Progressive Analytics Framework in Quality 4.0 PPT

This PPT slide, part of the 25-slide Quality 4.0 Series: Pillars (Part I) PowerPoint presentation, outlines the 4 categories of analytics within the Quality 4.0 framework, emphasizing their progressive nature. It presents a clear structure, categorizing analytics into Descriptive, Diagnostic, Predictive, and Prescriptive types. The first 3 categories are applicable to traditional data, while the Prescriptive category is exclusively linked to machine learning and artificial intelligence.

Descriptive analytics focuses on historical data to answer the question of "What happened?" This approach utilizes conventional metrics to identify known or suspected correlations, such as the number of open Quality events. The slide illustrates that this is foundational, providing essential insights into past performance.

Moving to Diagnostic analytics, it seeks to understand "Why it happened?" This form employs advanced techniques like data discovery and correlations, enhancing the depth of analysis beyond mere observation. It allows organizations to investigate underlying causes of past events, offering a more nuanced understanding of data.

Predictive analytics answers "What will happen?" by generating insights based on historical patterns. It aims to forecast future outcomes, such as predicting machine failures. This category is crucial for proactive decision-making, enabling organizations to anticipate issues before they arise.

Finally, Prescriptive analytics, which is highlighted as the wave of the future, addresses "What action to take?" It not only predicts potential failures, but also recommends actions to mitigate risks. This category leverages advanced technologies, showcasing the transformative potential of analytics in the Quality 4.0 era. The slide effectively communicates the importance of each category in driving informed decision-making and strategic planning.

This slide is part of the Quality 4.0 Series: Pillars (Part I) PowerPoint presentation.

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