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GC-MS Automation – The Pareto Principle

“80% of people know about the Pareto Principle, only 20% ever apply it.”

The Pareto Principle (or 80:20 rule) is a rule-of-thumb that reminds us that lots of things are unevenly distributed and it is very common that roughly 80% of an effect comes from approximately 20% of the causes.

This is true in life, in business and in the analytical laboratory.

For example:

  • 80% of errors come from 20% of possible causes.
  • 20% of samples require 80% of the work.
  • 80% of total costs are associated with 20% of the samples run.
  • 80% of the benefit your lab delivers is derived from 20% of the work it does.
  • 20% of the results you generate carry 80% of the significance.

The Pareto Principle is a valuable tool that enables you to evaluate your labs work and to highlight those areas where the biggest improvements can be made with the best use of time and resources available.

As you would expect, the Internet has plenty of advice on the topic.  This article covers 80% of what you need to know.

So what has all of this to do with GC-MS automation?

When automating sample preparation for GC-MS, the Pareto Principle pops-up everywhere meaning that automation has the capability to solve many different types of problem and is easy to justify:

  • It can reduce costs – sample preparation often represents 80% of the cost of the analysis.
  • It can improve data quality – often, 80% of mistakes are due to human error.
  • It can increase the number of samples you can run – often, manual sample preparation takes 80% of your staff time.

Take a few minutes to reflect on the relevance to the 80:20 rule to your current priorities and look for the big wins that automated sample preparation can deliver.

If you have an idea that involves automating sample preparation, then contact us and we can quickly help you assess its feasibility.

The few minutes this takes will be part of the 20% of your time that delivers 80% of your labs improvements!

Call us on +44 (0)1223 279210 or email:


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