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# Pareto Analysis Step by Step

~ By Duncan Haughey

Pareto Analysis is a statistical technique in decision-making used for the selection of a limited number of tasks that produce significant overall effect. It uses the Pareto Principle (also known as the 80/20 rule) the idea that by doing 20% of the work you can generate 80% of the benefit of doing the entire job. Take quality improvement, for example, a vast majority of problems (80%) are produced by a few key causes (20%). This technique is also called the vital few and the trivial many.

In the late 1940s Romanian-born American engineer and management consultant, Joseph M. Juran suggested the principle and named it after Italian economist Vilfredo Pareto, who observed that 80% of income in Italy went to 20% of the population. Pareto later carried out surveys in some other countries and found to his surprise that a similar distribution applied.

We can apply the 80/20 rule to almost anything:

• 80% of customer complaints arise from 20% of your products and services.
• 80% of delays in the schedule result from 20% of the possible causes of the delays.
• 20% of your products and services account for 80% of your profit.
• 20% of your sales force produces 80% of your company revenues.
• 20% of a systems defects cause 80% of its problems.

The Pareto Principle has many applications in quality control. It is the basis for the Pareto diagram, one of the key tools used in total quality control and Six Sigma.

In PMBOK, Pareto ordering is used to guide corrective action and to help the project team take steps to fix the problems that are causing the greatest number of defects first.

## Pareto Analysis

Here are eight steps to identifying the principal causes you should focus on, using Pareto Analysis:

1. Create a vertical bar chart with causes on the x-axis and count (number of occurrences) on the y-axis.
2. Arrange the bar chart in descending order of cause importance that is, the cause with the highest count first.
3. Calculate the cumulative count for each cause in descending order.
4. Calculate the cumulative count percentage for each cause in descending order. Percentage calculation: {Individual Cause Count} / {Total Causes Count}*100
5. Create a second y-axis with percentages descending in increments of 10 from 100% to 0%.
6. Plot the cumulative count percentage of each cause on the x-axis.
7. Join the points to form a curve.
8. Draw a line at 80% on the y-axis running parallel to the x-axis. Then drop the line at the point of intersection with the curve on the x-axis. This point on the x-axis separates the important causes on the left (vital few) from the less important causes on the right (trivial many).

Here is a simple example of a Pareto diagram, using sample data showing the relative frequency of causes for errors on websites. It enables you to see what 20% of cases are causing 80% of the problems and where efforts should be focussed to achieve the greatest improvement. In this case, we can see that broken links, spelling errors and missing title tags should be the focus.

The value of the Pareto Principle for a project manager is that it reminds you to focus on the 20% of things that matter. Of the things you do for your project, only 20% are crucial. That 20% produces 80% of your results. Identify, and focus on those things first, but don't entirely ignore the remaining 80% of the causes.

Topic: Pareto Analysis Step by Step
4/5 (9)
12th March 2020 7:11pm
Susan (Toms River) says...
Starting a new job. And I start with Pareto everytime. Focus my energy on the big 20% of SKUs, highest sellers and margins, customers... Also, use this to classify A,B,C,D similar to Peter's comment above. However, at a previous company the ratio was 97/3. Had never seen that before, but chalked it up to some severe issues: too many SKUs, excess stock, lack of rationalization, amongst other things. From these numbers I could see cashflow problems and lack of efficiency. What else can this indicate? Does anyone have other ideas or theories to share? Can ratios be influenced by industries? Would like collective brain thoughts on this please. Thank you all for your useful info.
4th February 2020 2:03am
Peter Earnshaw (Sheffield) says...
I've used Pareto analysis over a long number of years in a number of different companies. Rather than using it for one-off quasi scientific, research type projects, I added value to the basic theory. Using IT, I developed on-going monthly analysis, as a management information tool.

My running totals measured annual sales value and number of SKUs. In the case of my last employment, 85% of revenue came from 15% of the SKUs.

This was used as the focus for planning production requirements and, as a logical extension, for managing finished goods inventory.

I never used the Pareto Chart. For me, the monthly report was more than sufficient to provide a very keen refocusing of the company's product profile.

The enhancement I introduced to basic Pareto was to codify all products with A,B,C or D, based on where in the products list were. A = highest value products; D = lowest value products. That categorisation then determined the method of planning production and the inventory holding rules.

When you analyse your product profile in this way, you realise that the best impact on profitability and inventory reduction would be to delete all category D items.

I owe a good deal of my career success to Signor Pareto.

Peter Earnshaw
14th February 2019 4:18am
Jeff (La Verne) says...
This is the same process I was taught in an aerospace machine shop defined partially by Six Sigma and 5s. I was given certificates for achievements and everything. And here I thought the Fortune 500 company had come up with something new - LOL. I can tell you, the 80-20 rule works very well, right along with the 5 why process, the fishbone diagram and the corrective action report.
24th November 2015 10:45am
G Williams (Swansea) says...
This is very useful, but treats all faults equally (if it's used in the same way as the example graph). If a website had hundreds of missing tags, it might not have much of an effect on the browsing experience, whereas a couple of broken links can massively undermine the user experience.

It might be better to quantify the actual losses caused by the faults. For example, making the Z-axis represent losses in terms of money or time. That way the incidents that end up doing the most damage (even though they may occus less frequently) get the attention they deserve.
31st January 2016 11:02pm
Shaun Storbakken (Edmonton) says...
This is exactly what I was taught to do at university. We plotted the causes of failure along the X-Axis in the exact fashion shown here. The difference is that on the Y-Axis we plotted the cumulative cost of each failure type and ordered the causes of failure based on this metric. That way the most expensive types of failures as a percentage of the total failures are identified.
3rd February 2015 1:51pm
J Yeates (Birmingham) says...
I had never heard of Pareto Analysis before. It is an interesting way to record the ways in which we spend our time. It may help me and others to manage our time in a more effective way.

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