Data visualizations in combination with the expertise of a QA personnel such as Quality and risk identification and root-cause analysis can transform the way quality is managed
Method
Not a study but shows the use of visualizations in QA.
Results
Metrics has been used in the clinical research industry for many years to measure quality performance. Despite use of such metrics occurrence and recurrence of quality issues are not uncommon. One of the key challenges is the task of aggregating and decoding large number of data points. In the context of Quality assurance, the complexity increases because of the onerous task of requiring to correlate, identify outliers, patterns to zero in on anomalies to probe into processes and root-cause analysis. Data metrics provide information to certain extent but in the practical sense it means connecting many dots to determine insights. Recent advances in technology has complemented this process well through data visualizations
Conclusion
Transforming Quality metrics into insights and the way ahead.
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