Introduction
The programme “Analyzing Customer Experience Quality Using Big Data” develops professional practice in Quality. 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 customer experience development and complaint handling to risk assessment, controls, and response, with practical work on quality management and process control, data analysis and decision support, procedure analysis and work simplification. Participants prepare outputs to support workplace application and review the quality and results of implementation.
Learning objectives
- Design a service journey and complaint response based on customer needs and follow-up evidence in an application related to “Analyzing Customer Experience Quality Using Big Data”.
- Apply a quality approach connecting beneficiary requirements with process control and improvement.
- Turn available data into documented analysis that supports a specific professional decision.
- Redesign a procedure to reduce delays and rework while maintaining controls.
- Prepare a risk register connecting causes, consequences, controls, and treatment responsibilities.
Learning areas
1. Customer Experience Development and Complaint Handling
- Define customer groups, expectations, and touchpoints, and map an actual journey including waiting, effort, and information exchange.
- Analyze the voice of the customer, complaints, and feedback, classifying recurring causes and linking them to the process, product, or communication channel.
- Set response, resolution, and escalation standards that consider the problem's impact, staff authority, and message clarity for the customer.
- Simulate a difficult service situation, applying listening, empathy, and fact verification, and offer a feasible solution or alternative.
- Build indicators for resolution time, complaint recurrence, and experience quality, and use results to address root causes and monitor impact. The application examines a case related to “Analyzing Customer Experience Quality Using Big Data”.
2. Quality Management and Process Control
- Define beneficiary requirements and product or service acceptance criteria, and translate them into testable process controls.
- Map process interactions, identifying risks, resources, records, and quality control responsibilities at handover points.
- Use cause and data analysis tools to understand nonconformities, and distinguish immediate correction from corrective action.
- Prepare a verification and internal review plan using objective evidence, referring to the current applicable edition of the relevant standard during implementation.
- Evaluate improvement results in terms of defects, time, rework, and beneficiary experience, and document knowledge that should be shared more widely.
3. Data Analysis and Decision Support
- Frame an analytical question linked to a specific decision, and define the unit of measurement, time period, and data needed to answer it.
- Check data quality for completeness, accuracy, consistency, and duplication, and document cleaning steps and limitations on reliance.
- Select appropriate comparisons, indicators, and charts, and distinguish statistical correlation from causal explanations of results.
- Interpret results in the work context, test assumptions and unusual values, and present alternatives and their associated uncertainty.
- Prepare an analytical report containing the finding, recommendation, data source and date, review owner, and next follow-up step.
4. 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.
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 customer journey map, complaint response guide, and service quality cards.
- A process map, nonconformity register, and quality improvement plan.
- A dashboard and decision memo explaining the data, assumptions, and alternatives.
- An improved procedure map, service profile, and acceptance criteria for implementation.
- 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 quality, according to their practical responsibilities.
- Professionals responsible for applying the outputs of “Analyzing Customer Experience Quality Using Big Data” 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 “Analyzing Customer Experience Quality Using Big Data” 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.