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Overview

Preliminary risk assessment (e.g., Likelihood X Impact) and the results of previous audits (e.g., number of NCs) are often used to help prioritize the audit schedule. While these are worthwhile to consider, they do not necessarily reflect the real-time performance of the processes that could be included in the audit plan. This means many audits are likely investing time and human resources in looking at processes that are performing adequately, while others that might be at greater risk are not considered due to lack of preliminary insights into how they may be performing.

Those insights can be gained by using analytics to slice & dice data to look for patterns, outliers or other signals that a further investigation (the audit) is warranted. That is, rather than conducting the audit in order to see if there are any control issues, analytics helps determine ahead of time whether or not there are potential issues to be explored.

Given the importance of audits for helping ensure that management systems based on ISO 9001/14001/45001/20000 etc. are both in place and operating effectively, audit program managers must continually be searching for ways to maximize the yield from their efforts. Analytics is one new method to add to the audit planning toolbox.

Why should you Attend

Organizations are continually looking for ways to improve the effectiveness and efficiency of their processes. The processes involved in managing an internal management system audit program (e.g., for ISO 9001, 14001, 45001, 22000, etc.) are no different, and are not deemed to be value-adding activities the customer is willing to pay for.

It is therefore incumbent on audit program managers to find ways to do more with less, and methods to focus audits where they are more likely to be needed or beneficial is one way to do this. While the concept of risk-based thinking isn't new, it is often done qualitatively versus quantitatively, and infrequently rather than as part of planning each audit.

This webinar will explain how analytics can be used to determine which processes warrant conducting an in-depth audit versus those that appear to be operating normally. Adding this to the audit planning process can help ensure that resources are being used judiciously.

Areas Covered in the Session

  • How analytics beats qualitative approaches to risk-based audit planning
  • Analytics methods that can be used (e.g., cluster analysis, correlation, distribution analysis, ratios)
  • Performing and making decisions on the analysis
  • Samples of the use of analytics for audit planning
  • How audit resource usage is maximized

Who Will Benefit

  • Personnel who management internal Quality
  • Environmental
  • Safety
  • IT, etc. 
  • Management system Audits
  • Quality Manager
  • EHS Manager
  • Quality audit program Manager
  • EHS audit program Manager
  • Lead auditors for quality/EHS/IT, etc.

Speaker Profile

Duke Okes has been a consultant & instructor for designing, implementing, auditing, fixing and improving management systems since 1985. He was formerly a quality engineer with TRW Automotive, and holds degrees in technology, business and education. He holds ASQ certification as a manager of quality/organizational excellence, quality engineer and quality auditor. He is the author of three books and dozens of articles on quality management topics, and has presented hundreds of workshops and spoken at numerous conferences on root cause analysis, quality auditing, failure mode & effects analysis, risk-based thinking, human error and other topics across the US as well as more than a dozen foreign countries. Since 2013 he has conducted more than five dozen webinars for a variety of providers.