A 3-Step Guide to Legacy Modernization

In today's rapidly evolving technological landscape, clinging to outdated legacy systems can hinder your business agility. Modernizing these systems and migrating to a target platform offers numerous advantages, but the process itself can be complex.

In this experience sharing article - I have outlined a three-step approach to legacy system migration, ensuring a smooth transition and paving the way for a more efficient future.

Three Steps/Phases of Legacy Modernization

The figure below depicts the 3 phases of a successful legacy modernization. These phases are further elaborated in subsequent sections.

System Migration: This phase focuses on transforming your legacy system to the target platform. This is the most complex and time consuming phase. Typically, legacy systems have evolved over the years and includes large set of features, implements complex processes and integrates with many upstream/downstream systems. The figure below depicts what all needs to be considered in this phase.

It might not be possible for target system to achieve parity with the legacy system in one go, hence it is recommended to identify logically cohesive feature set that can make our system complete for certain use cases. Carefully identifying right feature set can help us reduce the time to deliever for business and they can experience the system early-on while system is still evolving. Below is one example of functional roadmap for Telecom Order Management system.

Please note that above figure only covers one dimension of Order Management System, there are other dimensions that you need to add e.g. Products/Services supported - to have a comprehensive view.

Data Migration: This phase involves transferring data from the legacy system to the target platform. Depending upon the level of transformation achieved with the target system, data migration could be "straight forward" to "very complex". In either case, it is all about data being carefully transformed & transferred from one system to another. There could be different category of data in the system - each of them may require different treatment.

Data migration phase has a dependency on the System Migration roadmap. If certain features are not yet modeled in the target system, you cannot migrate them (e.g. In a billing system, you might have certain payment system which is not yet supported by target system and in that case you can't migrate those customers). Hence, both System Migration and Data Migration activities go hand in hand. You have to identify right data set that is eligible for migration.

Similarly, when it comes to executing data migration there are some common approaches that are described in table below.

This is definitely not a comprehensive list, but in my experience I have seen all 4 approaches in different transformation programs.

One important element to keep in mind for Data Migration is the rollback and clean up planning. While all efforts are made to ensure successful migration of data, if there are certain data sets that could not be correctly migrated then each of these approaches might require different strategies for clean up of data.

User Migration: This phase involves transitioning users from the legacy system to the new platform. In my experience it is the most critical phase. Many of the migrations program fail because of the lack of user adoption and life of legacy systems are dragged because user migration is not completed. Secondly, in complex systems it is not possible to switch all the users to target system in one shot. Instead, in most of the complex systems, it is a controlled activity to identify user cohorts and phase wise migrate them to new system.

You can look at this phase as both driving the entire migration process or just following what is being delivered. Let me elaborate the last sentence, when I say "Driving the entire migration process", I mean, we can do the User base analysis, their usages pattern etc upfront and use that information to identify first cohort of users that must be brought to the target system. Use this information to drive your System Migration Roadmap and follow it up with Data migration plan. This way, every iteration will be delivering something tangible for uses to use and it will also increase the confidence of users.

Again, when we say Uses, there could be number of category of users that we need to look at and identify right set of access grants before the system is opened up.

Bringing it all together

Remember, while I have depicted these steps in sequential manner primarily from dependency perspective, practically, it is done in iterative manner. The success mantra is to start with the end in mind, identify the user cohorts, the activities they perform with the system, consider that as the starting point for the System migration planning.

Following this approach would greatly increase the chances of user adoption and drastically reduce time to value on the investments. Planning, close collaboration between teams, and a focus on data quality is equally critical for a seamless transition to new future.

By following this structured approach, you can achieve a successful legacy system migration that would eventually lead to the decommissioning of the legacy system.