Last year the Chartered Quality Institute embarked on detailed research on Quality 4.0 of which I was a part. The research was conducted by Oakland Group by no other than Professor John Oakland. The principles are defined and the foundation for propelling the profession into the future is laid out.
3 years ago I joined The Baltic Exchange to set up the Quality department, a journey that is so rewarding it keeps on giving.
The result? The deployment of Quality at the Baltic and the collaboration between data science and quality were deemed a success story and essential to the transformational programme, a case study was published. There are a total of 4 case studies showcasing what good looks like, this is the first and it aligns to 3 of the 8 principles of Quality 4.0.
Here is the summary and the report:
Digitalisation and Quality 4.0 has been fast-forwarded by the Covid-19 pandemic, and the Baltic Exchange has had to implement the new system remotely, bringing huge positive changes to people through digital working.
Quality 4.0 defined 8 principles that should be considered in today’s Quality Management world. Here are the three principles this case study highlights:
- Data Value
- Transparency and Collaboration
I think, for me personally, before we dive deep into the principles, it is important to acknowledge that as a Quality Professional, I do not claim to be a data scientist. And the Data Scientist whom I worked with did not claim to be a quality professional either. It was a collaboration that can only be described and respectful and trust worthy. We both understood each others capabilities and what we could bring to the business. And that was the start of it, which really represented the principle of Transparency and Collaboration within Quality 4.0.
Deploying a quality framework in a regulated framework that is based on data generation had to be robust. the framework has to have assurance policies, and procedures to integrate all the systems and touch points that are relevant. That’s were Cybernetics principle comes in handy. Quality professionals can understand that systems are designed differently and the way they display data ask output differ. This fundamental understanding is driven from the tools they use daily in process making, customer experience, and process improvement techniques.
With so many data available, we have the choice to do 2 things: ignore it the wealth of data we have, or understand what information it gives us. Having the commitment to drive improvement easily trigger the curiosity in Quality Professionals. What data points can we look at? What data is forming noise to the scope of our management system that we should set aside? How does the business look at this data? Working with Data Scientist can help us understand the data that is available for the business. After all we are driven by factual and risk based decisions. Understanding the Data Value will help Quality Professionals set governance framework and control metrics to ensure it supports the integrity of the business.
How are you interacting with Quality 4.0? Are there one or more principles you are working with? Please get in touch and lets discuss.
You can read about the Quality 4.0 principles and the research here. If you want to keep up with the case studies published by the CQI, please check them on here
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