Pareto Analysis
Pareto Analysis uses the Pareto Principle, also known as the 80/20 Rule, based on which 80 percent of problems can be traced back to 20 percent of causes.
The objective of pareto analysis is to find out which problems or problem areas have maximum contribution to the user's pain point and accordingly decide on the priority. As a general rule of thumb, we pick those problems that together contribute to 80% of the observed pain points. Pareto analysis can be done among and within the affinity groups, to prioritize problems from the entire list for further analysis.
Failure mode & Effect analysis
Failure Modes and Effects Analysis (FMEA) is a systematic method to identify possible failure areas, which will have maximum impact on the process.
FMEA analysis is an alternate and more detailed mechanism to identify the problems that should be solved on priority, to maximize impact on User's pain-point. It is based on evaluating the problem from three aspects - Occurrence, Detection, and Severity (ODS) and decide on prioritization.
Occurrence: What is the probability of occurrence of problem? (It is rated from 1-10; 10 being the Highest probability)
Detection: In case the problem occurs, how often it can be detected and addressed, before it affects the user? (It is rated from 1-10; 1 being the Highest probability)
Severity: In case the problem reached to the user, how severe would be its impact on the user? (It is rated from 1-10; 10 being the Most Severe)
Priority of the problem is calculated as Risk Preference Number (RPN), which equals to Rating (O) x Rating (D) x Rating (S). The problems with high RPN numbers are prioritized.
scatter diagram
A scatter diagram is used for analyzing relationships between two variables for determining how closely they are related.
All causal relationship are always in correlation. Scatter diagram helps to validate if a problem and a pain-point are corelated to each other or not. If there is no correlation, there cannot be any causal relationship as well. Therefore, we can eliminate those problems from further analysis. One variable is plotted on the horizontal axis and the other is plotted on the vertical axis. The pattern of their intersecting points graphically show relationship patterns - if they are too scattered, there is no correlation; if they are grouping around a trendline, there is a correlation.