Explore the pitfalls of lift and shift data migrations and learn how prioritizing data quality can drive better business outcomes.

When planning for data migrations, data stewards have numerous options on how to get things moving. Out of all of them, the lift and shift approach can seem like the easiest, most obvious option for a trouble-free experience. It’s a fast way to move your data into a new cloud environment. It requires less effort and no architectural changes.

It also doesn’t solve the core issues that made you consider data migration in the first place—and could even make them worse.

The dark side of lift and shift

When cloud infrastructure was first coming into its own, lift and shift was the easiest way for many organizations to begin their digital transformation journey. Existing data and applications would be migrated from on-premise architecture to cloud hosting, without any changes made.

Today, the disadvantages of lift and shift have become more apparent. The main problem with this approach is that it treats your enterprise data as a single movable object, rather than a collection where every item has its own strategic value. Enterprise datasets have only grown more diverse and complex with time. And with that comes greater potential for data quality to go overlooked.

When data quality fails

Migrating data wholesale solves none of the problems associated with poor data quality. Even the most advanced systems can be hobbled by errors, silos, and inaccuracies inherited from uncleaned, unstructured data. The results can be disastrous:

• Poor decisions informed by faulty data
• AI biases and poor output due to discrepancies in training data
• Delays and difficulties in accessing key business intelligence
• Data governance and security issues when sensitive data is indistinguishable from clutter
• Wasted costs and delays while addressing issues partway through a migration
• Data migration failure

In 2022, 61% of SAP customers in the UK reported that data management issues are slowing down impending moves to S/4HANA. Data is the foundation of all we do; it cannot be taken for granted. Your organization’s real focus should be on improvement, not just movement. Prioritizing your data is key for better business outcomes, customer satisfaction, and future growth.

Four reasons to go Data First

At Syniti, we take a Data First approach that prioritizes your enterprise data for better business outcomes. This means doing more than just shifting your data; we transform, clean, and curate even before the first test loads.

Here are just four reasons why leading enterprises choose to go Data First:

Data is refined, not just relocated

Cleaning and refining your existing data goes beyond lift-and-shift to deliver true transformative benefits. The Data First approach transforms enterprise data from an upload-ready object to a business-ready asset.

High-quality, accessible data lays the solid foundation required to launch high-power initiatives with long-term business benefits. Focusing on data quality unlocks the maximum value from your volumes of data—and the technological investments that depend on them to drive progress.

Support for high-value data and business initiatives

A Data First approach builds a solid foundation for future success and cross-functional cooperation. High-quality data provides a clearer picture of historical trends and patterns. The insights derived from this data foster better business results, which can be fed back into data and used to refine future initiatives.

This positive feedback loop benefits all enterprise functions. Improving data quality leads to more actionable insights, keen strategy, and intelligent decisions. When all your teams are working off a foundation of strong, easily accessible data, your enterprise can foster continuous improvement and make meaningful progress toward key business goals.

Simplified SAP landscapes

The December 2027 deadline to migrate to SAP S/4HANA looms ever closer for enterprises on older SAP systems. For those that haven’t already begun their migration, the best time to get started is today.

Streamlining enterprise data and prioritizing its quality, even before the first test upload, reduces operational and infrastructure costs for on-time, on-budget delivery with zero disruptions to your day-to-day business.

Reduce operational setbacks

Putting data quality first ensures that your new systems don’t inherit old problems—and things flow that much more easily. No more having to uncover and fix errors as you go. No more wasting time and resources under pressure. No more delays in getting the exact data you need. Just getting things right the first time, every time.

Conclusion

Lift and shift treats enterprise data as a movable object—nothing more and nothing less. Unlocking the value of your enterprise is key for sustained success, now and in the future.

Syniti helps leading businesses lead with world-class data management, migration, and governance solutions. Learn more about how we can accelerate your digital transformation with a Data First approach.