12 Table 5.12 Analyzing and Interpreting QAPI Data


IMPROVING MEAL SATISFACTION SCORES 1. Identify the issue


The QAPI team notices that client meal satisfaction scores have been declining over the past few months. 2. Collect Data


Data is gathered from various sources: • Client Surveys: Feedback on meal quality, variety, and temperature • Food Waste Logs: Records of uneaten food. • Staff Feedback: Insights from kitchen and serving staff


3. Analyze Data


The team uses tools like Pareto charts and root cause analysis to understand the data: • Client Surveys: Indicate dissatisfaction with meal temperature and variety. • Food Waste Logs: Show high waste for certain meals. • Staff Feedback: Highlights issues with meal preparation and serving delays. • Temperature Logs: Reveal that food often cools down before reaching clients.


4. Interpret Finds


The analysis points to several key issues: • Meals are not staying hot enough by the time they reach clients. • Limited variety in meal options is leading to dissatisfaction. • Delays in meal preparation and serving are contributing to the problem.


5. Develop and Implement Interventions


Based on the findings, the QAPI team develops targeted interventions: • Improve Meal Delivery: Implement insulated trays to keep food hot. • Expand Menu Options: Introduce more variety in meal choices. • Streamline Processes: Optimize meal preparation and serving schedules to reduce delays.


6. Monitor and Evaluate


The team sets benchmarks and monitors the impact of interventions: • Benchmark: Increase meal satisfaction scores by 15% over the next quarter. • Monitoring: Regularly review client surveys and food waste logs to assess progress.


7. Report and Communicate


Regular updates are shared with staff and stakeholders to ensure everyone is informed and engaged in the improvement process.


Source: Handy, 2016


SUPPLEMENTAL MATERIAL


Foodservice Management—By Design


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