Frameworks: Root Cause Analysis

About the Course

Root Cause Analysis provides a structured approach to identifying and resolving problems by addressing their underlying causes rather than just the symptoms. This course teaches practical problem-solving techniques that can be applied to both personal and professional challenges, improving decision-making and long-term outcomes. Whether tackling workplace inefficiencies, recurring personal issues, or team management obstacles, you will develop critical thinking skills to create sustainable solutions.

Course Information

Categories:

Learning Objectives:

  • Understand the importance of Root Cause Analysis (RCA) and its role in long-term problem resolution.
  • Apply RCA methodologies, including the 5 Whys, Fishbone Diagram (Ishikawa), and Pareto Analysis, to identify causes effectively.Distinguish between symptoms and root causes to prevent recurring issues.
  • Develop actionable solutions based on comprehensive analysis, rather than temporary fixes.
  • Utilize data-driven decision-making to enhance accuracy and impact in problem-solving.
  • Build a proactive mindset that fosters efficiency, continuous improvement, and innovation.

Course Instructor

Moneyling Moneyling Author

Introduction

Root Cause Analysis in Real Life
0

Structured Questioning Techniques

5 Whys
0
Drill Down Analysis
0

Cause-and-Effect Visualization

Fishbone Diagram (Ishikawa)
0
Fault Tree Analysis (FTA)
0
Current Reality Tree (CRT)
0

Data-Drvien RCA Methods

Pareto Analysis (80/20 Rule)
0
Failure Mode and Effects Analysis (FMEA)
0
Change Analysis
0
Statistical Process Control (SPC)
0

Systemic and Process-Based RCA Approaches

Kaizen RCA
0
8D Problem-Solving
0
Apollo Root Cause Analysis
0
Bowtie Analysis
0

Root Cause Analysis with Python

Why Python
0
Data Analysis & Visualization for RCA
0
Statistical Process Control (SPC)
0
Machine Learning for RCA
0
Failure Mode and Effects Analysis (FMEA)
0
Natural Language Processing (NLP) for RCA
0
Time Series Analysis for RCA
0

Course Outline

  • Introduction
    • Root Cause Analysis in Real Life
  • Structured Questioning Techniques
    • 5 Whys
    • Drill Down Analysis
  • Cause-and-Effect Visualization
    • Fishbone Diagram (Ishikawa)
    • Fault Tree Analysis (FTA)
    • Current Reality Tree (CRT)
  • Data-Drvien RCA Methods
    • Pareto Analysis (80/20 Rule)
    • Failure Mode and Effects Analysis (FMEA)
    • Change Analysis
    • Statistical Process Control (SPC)
  • Systemic and Process-Based RCA Approaches
    • Kaizen RCA
    • 8D Problem-Solving
    • Apollo Root Cause Analysis
    • Bowtie Analysis
  • Root Cause Analysis with Python
    • Why Python
    • Data Analysis & Visualization for RCA
    • Statistical Process Control (SPC)
    • Machine Learning for RCA
    • Failure Mode and Effects Analysis (FMEA)
    • Natural Language Processing (NLP) for RCA
    • Time Series Analysis for RCA
Scroll to Top