

Approach Potential planning role Questions to validate locally
AS/RS Automated storage and retrieval; a candidate where storage and retrieval capacity or density is part of the constraint. Does it fit the SKU and order profile, available space, inventory data, controls, and expected demand outside peak?
AMRs Transport within warehouse operations. Which routes or handoffs are constrained, and can the WMS coordinate movement and inventory data?
Additional or temporary pick stations Add or activate picking capacity for a seasonal workload. Is there floor space, staffing, and a workable process for installing, operating, and later removing or repurposing stations?
Leased automated equipment Potential way to address a seasonal capacity need without treating peak demand as permanent. Can the lease period, integration work, deployment schedule, and operating costs fit the peak window?
IoT monitoring Visibility into movement and operational conditions that can support monitoring and resource allocation. Which decisions will the data inform, and are the relevant systems and processes ready to use it?

Compare candidates on peak throughput, non-peak flexibility, SKU and order profile, storage density and floor space, WMS/ERP and controls integration, deployment disruption, workforce and safety effects, and the economics of temporary or leased capacity. The cited guidance does not establish a universal return-on-investment figure or capacity threshold, nor does it provide comparable performance data for ranking technologies. Request facility-specific estimates and validate assumptions in a pilot rather than treating vendor claims as guarantees.

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4. Prepare systems, workers, and safety processes

Before a pilot, assign clear ownership for the process and its interfaces. Check inventory-data quality and how the warehouse management system (WMS), enterprise resource planning (ERP) system, equipment controls, and robotics software will exchange the information needed for the operation. ASCM cautions that integration requires careful planning; MHI’s March 2026 robotics article says an up-to-date WMS is needed to coordinate robot movement and inventory data. MHI’s robotics and packaging guidance

Include frontline workers in the design and communicate what will change before deployment. Provide training for the roles affected and review safety implications of the new process, traffic patterns, equipment, and exception handling before scaling. MHI’s field account specifically highlights communication and training as important to scaling robotics. For a first assessment or pilot, MHI’s 2026 article recommends starting with an integrator or original equipment manufacturer (OEM); its contributor Greg Berguig of PAC Machinery says, “The best starting place for exploring your automation options is with an integrator or OEM.”

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5. Review performance after the surge

Once the peak passes, compare actual demand and operating results with the forecast and pilot assumptions. Use available data to identify what the system handled well, where work accumulated, and what should change in the next capacity plan. MHI recommends learning from peak performance and using WMS or ERP data to compare peak, average, and quieter periods.

  • Record throughput, service misses, and exceptions against the measures set before the pilot.
  • Review labor usage, overtime, equipment uptime, and safety observations where those records are available.
  • Include returns burden if it materially affected capacity.
  • Update the next forecast, capacity plan, and technology scope using the observed demand pattern.

What the available figures can—and cannot—tell you

ASCM’s December 2024 updated article says picking can account for as much as 55% of a distribution center’s operating costs. Treat that as a broad claim from the article, not a cost model for your building. The same article reports U.S. e-commerce sales of about $1.119 trillion in 2023, compared with $1.040 trillion in 2022; those figures provide historical context, not a current forecast for an individual warehouse. ASCM’s warehouse automation article

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The cited sources are professional or industry-association guidance, not controlled comparative trials. A site-specific decision depends on throughput, order profile, SKU mix, layout, labor, software, safety, and budget. Validate vendor performance claims against your own baseline and required service levels.

Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.