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At ComplianceQuest, our product and customer success teams continuously engage with quality engineers, quality leaders and risk management professionals. Through these conversations, we try to understand the common challenges they face on an ongoing basis.

One of our questions was: what is slowing down your non-conformance and CAPA management process? The answers mostly revolved around the following:

  • Early detection of non-conformances requires high-level of data visibility and it continues to be a challenge
  • Manually categorizing each and every NC and assessing for risk level is a time-consuming process for quality engineers
  • Do we move every non-conformance to a CAPA? Are we wasting time tackling NCs that are similar to earlier ones?
  • Reusing findings from earlier investigations of a non-conformance or CAPA process isn’t streamlined and is inefficient

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These conversations and structured interviews with quality teams led us to design CQ.AI and our approach of using AI to solve real issues faced by quality departments. In this blog, we focus on how we use AI to drive speed into process of dealing with a non-conformance.

For the product team at ComplianceQuest, it was critical to design AI capabilities that could drive business value.

We truly wanted to build a solution that would empower quality and safety managers – and, in fact, all users across your organization – to improve efficiency, decrease errors, and free up resources. Sign up for a demo of our powerful AI capabilities today!

AI-enabled Non-Conformance and CAPA Management: Saving Time and Increasing Effectiveness of Quality Teams

Implementing the appropriate corrective and preventative actions (CAPAs) is key to continuous improvement, but it is not possible without the early detection and correct handling of non-conformances (NCs), which requires vigilance and complete visibility into quality data.

Let’s say a non-conformance was detected with the latest lot of finished products based on product specifications. A Quality Engineer would have to classify the non-conformance and assign a risk to it which can be a greatly subjective decision. If the Quality Engineer is using ComplianceQuest, then an automatic recommendation for the category and risk priority of the non-conformance would be available to help in decreasing the chances of an error due to decision bias.

Upon reviewing non-conformance records, a Quality Manager would then have to determine if this is (or can become) a reoccurring issue with this particular product and what action should be taken. This would normally mean sifting manually through previous records, going through previous non-conformances, and trying to spot a trend, which can be time-consuming, subjective, and frustrating. Again, ComplianceQuest makes this process much easier by automatically identifying similar NC records and showing them to the Quality Manager with a score to determine reoccurrence and recommend escalation to CAPA.

If the non-conformance requires a CAPA to be opened, then a Quality Manager will need to begin an investigation to get to the root cause. But before opening a new investigation, the Quality Manager will need to make sure there isn’t a similar investigation that is already ongoing. Again, this means sifting manually through previous records, which can be time-consuming and frustrating except with ComplianceQuest. The platform automatically identifies similar CAPA records and allows the manager to directly link the CAPA record in question to an existing investigation to minimize duplicate entries and redundant work.

With this type of support, quality managers can truly implement a proactive approach that introduces continuous improvement to processes before major incidents and events, significantly decreasing the risk of non-compliance and the cost of quality.

Improving NC and CAPA Processes with AI

  • Identify similar Nonconformance to determine reoccurrence and recommend escalation to CAPA
  • Search for similar CAPA records linked to an existing investigation to minimize duplicate entry
  • Automated Categorization / Classification of Nonconformances
  • Automated Risk Prioritization of Nonconformances

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4 Key Benefits of using an AI-enabled Non-Conformance and CAPA Management Solution:

  • Reduction in labor costs and operational costs for the Quality department
  • Decreased manual or human errors and associated costs
  • Decreased risk and cost of major events with quicker investigation and resolution
  • Improved operational efficiency with comprehensive non-conformance and CAPA management

Try ComplianceQuest’s Nonconformance and CAPA Management solution, which is a part of our EQMS product suite, to experience the power of real AI. Watch the demos here:

https://www.compliancequest.com/demo-video/nonconformance-issues-management/
https://www.compliancequest.com/demo-video/corrective-and-preventive-actions-management/

In our next blog as part of our Applied AI series, we’ll be talking about the role of AI in handling safety incidents.

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