Data Analytics
Description
Statistical Process Control is all about boosting quality. Quality management can not only deliver value to customers and stakeholders, it can also enable data-driven decision making that helps organizations gain a competitive advantage in the marketplace. This intermediate-level course will introduce the basics of quality management, explaining the difference between quality control and quality assurance, providing methods for application of analysis, showing different applications of the Seven Basic Quality Tools. It all culminates in a brief case study, which illustrates the concepts covered.
credits
- PMI PDUs: 5
- Leadership PDUs: 2.5
- Strategic & Business Management PDUs: 0.5
- Technical PM PDUs: 2
- IACET CEUs: 0.5
- HRCI Credits: 5
- SHRM PDCs: 5
features
- Mobile-friendly
- Audio-enabled
- Badge and credit-awarding
- Real-world case studies
- Fully accessible
- Games & Flashcards
- Expert-supported
- Video content
learning Outcomes
- Describe principles that help guide quality management activities
- Use the Plan-Do-Check-Act cycle to coordinate work and implement change
- Explain the differences between quality control and quality assurance
- Create a SIPOC diagram to help visualize work as a process
- Explain the role that metrics and statistics play in measuring and controlling work processes
- Apply analysis and planning approaches to quality
- Explain how the Seven Basic Quality Tools are used to monitor and control quality processes
- Use the Seven Basic Quality Tools to process and sort non-numerical data
- Use the Seven Basic Quality Tools in combination to create powerful plans and solutions to quality problems
- Describe various quality management programs