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As the pandemic continues, companies are racing to transfer data from old, bloated IT systems to more nimble, modern setups in order to launch new online services and maintain operating systems remotely. But few of these large-scale initiatives proceed as planned or deliver promised results. Many multiyear IT data migration programs fail — often at a hefty cost.
Companies can reduce their chances of running into trouble by accepting that “less is more.” Below we share three principles companies can follow to successfully shift data into new systems in months instead of years, fueling faster innovation: tagging essential data that must be migrated; leaving behind “nice-to-have” data; and lowering data quality standards, even if it’s only by less than 1%.
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Start With a Minimum Set of Viable Data
When companies migrate data, they generally aim to move all of the foundational data structures in their legacy systems to the new IT system. But data migrations can happen much faster if businesses first select a new IT system and then work backward, with the goal of migrating only the minimum amount of viable legacy data required.
For example, one financial services company transferred the data for one of its products in four months instead of two years, after reexamining which data it truly needed moving forward. The old IT system collected thousands of columns of historical data that captured how the product’s value changed every time its fees or interest rate were adjusted. But the managers needed to migrate only the current value of the product and its transaction history. Every incremental fluctuation of its value over the past decade could be recalculated in the new system, if needed. As a result, managers shaved years off their data migration project by transforming only hundreds of columns of data, and leaving the rest.
Look For Data to Leave Behind
Because managers now have access to more accessible and affordable data storage options, they can now more easily and safely park legacy data in cold storage and source it from different systems later if needed. Data storage options mean that the traditional all-data approach — migrating all legacy system data in one operation with a single switchover date — is obsolete. The “big bang,” all-data strategy may seem to offer upfront advantages, such as shorter implementation times and lower front-end costs.