Four common mistakes of data migration

Don’t make these data migration mistakes

What happens when data migration goes wrong? We’ve recently seen some very large-scale failures that should act as a warning for any company planning to move data. Only last year TSB customers were locked out of their accounts due to the unsuccessful migration of customer data. The ramifications are still being felt. The business witnessed increased pressure on staff, negative social media comments, management changes as well as further IT problems. As well as giving thousands of customers a very poor experience.

It would be great to say that the case of TSB is a one off, but that’s not our experience. With new technologies pushing more businesses than ever to move data from one platform to another, the risk of error is increasing. 63% of data migration projects we have been engaged in over the past five years have all been due to a failed implementation. This is compared to only 27% of projects where we have been involved in the initial planning process. This suggests that roughly three out of four companies fail due to poor planning. Don’t let your company be one of them!

With this in mind, how can you ensure that your data is migrated successfully? We have identified four common data migration mistakes to avoid:

1. Letting the software company (SI) manage the entire process

You may think that your software integrator is the right team to be moving your data. It is a common misconception. However, we know, from picking up the pieces, that SIs are not best placed to handle data migrations. All but one of the projects we have been brought in to fix used an SI to handle the process. It’s important to remember that even though they are platform experts, their data migration skills may not be finely tuned. An SI will often throw data at the new system and deal with the fallout later, treating everything that does not load as an exception. This approach is doomed to fail.

2. Inadequate project scoping

In our experience, poor project scoping is one of the most common reasons why data migration projects fail. If you don’t think through your data requirements properly or go into enough detail when you are planning, your project needs might be misinterpreted. It’s critical to get your facts straight right from the outset and ensure that an initial analysis is conducted.

3. Setting unrealistic expectations

Data migration is time consuming and can often take the same amount of time as it does to develop the platform – there is no quick fix and anyone who says otherwise clearly does not know what migration involves. Set realistic expectations with project sponsors and the board to ensure you have enough time to implement changes. Yes, the timescale will be a lot longer but ultimately it will be far shorter than the time spent repairing a failed project.

4. Failure to overcome resistance

When people are confronted with change, there are certainly going to be those who resist. If resistors are not tackled swiftly, the likelihood is that there will be flaws in your data migration project and this will reduce its effectiveness. For example, one of our projects had been brought in because the SI had allowed their client to dictate that their new platform should follow old processes. This compromised the data model and led to the patching of data and processes.

For data migration to be successfully implemented it’s clear that the planning process needs to be handled in the correct way, otherwise, businesses may experience the same consequences as TSB. For more information, read our whitepaper on Data Migration and Modern Data Warehouses.