Data quality, a vague term, that commonly is quantified by the amount of data that is missing or where there are data consistency issues, another of those vague terms. In plain language, the consensus is to focus on visible errors, like the previous word, issues that are easily identifiable. However, this is only the tip of the metaphorical iceberg.
In our opinion data quality is not purely an exact science. There is no predefined standard by EASA, FAA or any other aviation authority. This means there is no predefined threshold for the amount and type of issues a data set can have before data quality might rise a concern.
There are mere guidelines and fluctuate from airline to airline, from project to project and it depends very much on an airline’s processes.
How to identify signs for ‘poor’ data quality
One of the immediate signs of ‘poor’ data quality or inconsistent data is when you are talking to the people that work with the system day by day, ask them to show how they do their job. Often these kinds of talks end up in alternative work methods, where you are introduced to excel sheets or references to another system to double check if the main system is correct. This is the initial sign that something is not as it should be, as apparently, they do not trust the system and this suspicion must have come from somewhere.
There are always multiple reasons for ‘poor’ data quality, however, these are the top 3:
- During an introduction of the system the data was never cleaned properly, implicating problems from the beginning as the source was never correct as well. Or after using a system for quite some years regular data checks do not take place.
- Employees are aware that procedures are not followed properly in the chain, many ‘dirty work’ arounds have been applied in the course of history of the system making it unreliable or, at best, giving slight concerns to the user base.
- Multiple systems are used in parallel which will have, for sure, synchronisation issues at some point in time and creating doubt among the company which system should be used and, more importantly, which system is correct.
Some of these problems look seemingly innocent and things are often put away as insignificant compared to the sheer size of modern datasets. But be aware, down the line, small issues can and will have exponential impact as the dataset grows, eventually leading to things such as full inventory audits to verify your stock and the value it represents, doing labour intensive dirty fingerprint checks because of high doubts of the system status. Or, in the worst-case scenario, keeping an aircraft AOG as there might be discovered that critical items are overdue making the aircraft instantly non-airworthy, potentially shortening its economic life. We’ve seen real-life materialization of all these examples during our work in the field.
We would like to invite you to ask yourself the following questions:
1. How long ago was the implementation of your current MRO software?
a) Less than 5 years ago
b) More than 5 years ago
2. Do you conduct regular data scans/checks, at least once a year?
3. How often do you find yourself double checking something from your own system?
b) Quite often
4. Do you avoid double entries of data?
5. Are people doing multiple things in the system outside of their original scope/function
6. How many component serial number readouts per aircraft per year do you have due to doubts in the system?
a) Less than 10
b) More than 10
If you have mainly chosen answer a, then you are on the right track. Keep on the good work! With this level of data quality, you might want to start looking into enabling more value from your aircraft data set by looking into advanced analytics and predictive analytics.
If you mainly have chosen answer b, it might be time to start addressing some of the core issues. Of course, you still operate within allowable boundaries of airworthiness management, however as your aircraft data will further grow so will the potential risks of impact of this aircraft data quality on critical airworthiness items.
Let’s take a simple example
You operate an airline with 50 aircraft and use your MRO software system for let’s say 5 years. This results in the fact that on average of 150MB of pure data (outside of document scans and certificates) is added to your system every day.
Well 150MB per day, so in one year 5.4 GB is added and as you are using the system for 5 years in total 27 GB has been added. Now consider how much of this information is created by means of automated inputs such as interfaces and how much is generated by manual user data entry. Likely the fast majority will be created by manual user data entry. Think of aircraft defects, maintenance work packages, material orders, incoming inspections, vendor details, parts definition data and so on.
Are you currently running a data migration project?
Many companies tend to run their old system in parallel for months after introducing a new system as a back-up or, because they are not feeling sure enough about it. This is a risky set-up and should never been done. If you are not sure you are ready, then don’t turn the new system on and do more testing, verifications and cleansing until you reach a high confidence level. If you feel you are ready, flip the switch immediately and degrade the legacy system, block all user access and force everybody to work in your state-of-the art new system.
Relevance of data quality
So, what is the real tangible relevance of data quality for aircraft airworthiness and maintenance & engineering? Basically, one can see these in 3 distinct area’s
- Airworthiness compliance
- Efficiency gains in business processes
- Financial impact
1. Data is airworthiness compliance
Everyone is aware that if data is not correctly entered into the system there can be huge safety implications, these mainly revolve around issues with rotables (missing parts, discrepancies in paperwork versus actually installed, requirements due), modifications status and any other controlled event that is overdue. Whenever we are talking about data, one thing that we need to understand is that first we’re talking about airworthiness compliance. Data indicates for an airline whether or not particular aircraft are airworthy. That is always the first and most important key consideration when talking about data… airworthiness compliance. As we all say in aviation, safety is paramount, and data quality and consistency are directly related to it.
2. Efficiency gains in business processes
Good data quality can mean huge efficiency gains and be a money safer too. A reliable clean system prevents double work from employees, avoids costly “rescue” operations, keeps your financial books tidy and creates room for further automation and innovation. In general, there are a lot of possibilities for example on the data analytical side: prognostics, monitoring certain things that have operational benefits. However, that is only possible if there is data available, accessible and obviously again on a appropriate level of quality.
3. Financial impacts
A reliable clean system prevents double work from employees, avoids costly “rescue” operations, keeps your financial books tidy and creates room for further automation and innovation. So good data quality is a money safer too.
Let’s have a look at an example of a lease hand-back:
When returning an aircraft to the lease company one of the first things the lease company will do is a records verification to check the records that accompany the aircraft including checking data in order to make sure that it is correct. They do that to confirm whether the aircraft is in compliance with airworthiness regulations as well as the lease agreement, which in turn has a direct effect on the value of that asset. No-one would buy an aircraft whose airworthiness is in doubt. So, there is a direct relationship between data, airworthiness compliance and asset value.
What you can do right now
Although issues and abnormal situations are inherent to human work, there are numerous safety nets that can be put into place to minimize the risks and severity of data corruption, a quick overview:
#1: Data Health Checks
Periodically checking your data health in an MRO system helps to identify problems areas that might require further structural attention. A data health check is best compared to a quality audit as performed routinely by your quality management department. Defining corrective actions and preventive actions for issues identified allow you to tackle the problem at hand as well as put measures in place that the detected data issues keep repeated themselves.
#2: Automatic data quality controls
Implementing controls that monitor the quality of your system data is an effective means to continuously track the current state as well as identify problem areas. An easy implementable form of such controls includes reports from your MRO software system on for instance:
- Aircraft components with a missing installation date
- Serialized components showing both on stock as well as installed on aircraft
- Mismatch in TAH/TAC sequence of aircraft between flights
- Material warehouse receiving’s without accompanying Materials order
#3: Create Awareness
Do not only enforce policies and processes, but also make your airline in general and your colleagues more aware of the importance of data quality. It needs to be part of your airline’s culture and starts with including this topic with some simple tips in any documentation.
#4: Tackle problems immediately
As soon as problems are spotted, do not try to work around, verify and adjust immediately where necessary. This should be encouraged throughout all layers of the company, again training will show employees how important this is. Without proper training there is no understanding.
#5: Competence Centre
Have a competence centre within your airline who will govern and control all facets of your different systems especially your MRO software. This competence centre should NOT only consist of IT people, but experienced system users from all disciplines of the organization. A good competence centre will warrant the data quality and reliability, but at the same time drive continuous improvement and innovation to make full use of its capabilities.
To put in a nutshell
Data and its quality are the backbone of a modern airlines. However, remember that it is (still) people that create the data and mistakes can be made. It requires uninterrupted attention and your data will require continuous maintenance, such as an aircraft, to keep it on a high quality and safe operating level. A sophisticated and well controlled dataset can truly push your airline to the next level, setting you ahead of the competition.
How EXSYN can help
EXSYN's team of aircraft data and aviation experts utilize a proven framework and methodology for data health checks in aviation and includes:
- Workshop on current processes and systems to develop the best strategy for your situation
- Conduct a data mapping workshop and fit -gap analysis to define current data consistency
- Delivery of a recommendation report about current data consistency status and areas to improve including a guide where to start
- EXSYN can support you in the implementation of the recommendations
Schedule a free information session for more details: