Data migrations can be a big undertaking for almost any organization. That’s why it’s so important that organizations set themselves up for long-term success. This means being able to ensure they’ll enable their desired outcomes—such as compliance, data accuracy, and performance—for the long haul.
How do you do this? It starts with understanding that data migration isn’t a purely technical topic, and it can’t be thought of as one. To make a data migration successful in the long term requires a combination of people, processes, and technology—and above all, it requires a mindset shift.
The Need for a New Mindset
A data migration is a transformational project—not just something to get through—and it needs to be treated like one. You’re bringing people together and committing major resources and time to this outcome, so it’s important to think bigger than just getting a system live.
Anyone who sees this as a technical exercise is missing the mark in terms of what a project of this magnitude can mean for your company. If you set aside the technical aspects of the project, the ability to unify a group around a common cause and solve a big problem will create good, strong relationships within a business. With any big project like this, if you view it through the lens of the impact it can have on your people and the relationships that you form, you take a big step forward in improving the way a project runs.
Operational change management is a big hurdle in these types of projects, and it’s one that too often gets ignored or deferred until it’s too late. That also needs to shift. Ultimately, this level of transformation must come from the top. You’re not going to be able to do this on your own as a senior manager.
How to Shift the Approach
To change how your organization approaches data migration, consider these four aspects:
- People versus technology: If you review these projects through the eyes of those involved, instead of just focusing on the technology you’re enabling, your results will be better, and you will improve adoption because people will rally around the change instead of feeling like it’s forced upon them.
- Asking the right questions: When you look at RFP responses, most people are focused on the features and capabilities of the software. They ask almost nothing about how to implement this for their company and what the risks would be. No one asks those questions, but that’s how you should be picking a partner in a software application—not “Can we do forms using your tool? Can we load data?” It’s important to really understand the how and not just the what.
- Defining the why: Define why you’re taking on this digital transformation project. It can’t be just because, “Leadership told us to.” Think about outcome. What will success look like when you’ve finished this project? Get as specific as you can: What are the benefits? Why are you doing this now instead of 2 years from now? What are the new things you want to take advantage of, or what are the problems with the old process that you want to fix? Translate those answers into things that people can hold you accountable for. You must have some sort of business proposition for the value you’re delivering. Once you’ve stated your outcomes, the next move is to protect the capacity to do those things. Milestones need to be part of the plan.
- Defining how you will achieve these goals, so you aren’t trying to lay the tracks while the train is moving: Create a strategy, then execute it. For example: We’ll translate the mappings into data standards in the catalog, and then the migration team will build the rule enforcements during testing phases. We’ll leave a build person staffed during the testing phase to add capacity for this.
Best Practices for Data Migration Success
When you’re executing, it’s all about sticking to your North Star. There will be scope creep, distractions, and escalation around things that aren’t actually part of your core focus. A core difference between companies that can do this successfully and can do it repeatedly versus companies that struggle with data migration/transformation programs is the ability to avoid distraction or derailment.
From a longer-term perspective, once you’ve set up and demonstrated your accountability and a track record of delivery, this can go a long way toward future success. Codifying this is key—essentially, being able to show there’s a mechanism for validating the budget you have. If you can’t tie these projects to the value you’re producing, you’ll be defunded; you need to show that your efforts provide value on a recurring basis.
Best practices include these points:
- Understanding the key stakeholders for undertaking a project: In particular, know who’s going to approve or deny your budget. But there will be other stakeholders, whether in the area where you’re trying to have an impact or just a loud voice in the room. You need to know whom to keep happy so that everything goes smoothly.
- Establishing clear and meaningful KPIs: What are the areas of focus? How will you measure success?
- Knowing what your minimum viable product (MVP) is: Define how that will change over time and how the solution will build on itself. Doing some road mapping will help you focus on what the MVP will be. Having clarity about your MVP enables you to say no to additional requests, which sets you up for success.
Prepare for the Long Haul
Data migration isn’t a purely technical topic, and thinking of it that way starts your project off on the wrong foot. How do you ensure that after a migration, you can enable your desired outcomes for the long haul? You need to combine people, processes, and technology to create a solution that’s customized for your organization’s unique needs. Use the four steps noted above to change how your organization conducts its migration, and be sure to follow best practices as well. These will set you up for success in the long term.