To help you with your projects, I've compiled 17 Top Tips on Data Migration and practical steps for you to think about.
With any data migration project you will need to consider activities before and after a migration, these tips will cover those stages too.
By including these steps you will experience a smoother transition that will lead to a successful migration outcome.
We've also created an infographic to give you a summary overview of the 17 top tips.
1) Senior Management Buy-In
It’s vital to have a buy-in strategy for Senior Management as data migrations are critical projects. In addition to acquiring initial funding, it’s important to provide regular updates to senior management. Use charts and statistics to measure your success.
2) Consult End Users
This is an absolute must. Have a way to engage every set of users for your new application. Users have vital information about business processes and how they would like to see them improved. Engage users at the start of the process, prior to training and hand-hold during the first weeks of go-live.
3) Measure Before Migration
The only way to know your data is right is to take a baseline measurement prior to any data cleansing work. Use Acuate’s Seven Dimensions of Data Quality to work out where to focus your efforts for data cleansing.
4) Decide What’s Old Data
Databases require a good cleanse. It’s time to archive contacts/accounts that are no longer useful. For example, contacts that are no longer at their company, accounts that have no activity for the last few years, deceased contacts, invalid email addresses, and so on. Holding onto old data only skews management reports and providing you inaccurate statistics.
There is always data absent from your database. Take this opportunity to add fresh data and fill-in missing information like email addresses, job titles, telephone numbers, etc. Having richer data after go-live will raise confidence and improve overall results.
6) Which Data is Important to Which Department?
Most systems have multiple stakeholders who care only about aspects of the data relating to them. Engaging each department will determine which data is important, why it’s important and how it should be migrated.
Not having a single customer view is inefficient for your business. Here are some of the benefits: better marketing returns, better sales management, accurate reporting, enables segmentation and lowers costs through a single platform.
8) Standardise Data
Place all of your data in the right place and make sure all of it looks the same. Standardisation helps the data cleansing phase and to identify duplicates accurately.
9) Data Cleansing
Once your data is standardised, it’s time to cleanse your data. Validate addresses, check email IDs, identify non-current data, and so on. Clean data will enhance the reputation of your new application as users feel confident about using good data.
10) Verify Your Data is Current
Data decays naturally, so it’s very likely there are contacts and accounts that are no longer active today. Determine through a call validation project the percentage of your data that is inactive. Then remove inactive data and where possible replace with new current data.
11) Removing Duplicates
All databases have duplicates and CRM applications aren’t good at finding true duplicates and merging data. Specialist software is required for this. Use Acuate’s latest De-Duplication software to find real duplicates, identify master records and merge them.
12) Create Training Guides
Users will require training guides about how to enter data into the new system. Never assume its easy, as poor data entry contributes to the overall data decay for any system. Use these guides prior to go-live but also include them into your induction process for new employees.
If you take a baseline measure of the data quality prior to the data cleansing exercise, then take a measure post-go-live using the same criteria. This will give before and after statistics of the improvements you have made. In nearly all cases, the percentage improvements in data are significant; giving you a platform to present results to senior management.
14) Data Life Cycle Diagram
Create data flow diagrams illustrating how data moves through the system. Where the data is entered, which departments use the data, how the data changes, etc. This will help users to understand and empathise with how other users rely of their data.
15) Data Entry Reports Per Person
Entering poor data is the second biggest cause of poor data (first is natural data decay). Teaching users to enter data better is a must, but even better is to show users how well they have entered data. This creates accountability and long-term improvements in data entry will occur.
16) Data Quality Dashboard
Management require diagrams/graphs/numbers, etc. Create a dashboard to show how data quality is improving; it gives confidence to everyone that the business is pro-active around data.
17) Promote Data Quality to Stakeholders
There will be users and managers who are very important to your new application being successful and for its continued success. It’s vital the data quality dashboards and data entry reports are provided to them. They will be the guardians of the application and champions of your data.