Logistics Quality Performance and Productivity Training Course

Course overview

Logistics teams are expected to move more orders with fewer errors, shorter cycle times and tighter labour budgets, yet performance discussions often rely on broad monthly figures that conceal the cause of failures. Late dispatches, picking errors, inventory discrepancies, loading damage, detention costs and rework can originate in different parts of the warehouse-to-delivery flow. This course equips logistics professionals to measure those losses accurately, distinguish normal variation from operational breakdowns, and prioritise improvement work against service, cost and risk targets.

Participants learn to build a practical quality and productivity management system for warehouse, transport and distribution operations. The course covers process mapping, critical-to-quality requirements, logistics KPIs, baseline measurement, Pareto analysis, root-cause investigation, statistical process control, labour productivity analysis and corrective-action control. Participants work with measures such as order accuracy, on-time-in-full, dock-to-stock time, lines picked per labour hour, trailer turnaround, inventory record accuracy, damage rate and cost of poor quality. They also learn to turn operational data into clear dashboards and improvement charters that managers can approve and frontline teams can use.

Delivery combines instructor-led explanation with realistic distribution-centre and transport cases, spreadsheet analysis, facilitated problem-solving and peer review. Participants practise using Excel, Power BI and Minitab to analyse logistics performance data, test likely causes and present findings. Each participant leaves with a completed Logistics Quality and Productivity Improvement Pack: a KPI tree, current-state process map, baseline analysis, root-cause record, prioritised countermeasure plan and 90-day implementation roadmap for a selected operational problem.

The course is suited to professionals who already work with logistics operations and need a disciplined way to improve service reliability, throughput and cost performance across warehouse and transport processes.

Course objectives

By the end of this course, participants will be able to:

• Define a logistics KPI tree linking customer service, quality, productivity, cost and safety measures
• Map warehouse and transport processes using SIPOC and swimlane process maps
• Calculate baseline performance for OTIF, order accuracy, labour productivity, inventory accuracy and damage rates
• Analyse operational loss data using Pareto charts, run charts, control charts and stratification
• Conduct root-cause investigations using 5 Whys, fishbone diagrams and cause-and-effect verification
• Build an Excel and Power BI dashboard for daily logistics quality and productivity review
• Develop corrective and preventive action plans with owners, due dates, controls and verification measures
• Produce a 90-day logistics improvement roadmap supported by a quantified business case

Benefits of attending

Target competencies

Who should attend

• Warehouse Managers — who must improve throughput, accuracy and labour performance without weakening service controls
• Logistics Managers — who need to connect warehouse, transport and delivery KPIs to customer commitments and operating cost
• Distribution Centre Supervisors — who manage daily exceptions, team output and adherence to standard work
• Transport Operations Managers — who need to reduce delivery failures, loading errors, turnaround delays and carrier-related waste
• Continuous Improvement Specialists — who facilitate Lean and quality projects in logistics and distribution environments
• Supply Chain Analysts — who convert WMS, TMS and ERP data into actionable operational performance insight

Requirements and prerequisites

Participants should have at least six months of experience in warehouse, distribution, transport or logistics support operations, and be familiar with common measures such as orders shipped, delivery performance, inventory accuracy, labour hours and operating cost. They should be able to use Microsoft Excel for basic formulas, sorting, filtering and charts. Experience with a WMS, TMS or ERP reporting environment is useful because course examples use operational extracts, but no particular system is required. Prior Lean Six Sigma certification, statistical training, Power BI expertise or Minitab experience is not required; these methods are introduced and applied in a logistics context.

Training methodology

The course uses short instructor-led sessions to introduce each method, followed by hands-on analysis of warehouse and transport data sets. Participants construct process maps, calculate KPIs in Excel, create visualisations in Power BI and interpret variation using Minitab outputs. Cases include picking inaccuracies, dock congestion, late delivery and inventory-record errors. Small groups test root causes, challenge assumptions and develop countermeasures. The final day is an application workshop in which each participant assembles a practical improvement pack and receives instructor feedback on measures, controls and implementation priorities.

Course outline

Day 1: Measuring logistics quality and productivity

• Customer requirements and critical-to-quality measures in logistics
• Quality, service, productivity and cost KPI definitions
• OTIF, order accuracy and inventory-record accuracy calculations
• Labour productivity measures for receiving, picking, packing and loading
• Cost of poor quality in warehouse and transport operations
• KPI trees linking strategic targets to frontline measures
• Data definitions, measurement frequency and source-system ownership

Workshop: Participants build a KPI tree and baseline scorecard for a distribution-centre scenario using a supplied operational data extract.

Day 2: Mapping flow and identifying operational waste

• SIPOC analysis for warehouse-to-customer order fulfilment
• Swimlane mapping across warehouse, transport and customer-service roles
• Value-added, non-value-added and necessary non-value-added activity analysis
• Warehouse waste categories and their observable indicators
• Standard work and process adherence checks
• Constraint identification using capacity, queue and cycle-time data
• Failure-mode mapping for picking, loading and delivery handoffs

Workshop: Participants create a current-state swimlane map, identify bottlenecks and produce a waste-and-failure register for a delayed dispatch process.

Day 3: Analysing variation and finding root causes

• Pareto analysis of defects, delays and exception reasons
• Run charts and control charts for logistics process stability
• Stratification by shift, zone, SKU, carrier, customer and operator
• Process capability concepts for cycle-time and accuracy requirements
• Fishbone diagrams for people, process, equipment, material and data causes
• 5 Whys investigation and evidence-based cause verification
• Minitab analysis of operational variation and out-of-control signals

Workshop: Using a picking-error case, participants produce a Pareto chart, control-chart interpretation and verified root-cause statement.

Day 4: Designing controls and improving performance

• Countermeasure selection using impact-effort and risk criteria
• Corrective action and preventive action workflow design
• Error-proofing methods for scanning, labelling, slotting and loading
• Visual management and daily performance-management boards
• Standard work documents and supervisor confirmation routines
• Control plans with leading indicators, trigger limits and escalation paths
• Power BI dashboard design for daily logistics performance review

Workshop: Participants design a corrective-action plan and prototype a Power BI performance dashboard for a recurring loading-quality problem.

Day 5: Leading a logistics improvement project

• Improvement charter scope, problem statement and target condition
• Baseline-to-target benefit calculation and savings validation
• Stakeholder analysis for operations, IT, carriers and customer service
• Pilot design, test measures and implementation risk controls
• 90-day improvement roadmap with milestones and accountable owners
• Management review packs and operational storytelling with data
• ISO 9001-aligned evidence for monitoring, nonconformity and corrective action

Workshop: Participants complete and present a Logistics Quality and Productivity Improvement Pack containing their charter, analysis, countermeasures, control plan and 90-day roadmap.

Tools & standards covered

Microsoft Excel, Microsoft Power BI, Minitab Statistical Software, ISO 9001:2015

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions