Sometimes “enough” means “too much”.

The Pareto Principle is a decision making tool used in industry. Also known as the 80–20 rule, it came out of observations made by the Italian economist Vilfredo Pareto that 80% of the land in Italy was owned by 20% of the population. He made other observations where this rule of thumb applied, roughly but consistently enough.

I used this simple tool frequently during analyses of data on causes for scrap when I worked at the factory that made industrial and hydraulic hoses.

To look at the numbers without some organization was confusing because of the number of possible scrap causes in the product made where I worked. If one wanted to reduce scrap by working on causes, then one needed to grasp where the most value gained for time, resources, and people used would be. The Pareto Principle quickly organized data into a format that did just that.

I mention this little tool because I find I need to review the blogs I follow in some meaningful way and to help me cull those that aren’t for me.

In the meantime, I worked up an example of how applying the Pareto Principle helps point you in the right direction. It is just an example, I note, and the “causes” are just made up, as are the data.

Chaos at the start; clarity at the end.

Chaos at the start; clarity at the end.

I highlighted the major “causes” (“the significant few”) with red boldface so you can see how data accumulated randomly might appear in part A., can gain a little clarity by calculating percentages of the total in part B., but become strikingly obvious in Pareto order (largest to smallest) in part C. The last column, with the accumulated percentage, by “cause”, shows how data needn’t be a 80-20 split to be useful, just approximately 80-20 for the underlying principle to hold true: You get the biggest bang for your buck by working on reducing or eliminating the items marked in red boldface even though they just approximate the mythical 80%.

Why am I putting you through this little tutorial on use of a simple statistical tool? It’s the way I think about problems, even after over four and a half years of retirement. My example lists some of what one might regard as potential problems worthy of a look.

If I made a Pareto analysis of what I don’t like enough about blogs to cause me to unfollow them, it might look something like the fictional part C. table above. Or it might include causes that demand immediate attention and a lot less of this navel gazing. For example, some blogs take up a lot of time to follow.

Here’s a real life example of the time issue. One blogger’s new posts and new comments notifications accounted for the biggest single part of what I opened every day. It became a burden. Though I mostly liked what I read, I just didn’t have time to read seven, eight new posts a day and all of the comments. This one blog took close to 25% of my total time! There was no way I could follow his blog without significantly shortening the time I spent reading the one or fewer daily posts of other people I follow. There also was the question of getting around to writing for my blog when catching up with all posts and comments took a major part of my day.

Another cause for dropping a follow is “self-important blogger”. Believe me, pride DOES go before the fall! I even experienced it this past week, shared it with you as a way to straighten up my prideful self. I dropped a blog this morning because of it. His hubris, not mine. Oh yes, and he replaced the other fellow who posted so frequently and whose followers commented so much that I spent most of my time sorting through g-mails related to his blog, and little on anything by anyone else.

In this instance, it wasn’t enough of a cause to make me to unfollow the blog. There were more than one, including insulting people who “liked” one of his recent posts!

Sometimes “enough” means “too much”.

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