Taming the Data Beast: Data Migration Best Practices
It’s staggering to think about how in today’s world, data surrounds our every move. Recent studies report that there are 2.5 quintillion bytes of data created each day, and that pace is only accelerating.1 Global data volume doubles each year as information pours in from digital platforms, wireless sensors, and billions of mobile phones.2 Only a small percentage of this data is retained, but what we’re often left with is data that needs to be transformed, cleansed, and stored safely and securely.3
Historical legacy data represents a significant issue for group insurers and pension funds, and this is further complicated when these systems are transitioned to more modern platforms for faster and more efficient administration. Think about it: huge volumes of sensitive data, including insurance claims, contributions, retirement fund balances, medical information, etc., that needs to be cleansed and transformed before being migrated to an entirely new ecosystem, interacting with APIs and automation processes. A modern administration system comes alive with data, so it’s critical to have accurate, clean, reliable, and complete information from the start. A strategic approach for data migration, data cleansing, QA, and reconciliation, as well as the right team, can tame the data beast for a streamlined and seamless implementation.
Cleaning The Lion’s Den
To mitigate data conversion risks, it is imperative to profile legacy source data to identify data issues and assess the state of the data. Clients must have data retention rules and tax reporting needs top of mind before selecting the data to transfer. It’s particularly useful to have preliminary client conversations to determine what historical data should be retained to separate “nice to have” data from “must have” data. An insurance implementation typically requires far less historical data than a retirement implementation, but the expression “less is more,” really applies to both. Overall, decisions on historical data have a significant impact on the timeline, cost, and cleansing and testing processes.
The Importance of QA
As data and systems have become increasingly complex, it is key to incorporate migrated data early in the testing effort. Repeatable, automated, and focused QA processes confirm that migrated data is accurate, complete, and works as intended with the new system and interfaces. Reconciliation criteria and processes need to be established to confirm that all necessary data is accounted for and migrated.
The Power of the Pride
Like a pride of lions on the hunt, a cohesive and experienced team increases the chances of success. Whether the data migration is a multistep rollout or a one-time, “big-bang” operation, a dedicated and empowered team that understands and mitigates the risks when dealing with legacy data sources is invaluable to a successful data migration.
As insurance and pension organizations continue to prioritize core system upgrades, a carefully planned and orchestrated data conversion is essential. A detailed process, with a skilled team that possesses deep domain knowledge, can tame the data beast and turn the new system and its associated data into a strategic asset for clients and their constituents.
1 “How Much Data Do We Create Every Day? The Mind-Blowing Stats Everyone Should Read,” Bernard Marr, Forbes, May 2018
2 “The Age of Analytics: Competing in a Data-Driven World,” McKinsey Global Institute, December 2016
3 “Volume of Data/Information Created, Captured, Copied, and Consumed Worldwide from 2010 to 2020, with Forecasts from 2021 to 2025,” Statista, September 2022