Lean Six Sigma is one of the most eye-catching terminologies in managerial affairs.
We point out the top reasons why data analytics courses in India are so popular with the Lean Six Sigma practitioners and project managers.
1 – Identify the Purpose of Lean Six Sigma Practices
Data Analytics professionals can help Project Managers align their overall QMS and practices with high quality intelligence derived from disparate information collected for analysis from various sources. These could be:
- Customer Survey results
- Employee survey results
- Internal product DevOps
- QC audits
- Non-conformance data
- Inventory and asset management data
2- Promoting Data, and Quality Management as a Culture Thing
Only a handful of industries have been successfully managed to fully understand and deploy Six Sigma principles. And, the count of organizations in these industries is appallingly low.
Imagine a challenging scenario:
Your product launch is next week, and your AI-based QMS dashboard suddenly reports:
“Your product is not up to the QC standards. Don’t release it next month.”
What would you do in such a scenario?
As a Project Manager, can you tell this to the Board of Directors that we have failed to plan and deliver on the product, and the QMS tells us not to release it?
The board rightfully retorts: Are you 100% sure that the product will fail? What does your data analyst team suggest?
The answer lies in the next pointer –
2- AI for Personalized Six Sigma Training Models
In the US, a majority of business leaders from the QC-intensive industries such as healthcare, pharma, automobile, and life sciences agree that AI tools can play a huge role as an ‘enabler’ in transforming the overall effectiveness of QMS.
At the core of any Lean project is human intelligence. Empowered by the new age power of Data Analytics, Six Sigma Project managers, and Product development professionals are training with AI and machine learning applications to facilitate innovations in “defect detection” and product improvements.
AI-based supervised learning can be used to augment human intelligence in designing the most advanced set of personalized Training, Learning, and Development modules for Quality management teams.
4 – Compliance and Quality Control Benchmarks
There are many quantitative methods of quality control and project improvements. As a concept, all business leaders are already aware of the benefits of addressing quality management challenges.
Data Analytics in Business Intelligence helps to continually enhance the operational quality and productivity. In most organizations, ISO 9000 is already established as the international benchmark of Quality Management systems. But, with the rapid rise of Digital tools, Six Sigma to has been accepted as an effective policy to ensure quality managers and product development teams have a clear understanding of customer requirements.
If you are a Lean 6 Sigma Project manager or a practitioner, you must find ways to improve the performance of one or more operations by leveraging data analytics courses to improve the product quality.