Packing for a move into a new home always takes more effort than expected. Decluttering and downsizing are time-consuming, emotional processes. Everything slows down as you decide whether you can bear to part with old clothes and tchotchkes.
Similar emotions arise when preparing to move data into a new system. You must make hard but realistic decisions: Will you actually use this data, or is it just sentimental clutter?
In the first post of this two-part series on preparing for data migration, we described problems that arise when you don’t have time to review and clean up data before moving it into a new system:
- Unexpected costs
- Delayed timelines
- Staff burnout
- Poor system adoption
- Lost opportunities
The first step of data migration is deciding what data you’re moving—we covered that in our last post. In this post, we’ll look at the next three data preparation steps.
Step Two: Create Your Data Migration Plan
A data migration plan is your moving checklist. It prepares you and your team for moving essential data out of old systems and into the new one.
Who’s responsible for data migration?
Long before moving day, data migration starts with data stewardship.
Every department that manages data—membership, events, marketing, IT, finance, and others—appoints one person to represent them on a data governance team. The people on this team are the association’s data stewards. They create and enforce policies and best practices to keep data updated and clean. They ensure your association stays in compliance with privacy regulations.
The team meets monthly to identify and review data integrity reports and issues. Granted, everyone is busy, and data issues never seem that urgent, but don’t give in to temptation and cancel a meeting “just this one time.” Data quickly becomes compromised and unwieldy if it doesn’t receive regular attention.
Which data are you moving and where is it?
Once established, the data governance team learns the location and state of data in official systems and shadow systems, such as Excel files, Airtables, and Smartsheets.
This need-to-know is critical because data leads to insights. Data tracked in one department might be valuable to people in other departments. For example, Joe’s abstract collection platform contains information about paper topics and the people who submitted them. His colleagues could uncover emerging trends and member engagement activity in this data, but only if they’re aware of it.
The team knows about Joe’s “official” system. But why would Jennifer tell the team about her secret Smartsheet? Because when you find out why she resorted to using Smartsheet instead of the IT-approved system, you:
- Fix the offending bug in the official system.
- Improve the process she’s working around.
- Give her access to existing software she doesn’t know about.
- Involve her in the selection process for new software.
In short, you make her job easier. In the meantime, decide what to do with her shadow data. Either include it in your migration plan or connect it to a unique number used in the database so you have an option for putting it in later.
How are you labeling data?
Unpacking chaos awaits if you and your spouse call two different rooms in the new house “the den.” Similar confusion occurs if staff use different definitions for data, for example:
- What qualifies someone as an “active member”?
- Is “lapsed” the same as “inactive,” or are they distinct statuses?
Review and document definitions and historical codes to ensure everyone knows and agrees on their meaning.
When do you start preparing for data migration?
Right now. It’s easier to clean 20 records a week over a year than 10,000 records in a month. Build data cleanup into regular workflows instead of treating it as a one-time project.
The more you kick the can down the road, the more time you’ll spend going through, organizing, and cleaning out junk at the last minute.
Step Three: Clean Before You Pack
“OMG, are these dirty dishes?” Yes, while helping a friend unpack, I witnessed this—and the consequent shouting. Good data hygiene habits ensure you only migrate clean data to your new software.
Keep an eye out for these common data hygiene pitfalls.
- Inconsistent formats: phone numbers in different styles or names in all caps
- Legacy codes with unclear meanings: “Status = G” but no one remembers what “G” stands for
- Critical information buried in ‘Notes’ fields instead of structured data fields
Take advantage of tools and practices that help prevent these issues.
- Data audit reports to highlight incomplete or inconsistent entries
- Validation techniques to ensure data meets quality standards before migration
- Built-in deduping capabilities of your system or third-party deduplication software to identify and merge duplicate records
- NCOA database to standardize American addresses
To speed things up, hire an external partner to help with data analysis and cleanup or provide a cleanup plan. Make sure someone on staff is available to help contractors make decisions.
While going through the cleanup process, document data standards and procedures for the future.
Step Four: Downsize Before Moving
It’s hard to feel at home in a new apartment if you’re constantly bumping into boxes of stuff you moved with you. If only you had organized and cleaned that junk out before packing.
The emotional side of letting go
Teams often cling to data “just in case.” This mindset is driven by fear rather than strategy.
Data is only valuable if it’s actionable. When reviewing data before migration, ask these colleagues:
- What are you going to use this data for?
- When will you use it?
- Will it still be accurate and relevant then?
If a colleague believes they might need a data set later, use a less costly method to store it. Talk to your implementation partner about archive files as an option for “nice-to-have” data.
The cost-benefit analysis for sentimental data
Data storage isn’t free, especially for large datasets in cloud systems. One association we know paid thousands to migrate outdated data, only to delete it months later when their storage costs piled up.
Would you pay movers to haul a broken chair across the country? Apply the same logic to data: leave it behind if it doesn’t serve a purpose.
Make Data Stewardship an Ongoing Practice
Data management isn’t something you do once—it’s a continuous process overseen by your data governance team. Small, consistent actions (like regular data cleanups) are more effective than last-minute scrambles. Think of data stewardship as a practice, not a project.
Build regular data audits into your operations, just like financial audits. Occasionally, dig through your data closets and drawers. Organize and get rid of things so you won’t have a mess to deal with the next time you move.
Don’t collect data you can’t maintain. Otherwise, you’re creating another messy attic full of dirty and out-of-date data.
Embed these simple routines into your team’s workflow.
- Monthly cross-departmental data governance meetings with data health check-ins
- User-friendly member portals that encourage members to update their own information
- Continually updated and accessible documentation that explains data management policies and procedures (how it’s supposed to be done) and definitions of terms and fields
Empower your team by training them on data best practices. Celebrate data wins, like reducing duplicates or improving member engagement stats.
Ready to Move?
Our Fíonta consultants have helped many associations establish good data habits. Contact us to find out how we can help you with a smoother, more cost-effective, and less stressful data migration. Your new system deserves clean data. Let’s help you move the right way.