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Adoption of a data driven decision making approach to implement and sustain a continuous improvement culture in the food industry
Manufacturers face complex challenges in delivering quality products to successfully gain competitive market share. Organizations must learn how to collect and interpret data about process performance to discover best practices. Risk of food quality non-conformance can lead to holds and customer complaints. When data is captured quality management tools can be used to identify root causes and drive corrective action plans for non-conformances. Monitoring process data allows management to design improvements that overcome a culture of status quo, as in “if it’s not broken, don’t fix it.” This thesis focuses on five factors that directly contribute to product quality improvements. Tracking key performance indicators in real-time assures products is going to delight customers and simultaneously meet quality compliance standards. Continuous improvement is a commitment by management to create a culture of data analysis to identify improvements that allow manufacturers to gain a competitive market advantage.