Baseline current picking productivity, travel time and error rates before modelling automation impact.
Warehousing & Procurement
Building the Business Case for Autonomous Mobile Robots in Order Picking
Learn to build a rigorous, defensible business case for autonomous mobile robots in order picking, from throughput modelling and total cost of ownership to a phased implementation plan.
🗓️Duration5 training days
📚Content4 modules · 8 sessions
🎓On completionAccredited attendance certificate
About the programme
Course Overview
Warehouse leaders are regularly pitched autonomous mobile robots as a way to cut walking time and lift picking productivity, but vendor throughput claims rarely survive contact with a specific site's layout, order profile and labour market. This course equips participants to build their own defensible business case rather than relying on a supplier's numbers, starting from a picking-process baseline and working through fleet sizing, throughput modelling and total cost of ownership. Participants learn to capture current pick rates, travel time and error rates as a benchmark, model how an AMR fleet would change those figures under realistic congestion and charging assumptions, and size the fleet against peak and average volumes rather than a single average day. The course covers total cost of ownership beyond the robot price, including charging infrastructure, network and safety upgrades, WMS integration, and ongoing maintenance and fleet management staffing. It also addresses labour impact: planning redeployment, retraining and shift restructuring, and comparing AMR investment against alternatives such as goods-to-person shuttles or process redesign without automation. A modelling exercise using sample site data has participants build a payback and sensitivity analysis and structure a phased implementation plan a leadership team would fund.
Expected Learning Outcomes
Size an autonomous mobile robot fleet against peak and average order volumes with congestion assumptions.
Build a total cost of ownership model covering robots, infrastructure, integration and ongoing fleet management.
Compare AMR investment against alternative automation such as goods-to-person shuttles or process redesign.
Plan the labour impact of AMR deployment, including redeployment, retraining and shift restructuring.
Construct a payback and sensitivity analysis that tests the business case against volume and cost variation.
Structure a phased implementation plan and funding proposal that a leadership team can approve and track.
Who Should Attend
Warehouse and distribution centre managers evaluating robotic picking automation.
Operations and industrial engineers building automation business cases.
Finance business partners assessing capital investment proposals for warehouse robotics.
Supply chain directors comparing automation options across a distribution network.
Project managers who will lead AMR implementation once a business case is approved.
Continuous improvement leads exploring picking productivity alternatives to full automation.
Course Modules
Select any module to see its sessions and points.
01Baselining the Current Picking Operation
2 sessions · 8 points
Session 1Capturing Process and Productivity Data
- Measure current pick rates, travel distance and time-per-line across representative shifts and order profiles.
- Record error rates, rework and their downstream cost to establish a quality baseline for comparison.
- Profile order characteristics such as lines per order and SKU velocity that shape automation suitability.
- Map the physical layout and congestion points that any robotic solution would need to navigate.
Session 2Defining Success Criteria for Automation
- Set target improvements in productivity, accuracy and labour cost that justify pursuing automation.
- Identify constraints such as ceiling height, floor condition and racking type that limit robot options.
- Engage warehouse staff early to surface practical concerns about robot interaction with manual work.
- Agree the evaluation criteria and weighting that will be used to compare automation options later.
02Modelling Throughput and Fleet Size
2 sessions · 8 points
Session 1Sizing the Robot Fleet
- Model required fleet size against peak-hour and average-day order volumes rather than a single figure.
- Account for charging cycles, battery swap strategy and downtime when calculating effective robot availability.
- Simulate congestion and queuing effects as fleet density increases in shared aisles and staging areas.
- Test fleet-size assumptions against seasonal peaks and promotional volume spikes.
Session 2Projecting Throughput and Labour Impact
- Project pick-rate improvement from reduced travel time against the baseline established earlier.
- Model labour requirements under the automated process, distinguishing redeployment from headcount reduction.
- Estimate training time and productivity ramp-up for staff transitioning to pick-to-light or tablet-guided roles.
- Stress-test throughput projections against vendor claims using independent simulation or site trial data.
03Building the Ownership Cost Model for AMRs
2 sessions · 8 points
Session 1Capturing Full Investment and Running Costs
- Itemise capital costs covering robots, charging infrastructure, safety systems and network upgrades.
- Estimate integration costs for connecting the robot fleet management system to the warehouse management system.
- Budget ongoing costs including maintenance contracts, spare parts, software licensing and fleet management staffing.
- Include facility costs such as floor marking, lighting and racking modification required for robot operation.
Session 2Comparing Automation Options
- Compare autonomous mobile robots against goods-to-person shuttle systems on cost, flexibility and footprint.
- Assess a non-automated process redesign, such as batch picking or slotting optimisation, as a baseline alternative.
- Weigh scalability and redeployability of AMRs across sites against fixed automation investments.
- Summarise the comparison in a decision matrix scored against the criteria agreed with stakeholders.
04Presenting the Case and Planning Implementation
2 sessions · 8 points
Session 1Building Payback and Sensitivity Analysis
- Calculate payback period and return on investment using the total cost of ownership and productivity model.
- Run sensitivity analysis testing the business case against volume decline, cost overrun and delayed ramp-up.
- Identify the break-even assumptions that most influence the investment decision.
- Prepare a risk register covering technology, labour and operational risks tied to the investment.
Session 2Structuring the Implementation Plan
- Design a phased rollout starting with a pilot zone before committing to full-site deployment.
- Plan change management and communication for staff affected by the automation rollout.
- Define governance and milestones for tracking the business case's assumptions against actual results.
- Present the completed business case in a format suited to capital approval by senior leadership.
What the participant receives
4 course modules
A structured syllabus
8 training sessions
across 5 days
32 detailed points
Applied, detailed content
Accredited attendance certificate
On completing the programme
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