Introduction
The programme “Data Analytics Techniques for Improving Supply Chain Processes” develops professional practice in Supply Chains and Logistics. It connects the subject with workplace challenges by examining existing evidence and practices and choosing methods appropriate to the organization and its available resources.
The learning progresses from supply chain and logistics planning to risk assessment, controls, and response, with practical work on procedure analysis and work simplification, inventory, warehouse, and custodial asset control, procurement planning and supplier evaluation. Participants prepare outputs to support workplace application and review the quality and results of implementation.
Learning objectives
- Analyze supply flows and design alternatives that reduce disruption and improve order fulfillment in an application related to “Data Analytics Techniques for Improving Supply Chain Processes”.
- Redesign a procedure to reduce delays and rework while maintaining controls.
- Control inventory movements and set reorder levels using demand data.
- Prepare a purchasing plan and bid comparison based on needs, specifications, and published criteria.
- Prepare a risk register connecting causes, consequences, controls, and treatment responsibilities.
Learning areas
1. Supply Chain and Logistics Planning
- Map material, information, and financial flows from supplier to beneficiary, identifying dependencies, bottlenecks, and delays.
- Compare demand forecasts with available capacity and supply dates, and build a coordination plan across purchasing, inventory, production, and distribution.
- Evaluate transportation, storage, and sourcing alternatives in terms of cost, duration, reliability, and relevant contractual terms.
- Test a supplier or transport route disruption scenario, and define alternatives, minimum levels of critical materials, and the escalation path.
- Build indicators for on-time delivery, cost, losses, and service levels, and use them to review the performance of supply chain participants. The application examines a case related to “Data Analytics Techniques for Improving Supply Chain Processes”.
2. Procedure Analysis and Work Simplification
- Define the procedure's start, end, owner, inputs, and outputs, and collect data on processing time, waiting, and rework.
- Map the actual workflow between roles, identifying approvals, handovers, bottlenecks, and duplicate data entry.
- Analyze the value added by each step and the controls it provides, and propose combining, removing, or running steps in parallel with reasons for the choice.
- Document the improved procedure with clear authorities, forms, timelines, and standards, and review its effects on beneficiaries and delivery teams.
- Test the procedure on a limited case, measure time, errors, and output quality, and document adjustments and the rollout plan.
3. Inventory, Warehouse, and Custodial Asset Control
- Classify items by value, movement, criticality, and storage requirements, and connect each classification to the required level of monitoring and control.
- Define the cycle of receiving, inspection, coding, storage, issuing, and returns, and document segregation between custody, recording, and approval.
- Analyze consumption and lead-time data to estimate reorder points and safety stock, stating assumptions and estimation limitations.
- Design periodic or full stocktaking and documented reconciliation of differences, examining causes of losses, slow-moving and damaged stock, and data quality problems.
- Improve warehouse layout, movement routes, and preventive requirements, and monitor accuracy, availability, turnover, and holding costs.
4. Procurement Planning and Supplier Evaluation
- Analyze the need, request timing, and life-cycle cost, checking for alternatives available in inventory or existing contracts.
- Write clear specifications, scope of work, and acceptance criteria, avoiding restrictions that the nature of the need does not justify.
- Study the supplier market, define the procurement method, timetable, and authorities, and refer to applicable regulations and policies.
- Compare bids using published technical and financial criteria and documented weights, and prepare a record showing assessment evidence and potential conflicts of interest.
- Build a mechanism for monitoring delivery, quality, obligations, and change, and measure supplier performance and address noncompliance.
5. Risk Assessment, Controls, and Response
- Define the work context, objectives, and assessment boundaries, and distinguish the risk source, potential event, and effects on results.
- Gather risks from processes, data, past incidents, and interviews with responsible staff, and document causes and existing controls.
- Estimate likelihood and impact using stated criteria, and review control effectiveness to determine residual risk levels.
- Select a response proportionate to the risks, resources, and authority, and specify the owner, deadline, and early warning indicator.
- Test a scenario involving changing circumstances, update the risk register, and present material risks and required decisions to the appropriate authority.
Practical outputs
- A supply chain map, demand and supply plan, and logistics risk register.
- An improved procedure map, service profile, and acceptance criteria for implementation.
- Inventory cards, a stocktaking plan, and an item classification and reorder matrix.
- A procurement plan, supplier evaluation matrix, and contract follow-up template.
- A risk register, control matrix, and prioritized treatment plan.
Who should attend
- Practitioners, specialists and supervisors whose work relates to the programme subject.
- Managers and teams working in supply chains and logistics, according to their practical responsibilities.
- Professionals responsible for applying the outputs of “Data Analytics Techniques for Improving Supply Chain Processes” within their organizations.
Prerequisites
- Working familiarity with the programme field and the ability to discuss a professional case or challenge.
- Confirm the suitability of your experience and any specialist prerequisites with the Union before participation.
Conclusion
The programme “Data Analytics Techniques for Improving Supply Chain Processes” brings together concepts, case review and a practical application. Participants prepare steps that can be adapted to their responsibilities and organizational resources, with an indicator to follow application and review results after returning to work.
Participation arrangements and any special requests are specified in the confirmation issued by the Union.