7 Tips: Dealing with data migration in aviation
Many airlines get new aircraft to replace old ones, extend their fleet or buy a new MRO software system to replace their legacy system. In any of these scenarios the process of data migration is involved. You either have to phase-in data of a new aircraft into the existing airline systems, or to shift the entire maintenance systems from the legacy to the new MRO software.
As many of you know data migration is not a trivial task, it’s a complex procedure. Data needs to be retrieved from multiple sources, can have different standards and is prone to cleansing and standardization. Next to this, data quality is of vital importance to aircraft airworthiness and, as if it’s not enough, time pressure is mostly high. Thus, we would like to share some practical tips with you:
#1: Setting up a detailed project plan and processes beforehand
Before getting started with your data migration project, outline the complete project and processes in a detailed plan. This project plan should also include the names of people that are responsible for certain aspects of the project. These people should have the decision-making power to avoid unnecessary long discussions and to drive decision making when required. Even more important, stick to the developed plan if you want to stay on time and budget.
#2: Having dedicated key-users involved from the beginning
It is of utmost importance that your key-users are involved in the data migration project right from the start. They work with the data on a daily basis and understand the meaning and value of the data. Among the key-users should also be decision-makers in order to drive decision making when required.
#3: Establish good data standards/templates and a repeatable process
Data standardization and templates are the bases for the whole data migration. Once established you can use them for repeatable iterations. Having a suitable tool to perform repeatable iterations during data migration will save significant time and resources and will allow you to undergo multiple data iterations to reach acceptable levels of quality.
#4: Good overview of all data sources and being accessible during the whole project
In the beginning make an overview of all sources to avoid overseeing anything in a later stage and ensure that you can access all sources during the whole project.
#5: Make user acceptance tests in particular detail
Schedule user acceptance tests before go-live, so that you can see if the data is fit for go-live. The user acceptance test is a detailed test of the data and processes. Passed the user acceptance test successfully, your data and you are prepared for go-live and unnecessary surprises can be eliminated to a minimum.
#6: Focus per subject, don’t do different things simultaneously
Great if you have strong multitasking skills and can focus on different things simultaneously, but please do not apply this to data migration project. The key to success is to take everything step-by-step, one after another. For instance, start with the migration of all static data and then focus on the dynamic data on a per subject schedule. It’s like building a house, first you need the plans to build, then lay the foundation and then proceed with the walls, ceilings, rooftop and interior.
#7: Don’t stick to old processes, be open for new things and be prepared for surprises
Last but not least, be open for changes and new ideas. Just because you have always done it this way does not mean that it is the best way. Be prepared for surprises, as you will encounter things in your data that you thought were not possible.
Update May 2017
