What is Root Cause Analysis (RCA)? How to do an effective RCA: We have to understand first what does meaning of Root Cause is? Basically, the root cause is defined as a factor that caused a nonconformance and should be permanently reduced or eliminated through process improvement.
The root cause is a high-level issue that leads to the main problem of the process or product.
History of Root Cause Analysis (RCA)?
RCA (Root Cause Analysis) can be traced to the broader field of TQM (Total Quality Management). Root Cause Analysis (RCA) is a part of a more general problem-solving process and an integral part of continuous improvement.
The Root Cause Analysis (RCA) in itself does not produce any result, It must be a part of the larger problem-solving effort for Quality Improvement.
How and When Should Conduct an RCA (Root Cause Analysis)
A typical design of Root Cause Analysis in an organization follows the below-mentioned steps:
- Form a small team to conduct a Root Cause Analysis (According to the criticality of the process)
- The team member is selected from the business, process, and area of the organization that experiences the problem.
- The team might be supplemented by: a) A-Line manager who has the authority to implement the solution. b) An Internal Customer of the process with the problem. c) A Quality Improvement expert (Master Black Belt or Black Belt) of the process.
- The Root Cause Analysis lasts about two months. During the Root Cause Analysis, equal emphasis is placed on defining and understanding the problem of process and product or services and brainstorming on possible causes. Analyzing Cause and Effect, and devising a solution to the problem.
Which tools we can use for Root Cause Analysis in BPO or calling process?
Many methodologies, approaches and techniques are there to conduct a Root Cause Analysis (RCA). The below mentioned mostly use the method and techniques.
- Cause and effect analysis through Fishbone diagram
- 5 Why Analysis
- Event and Causal factor Analysis
- Kepner-Tregoe Problem-solving and decision making
