Why quality improvement is imperative in the big data era
Solving Tough Quality Problems: Keys to Success
“A key prerequisite is to rethink how we view improvement,” says Roger Hoerl, author of Statistical Thinking: Improving Business Performance. “I think we have to get away from the mindset that there’s going to be this latest and greatest technique – AI and machine learning, for example – that will somehow save the day.”
Hoerl gives an overview of the quality engineering landscape, discussing the reasons why quality improvement is an imperative in the big data era, the limitations of current state-of-the-art quality improvement approaches and the next era of continuous improvement.
Watch to learn more about the keys to success, including:
- A reminder that quality improvement occurs through process improvement.
- The importance of leadership.
- The primacy of subject matter knowledge.
- Keeping our focus on the problem, rather than the tools.
- Relying on a framework to tackle tough problems.
Xaar, NNE and IT&M Stats increase efficiency and effectiveness with modern quality engineering
How can your organization design products, processes and systems that meet or exceed customer and market expectations? With quality engineering, you can systematically use data to find more effective ways to get things done throughout the product life cycle, while minimizing the associated cost, waste and time. Industry experts talk about how to improve your competitive position with modern tools for quality engineering and make better use of data to identify and fix real problems.
You’ll hear from:
- Vasco Cachaco, Xaar
- Per Vase, NNE
- Delphine Attonaty, IT&M Stats