Data mining is a critical, intermittent risk management activity safety managers need to perform in their aviation safety management systems (SMS) to organize, understand, and process collected safety data acquired during the organization's risk management processes.
Data mining techniques can be performed with a modest, home-grown aviation safety database and simple tools, or with complex software and professional, commercially available aviation safety databases.
Data mining goals are to establish:
Successful data mining activities in aviation SMS implementations allow you to:
In aviation SMS implementations, data mining is the responsibility of safety managers and supporting safety teams. However, since accountable executives are responsible for ensuring the aviation SMS is properly implemented and performing in all areas of the organization, the account executive will need to provide oversight into the data mining process.
Too often, accountable executives are not included before safety teams initiate their data mining activities. This unintentional failure affects the ability of the accountable executive to provide oversight for the system that is directly under their control. Every accountable executive must regularly review their organization's safety performance and whenever substandard safety performance is identified, the accountable executive is responsible for correcting the substandard safety performance.
In addition to providing oversight for the aviation SMS, accountable executives are familiar with organizational goals and objectives that may be affected by any insights offered by the aviation SMS' data mining activities. These two reasons should be enough to convince any safety team of the importance of including the accountable executive in the data mining processes. In short, the accountable executive is responsible for monitoring organizational safety performance and may provide insights that extend beyond the purview of safety managers.
To practice data mining, you obviously need to have some data to mine. This data may come from:
A great deal of data will be collected naturally as a result of documenting the SMS' risk management processes, assuming that your SMS implementation is actively collecting safety data in the operational environment.
Active is the "all word" for a risk management program. It simply means:
In every organization, several core activities drive the engine of every SMS implementation. These activities include:
Assuming these activities are happening frequently enough, you can begin to “make sense” of your data by exploring what you have documented. Which begs the question, what is important to document?
The word we are looking for is called “metadata,” which is information that describes the data and gives it context. For example, some important pieces of metadata that are needed to do sufficient data mining are:
Numerous data mining techniques can be used to fulfill the following goals in risk management programs:
These goals can be accomplished with several data mining methods:
There are numerous other methods for data mining, but usually the above methods will be used in most instances. These methods will allow you to establish patterns, trends, and hard-to-define relationships.
Data mining in aviation SMS implementations is incredibly important for several prime reasons:
Safety goals and objectives demonstrate safety performance monitoring activities within the aviation SMS, and data mining is how you evaluate whether those goals are being reached. If you have not yet identified your safety goals and objectives, this article should motivate you to consider the data mining processes necessary to acquire data to validate whether safety goals are being accomplished. These data mining processes include:
In addition to being able to develop and evaluate safety goals and objectives, data mining is also how you demonstrate the continuous improvement of the aviation SMS. Continuous improvement is the cycle of:
Development and implementation hinge on proper evaluation of safety performance. Data mining is almost undoubtedly the single most important determinant in how well you evaluate the aviation SMS' performance.
For decades, we have heard the saying: "Garbage in, garbage out." This saying highlights the importance of using quality datasets to arrive at fact-based and data-based assumptions. If your datasets are incomplete or hold incorrect records due to data entry errors, your assumptions may be incorrect.
If you are like many other aviation service providers, you may base your aviation SMS data management strategy on spreadsheets, email, and paper. Unfortunately, these are among the most difficult data types to mine for information. In the perfect world, every operator would have a robust aviation SMS database that:
A frustrating experience shared by most safety managers is when the accountable executive asks for safety performance reports and the safety manager does not know where to get the data necessary to generate the reports. This issue becomes more prominent when the data is not centrally located but resides on various users' computers or in ill-defined network drives.
To avoid common data mining woes, I recommend that your SMS data management strategy employs a low-cost, commercially available SMS database. Commercially available SMS databases have been designed to address specific SMS requirements across the entire SMS implementation.
To learn how your organization can benefit from a commercially available SMS database, watch these short demo videos.
Last updated in July 2024.