In a previous article “Migration strategy and the path to operational resilience”, we examined the relationship between data migration and regulatory compliance, and the importance for enterprises to create a clear plan for initiating a data migration. Today, we will look at how migration is never one size fits all, and how each company’s migration journey will be different, requiring strategic approaches linked to the complexity of the unique data.

 

There are several key steps to ensure migration initiatives are as streamlined as possible.

  • Understand the project scope: Assessing the quality of data, requirements, and complexity of data will help you set the right migration strategy.
  • Set realistic timelines: The assessment phase will help create an achievable migration plan that includes an ability to clearly measure progress.
  • Define the migration rules with the experts: Allow the migration expert to come out with the migration order and the rules for you to confirm.
  • Validate the migration: Set the testing strategy during the assessment phase. Conduct preliminary testing during the building phase and confirm with the 
    business that all use cases were considered when preparing the test scripts.
  • The final migration strategy: The migration strategy dictates how the migration will be performed, on a one time basis or incrementally, and how to shut down and dispose of old legacy systems.
  • Sanity checks in production: Once the migration is complete, a sanity check on the agreeable amount of migration data should be initiated to prove that the migration is performed in accordance with the validation phase.

Define the scope of the project

Scoping a migration project involves defining the parameters, requirements, and goals of the project, and developing a clear plan and timeline for the migration. It’s also important to define the limits of the project and identify what won’t be included in the current phase.

For example, in the pharma industry, the implementation of the IDMP (Identification of Medicinal Products) standards requires updates, changes, and possibly even the roll-out of a new information system, but this type of agile modus operandi doesn’t always align with the pharma industry’s historically siloed way of working. Nearly every team in the drug development lifecycle – safety, clinical, regulatory, and research and development – can use different, disconnected systems that might not even integrate (e.g. Submission management, RIM, Master data management, Pharmacovigilance, Document management system etc.). Additionally, they are encouraged by the IDMP implementation to apply a single unified, holistic platform that removes silos connecting data and people.

When a decision on the implementation of a new solution and migration is made, it is important to set a clear scope and goal for the whole project. In the context of the implementation of regulatory solutions in the pharma industry, this can be a big deal for the company and the comprehensive assessment of the project is of paramount importance.

Getting started: Plan a data assessment

Before commencing, it is critical to have a clear overview of the project scope, data, and information to ensure efficient planning and execution. Data migration projects in the life science space are often complex, time-consuming and in most cases involve multiple systems and different technology. A clear and comprehensive assessment phase is key to avoiding exceeding predetermined budgets, implementation delays or undercutting business processes. The assessment phase is primarily used to review and assess the data in the existing systems and identify any potential issues and risks that might occur during the project. The purpose of this phase is not to carry out any migration activities, but to benchmark the scope, set recommendations, strategy and ensure visibility for the client. At this juncture, the client should have already known the migration requirements and the expectations for the migration. As a result of the assessment, a decision can be made to go further with the major project after the plan is clear or whether a POC (Proof of Concept) should be performed to assess some more complex data of the migration (e.g. Migration of the drug registration history).

Choosing the right migration approach

Once a thorough data assessment has been carried out, the next step is to decide on the right migration approach. Every company’s data is unique, and the appropriate migration strategy will depend entirely on the quality, value, and complexity of the data. For example, sensitive regulatory data should be handled with particular care. Moving ahead without proper planning will ultimately cause more work in a later phase, and possibly undermine a project’s success. We often recommend businesses to migrate registrations of important products separately and the rest after the go-live, using the same migration rules. This decision can be made if a high volume of data should be enriched, and the business cannot provide them on time. Another important consideration is whether to migrate everything at once – a Big Bang migration – which requires considerable time and resources to complete. Alternatively, businesses can carry out the migration incrementally and transfer data in phases – this is a rolling migration. A big bang can be more straightforward, but a problem with this approach is that no additions or changes can happen during this time, as all data processes are paused during the migration process. An incremental approach doesn’t require as much downtime but can bring more complexity as the source and the target system are run in parallel, eliminating downtime.

 Aligning project & migration timelines

Knowing when to initiate the migration is pivotal. Ideally, the migration should take place in parallel with the solution implementation process, and the development of the migration rules should follow the implementation cycles. For example, when the solution implementation of master data is locked, the definition and development of the migration master data can start and eventually be migrated. After each cycle, the business should confirm the migrated data in the target system and if all the requirements were fulfilled. This approach tells us that we need to understand the whole concept of the project, including the implementation of the solution when building the plan. Otherwise, it is impossible to set all cycles in a logical order and set the right priorities. It is essential that the data migration is carried out in tandem with domain experts that have the technological know-how and strategic acumen to deliver.

Consider a Proof of Concept data migration

Rigorous planning and assessment are critical to the success of any data migration project, and in some instances, a proof of concept (POC) is highly advisable. A POC data migration is essentially a trial run of a larger data migration project, geared towards testing the feasibility of migrating data from one system to another. The purpose of the POC is to demonstrate the viability of the data migration project and to identify any potential issues or challenges that may arise during the actual migration process. When a company is approaching a large-scale data migration, or a high-risk migration involving sensitive or mission-critical business data, a POC can provide significant value.

For a successful POC, it is important that the business provides rich sample data so that the migration team can test and verify the exact processes that will be used in the full migration.  Before running the POC, businesses should:

  • Review sample data sets and consider all use cases
  • Confirm the result of the migration fulfills the requirements
  • Examine and define any gaps and how to fill them
  • Define what work is required if they need to enrich their data

By its very nature, migrating data can be a complex and protracted process, and if not thought out fully in advance, can lead to significant data loss and system downtime. In our next blog, we will highlight the key success factors and best practices for optimized migration.

Contact us to start your migration right

Whatever the reason for the data migration, the goal of all stakeholders is to provide a solution to the business in order to improve business performance and ensure competitive advantage. To achieve this, they should give more attention to data migration and be smarter in the assessment, planning, and migrating data with experts that have experience and knows the business in the life science industry.

fme has been guiding global pharmaceutical and manufacturing firms through their complex migration journeys for over 20 years. We’ve even developed our own proprietary tool migration-center to enable seamless migrations with minimal downtime. Contact us to discuss your challenges and start your journey on the right path.


Are you interested in future blog posts from the life sciences area? - Please follow us on our social media accounts.

LinkedIn     facebook     twitter

 

Tags: Content Migration, Life Sciences