Digital Transformation for Logistics and Transport Services Training Course

Course overview

Logistics and transport operators are under pressure to provide accurate shipment visibility, lower empty running, respond to disruption faster, and exchange reliable data across carriers, warehouses, ports, customers and regulators. Yet many transformation programmes stall because digital initiatives are selected as isolated technology purchases rather than being tied to a measurable operating problem. This course helps participants evaluate where connected transport data, automation, analytics and platform integration can improve service, cost, asset utilisation and resilience across end-to-end logistics operations.

Participants examine the digital operating model for road, rail, air, sea and warehousing environments. They learn to map logistics processes and pain points, assess digital maturity, define data requirements, design visibility and control-tower use cases, and prioritise initiatives through value, feasibility and risk assessment. The course covers transport management systems, warehouse management system integration, telematics, IoT events, APIs, GS1 EPCIS 2.0 event standards, Power BI analytics, process mining concepts, cybersecurity and implementation governance. Participants practise building business cases with operational KPIs such as on-time in-full performance, dwell time, cost per shipment, empty kilometres and inventory accuracy.

Delivery combines instructor-led briefings with logistics case work, data exercises and facilitated design workshops. Participants work with a realistic multi-carrier distribution scenario, translating fragmented shipment events into a target-state process, dashboard requirements and prioritised roadmap. They leave with a practical Digital Transformation Action Plan containing a current-state assessment, selected use cases, KPI baseline, data and integration requirements, stakeholder map, phased implementation roadmap and benefits measures that can be adapted for their own operation.

The course is designed for experienced logistics, transport, supply chain, operations and technology professionals who contribute to digital investment decisions or lead process improvement across transport networks, warehouses and distribution services.

Course objectives

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

• Map an end-to-end transport and logistics process using SIPOC and value-stream mapping to identify digitalisation opportunities
• Assess logistics digital maturity across data, systems, processes, workforce capability, governance and cybersecurity
• Define a shipment-visibility use case using milestones, exception rules, data owners and GS1 EPCIS 2.0 event requirements
• Design a KPI dashboard specification in Power BI for OTIF, dwell time, cost per shipment, empty kilometres and exception ageing
• Evaluate TMS, WMS, telematics and IoT integration options using API, data-quality and interoperability criteria
• Prioritise digital initiatives with a value-versus-feasibility portfolio and quantified benefits assumptions
• Build a transformation business case including baseline metrics, investment costs, risks, benefits owners and implementation stages
• Produce a phased logistics digital transformation roadmap with governance milestones, pilot scope and adoption measures

Benefits of attending

Target competencies

Who should attend

• Logistics Managers — who must improve service performance, asset utilisation and operating cost across distribution networks
• Transport Managers — who need usable visibility, carrier performance data and better exception-management processes
• Supply Chain Managers — who coordinate digital initiatives across planning, warehousing, transport and customer service
• Warehouse and Distribution Centre Managers — who need WMS, transport and inventory data to work as one operating process
• Digital Transformation and IT Managers — who translate operational requirements into practical architecture, integration and rollout plans
• Continuous Improvement Managers — who need to convert process waste and performance gaps into prioritised technology-enabled initiatives

Requirements and prerequisites

Participants should have practical experience of logistics, transport, warehousing or supply chain operations and be familiar with common measures such as service level, lead time, cost per shipment, utilisation and inventory accuracy. A working understanding of at least one operational system, such as a TMS, WMS, ERP platform, fleet telematics portal or reporting dashboard, is helpful. Participants should be comfortable interpreting tables and basic charts in Excel. Prior coding, database administration, data-science expertise or Power BI development experience is not required; the course focuses on making sound operational and investment decisions rather than programming solutions.

Training methodology

The programme uses instructor-led briefings to establish transport and logistics digitalisation methods, followed by hands-on work with a multi-carrier distribution case. Participants map processes, review sample shipment-event data, define dashboard measures in Power BI and compare TMS, telematics and API integration choices. Small groups test use cases against operational constraints such as carrier adoption, data quality, cybersecurity and change resistance. Each day adds a component to an individual transformation plan, culminating in a facilitated roadmap review and peer challenge session.

Course outline

Day 1: Digital logistics strategy and operating-model diagnosis

• Digital transformation drivers in freight transport, warehousing and distribution
• Current-state process mapping with SIPOC and value-stream mapping
• Logistics digital maturity assessment dimensions and scoring
• Customer journey and shipment lifecycle pain-point analysis
• Operational KPI trees for service, cost, utilisation and resilience
• Digital use-case categories from planning through last-mile delivery
• Target operating model principles for digitally enabled logistics

Workshop: Participants map a distribution process, identify failure points in the shipment lifecycle and produce a scored digital maturity heat map.

Day 2: Data, visibility and connected transport operations

• Shipment milestones, planned-versus-actual events and exception management
• GS1 EPCIS 2.0 event model for logistics traceability
• Telematics, IoT sensors and asset-location data sources
• Data quality profiling for completeness, timeliness, accuracy and consistency
• Master data requirements for locations, carriers, equipment and products
• API, EDI and event-stream integration patterns
• Control-tower design principles and escalation workflows

Workshop: Participants define a shipment-visibility event model and exception workflow for a multi-carrier transport network.

Day 3: Systems, analytics and automation choices

• TMS capabilities for planning, execution, freight audit and carrier management
• WMS and TMS integration across dispatch, loading and proof of delivery
• SAP Transportation Management process and data touchpoints
• Power BI data model concepts for logistics performance reporting
• Dashboard measures for OTIF, dwell time, cost per shipment and empty kilometres
• Process mining concepts for conformance checking and bottleneck detection
• Automation opportunities using workflow rules, RPA and predictive alerts

Workshop: Participants create a Power BI dashboard specification and select automation opportunities from a delayed-delivery dataset.

Day 4: Value cases, risk controls and implementation governance

• Benefits baselining and KPI measurement plans
• Value-versus-feasibility prioritisation matrix for digital initiatives
• Total cost of ownership for logistics platforms and integrations
• Business case assumptions for service, capacity, cost and working-capital benefits
• Cybersecurity controls for connected fleets and logistics data exchange
• Vendor evaluation criteria for interoperability, scalability and data ownership
• Programme governance, product ownership and change-adoption roles

Workshop: Participants build a prioritised initiative portfolio and draft a quantified business case for one selected logistics use case.

Day 5: Roadmap design and transformation delivery

• Pilot selection criteria and minimum viable product scope
• Phased roadmap sequencing for data foundations, integration and scale-up
• Stakeholder mapping across operations, IT, carriers, customers and partners
• Change-impact assessment for dispatchers, planners, drivers and warehouse teams
• Data governance roles, decision rights and issue-management routines
• Implementation risk register and mitigation planning
• Transformation scorecards and benefits-realisation reviews

Workshop: Participants complete and present a 12-to-18-month digital transformation action plan with roadmap, governance model, KPIs and pilot measures.

Tools & standards covered

Power BI, SAP Transportation Management, Azure IoT Hub, GS1 EPCIS 2.0

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