Organizing data and information is extremely important in SMS, as much of your data analysis and performance monitoring depend on such an organization. One best practice to organize your data is assigning classifications to issues.
A classification is an organization tool. Classification is a word or a short phrase that describes the safety issue in some way. In other words, classifications categorize your issues. They can be categorized in different ways, such as:
When you are managing safety issues, you assign classifications to the issue to organize it. Over time, you can easily research data regarding specific categories.
For example, you could find out how many runway incursions were caused by a lack of communication by searching for issues with a “runway incursion” hazard classification and a “lack of communication” human factor classification.
Classifications are perhaps the best way to organize your data. Its goal is to find a way to organize data:
Case in point. We recently worked with an operator who attempted to adopt a classification system to organize data. We reviewed their data and tried to establish how many “Go around” they had so far this year.
In their existing program, they were trying to search through their issue titles for the term “go around.” What we quickly found though, is that different managers had used 4 (and possibly more) different terms for this idea, such as “fly-by”, “fly around”, and “go by.” And there may have actually been more with different terms, or spelling.
The result was that it was:
The purpose of classifications is to solve these kinds of problems, which are significant and very real in the aviation industry.
Some benefits of organizing safety data with classifications involve having classification trees that:
Good use of classifications provides the following benefits:
Classifications are fundamental to having the most reliable data possible. It is very difficult to have high-quality data analysis and data mining without them.
Organizing your safety data with only one classification provides some minor benefits for acquiring data. However, data that can be organized in multiple different ways provides a powerful ability to understand data very specifically.
Using classifications, you grant yourself the ability to organize data in different ways by assigning multiple types of classifications. For example, we highly suggest that for each issue, you categorize issues based on, at the very least:
When you classify each issue with different classifications, you can search for issues based on any of your classifications. You might, for example, search for “Lost time injuries” that happened because of “lack of communication” and “faulty equipment”. This is a bit of a facetious example, but it highlights how you can really drill into your data.
A very good practice for organizing your data is to create classification trees with three levels:
Classifications are organized this way, not so much for the benefit of retrieving data and performing data analysis, but for the benefit of proving classifications to issues:
One questions we often get asked is: how specific should classifications be? If you organize your data with classifications that are too specific, it will be very difficult for you to perform meaningful data analysis.
The point of organizing data is to clump data that is similar, not to describe your piece of data in intimate detail.
Describing data in detail is the job of issue titles and descriptions.
Here are some examples of good specificity for hazard classifications:
These examples are specific enough to capture the essential piece of information (“wildlife” and “runway”) but not so specific that you will need to assign a couple of classifications just to capture one idea.
The point is: one type of problem, one type of classification.
Oftentimes, when employees submit hazard reports, the title they use on their report is not ideal. The title gives you a meaningful opportunity to apply meaningful data keywords that will be useful for data mining.
For example, while:
Hence, at the end of the year you can search through issues for “goose” to get a good estimate of how many goose strikes you had. This is a good practice to do for all issues.
In smaller organizations with one or two managers responsible for managing issues, this practice is easy to manage. In larger organization, we highly recommend you have guidelines for how to rename issues, including a glossary for common terms to use for various types of issues.
An extremely important practice when you create classification trees and are classifying issues is DRY:
It is a very important term in many industries, as the goal is to ensure:
In the context of classifications, it means don’t include the same classifications in different classification trees. This would cause you to have extra classifications and have to classify the same issue twice.
Furthermore, you avoid confusion when people search for specific data, and see the same classification(s) in different locations.
Different types of classifications should be organized into their own classification trees. Some common types of classifications we see used by aviation service providers are:
You can literally create any type of classification tree you want that best fits your organization. The point is that different types of classifications are separated. As noted, each classification tree should have its own unique classifications, and should not repeat classifications from other trees.
As discussed, it is very useful to assign different types of classifications to an issue to organize it. Here are some loose guidelines that we suggest for how many of each type of classification to apply when classifying issues.
Remember, these are not hard rules, they are simply best practices – i.e. “soft rules”. Some issues will require you to be flexible.
Good classification practices will make a big difference in how easily and how well you can sort data.
Last updated August 2024.