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Benchmark Six Sigma Expert View by Venugopal R ‘Priority Consciousness’ is one of the key topics discussed in Management. Sometimes we do hear people saying the ‘Everything is equally important’.. however, in reality it becomes difficult and even inefficient if we do not prioritize our tasks. Principle of Pareto Analysis would not require any explanation for most members in this forum. Pareto principle, though named after the Italian economist Vilfredo Pareto, was popularized and adopted in the field of Quality Management by Joseph Juran. All the seven Quality tools are excellent methods to provide guidance to problem solving, but teams have to apply their minds, process knowledge and situational requirements for the best decisions. This applies for the usage of Pareto analysis as well. There could be many ways by which the Pareto analysis may not be done to get its best benefits, and some misuse as well. 1. Not considering severity We may use Pareto analysis to classify the defects of a product based on the frequency of occurrence for a period of time… for example, take the case of an electrical home appliance. Top most occurring defect could be a scratch on the panel, and the least occurring could be an insulation breakdown. Obviously, if the priorities are judged based on frequency of occurrence alone, without considering severity, it could be disastrous! It will be a good practice to perform FMEA as well, so that the priorities are not decided just based on the occurrences alone. 2. Using Pareto charts only as a presentation tool Pareto charts are meant to be tools used as part of causal analysis, but they also serve as good presentation method. If we draw up the pareto charts just for project presentation, and do not build them during the appropriate phase of the problem solving, it is a misuse. 3. Labeling ‘stratification’ as ‘cause’ Pareto analysis can be used for stratification of data as well as for causal analysis. For example, the sales figures of a particular product across 12 cities can be depicted using a pareto, as a stratification exercise. However, if you drill down to 10 reasons for poor sales and depict them using pareto for each city, then you are using the tool for causal analysis. Sometimes, the failure to differentiate between the two, could result in labelling ‘stratifications’ as ‘causes’ 4. Improper Grouping The purpose of pareto is to identify a pattern of “Vital few and Trivial many”. If one type of grouping is resulting in a flat pareto, you may have to try some other type of grouping. For example, if you are working on improving the productivity of processing invoices and you develop a pareto of the productivity by grouping them vendor wise… assume you get quite a flat pareto. This does not allow you to differentiate productivity levels across vendors, so, you may try to group the data based on types of invoices, irrespective of vendors and develop a pareto. Similarly, different types of grouping need to be tried to identify a pattern of ‘vital few’. 5. Making ‘Others’ too tall Lack of adequate grouping can result in a very tall ‘others’ bar. We have seen pareto charts where the ‘others’ bar come up as the tallest! Certainly, the thoughts and efforts for grouping have not been adequate. 6. Missing out on ‘Quick wins’ Many times, an occurrence with lower frequency could have an easy solution, with less efforts. You should not just keep putting efforts only as per the pareto sequence, failing to notice the quick wins. Pareto analysis finds application in all phases of DMAIC phase. However, this tool has to be applied with some logical thinking and subject matter knowledge. It is a tool that helps in giving a broad level of prioritization, which has to be used along with other considerations.

Misuse of tools and techniques is a very common phenomenon. Misuse of a tool primarily happens because of two reasons 1. Intentional Misuse (it is better to call it as Misrepresentation) 2. Unintentional Misuse (due to lack of understanding of the concept) Pareto analysis or the 80/20 rule is a prioritization tool that helps identify the VITAL FEW from TRIVIAL MANY. 80/20 implies that 80% of problems are due to 20% of the causes. Intentional Top 20% causes might not be the ones leading to bigger problems - usually it is observed that causes with smaller effects occur more often. Applying the Pareto principle will divert the focus of the team to the causes that have a smaller effect on the customer while the actual cause might be languishing in the trivial many Prioritization without keeping in mind the goal - Pareto will help if the significant contributors identified help us achieve the goal. However, it is seldom checked whether the VITAL FEW will help us achieve the goal or if there is a need to take a larger number of causes. As an example, if our goal is complete defect elimination, we will need to consider all causes. If our goal is elimination of 95% defects, we will need to cover more of the cause. Unintentional Going strictly by the 80/20 rule - some people take the 80/20 principle in the literal sense. They will do a Pareto plot and blindly apply the 80/20 principle. What needs to be noted is that 80/20 is a rule of thumb and it is not necessary to always have 80/20 split. It could also be 70/30 or 90/10 Keeping the total to 100 = 80+20. This is one of the most common misunderstanding of the 80/20 rule where one beliefs that the sum should always be 100. It could be 80/15 or 75/25 as well Unclear about the purpose of using a Pareto Analysis. Pareto can be used while defining afocus area and also in Root Cause Analysis to identify significant contributors. In the former, data is for problems and their occurrence while in the later, it is causes and their occurrence. Due to lack of clarity of purpose, if problems and causes are clubbed together in the same Pareto, then meaningful inferences cannot be drawn. Treating Pareto as a non-living tool - Pareto is usually done once and the same result is treated as sacrosanct for a long period of time. Pareto chart only provides a time snapshot. Over a period of time, the defect categories or causes and their occurrence numbers might also change and hence if Pareto Analysis is done at different points of time, it might yield different results Some that could fit in both categories Small data set - Pareto Analysis will help if you want to prioritize vital few from a big data set. Doing a Pareto analysis on 4-5 categories will seldom yield a good result Completely ignoring the trivial many - Pareto analysis helps identify the vital few but it does not say that one should ignore the trivial many. It simply states that first fix the vital and then move on to trivial. However, most people consider that if they fix the top 20%, they do not need to work on the remaining. Pareto can be used to continuously improve the process by repeatedly prioritizing the causes that you need to focus on Doing Pareto at a high level only - Like most of the tools in Root Cause Analysis, Pareto can also be used to drill down. E.g. Pareto can be done first to identify the top defect categories and then a second level Pareto can be done for the top defect categories (using the causes)