4 M&A Data Migration Best Practices You Should Know
This is part of Solutions Review’s Premium Content Series, a collection of reviews written by industry experts in maturing software categories. In this submission, Appfire Product Management AVP Paul Lechner offers some key M&A data migration best practices to consider.
The tech industry has seen some of the biggest mergers and acquisitions in recent history this year, including Amazon’s acquisition of iRobot for $1.7 billion in August.
Despite economic uncertainties, growth remains a top priority for many tech companies. This has drawn attention to mergers and acquisitions, which organizations execute to gain greater market share, reduce operational costs, or even create new offerings. However, mergers and acquisitions require organizations with different processes, business rules and applications to come together, which often creates new challenges.
One challenge in particular is data migration, because organizations have unique ways to measure, use, and store their data. A failed data migration can lead to headaches for employees and operational and financial setbacks for businesses. Mergers and acquisitions don’t seem to be slowing down anytime soon, so it’s critical that companies approach data migration cautiously and proactively.
Costs of an unsuccessful data migration
Technically, a successful merger or acquisition is no small feat. In addition to unifying business processes and applications, IT teams must integrate huge volumes of critical data from every business into a single repository.
The data migration process is complex: CIOs and their teams must find ways to merge incompatible data formats and resolve disparities between organizations’ data governance frameworks. They must create plans to deal with poor quality and incomplete data and transfer sophisticated data structures to new systems.
Even though data migration is a big undertaking, CIOs and IT teams often execute the initiative without proper planning and testing. Some of the most common data migration errors include:
- Lack of expertise
- Bad scope and budgeting
- Human error
- Data Cleansing Failed
- Data integrity issues
When organizations succumb to common data migration pitfalls, issues such as prolonged downtime and inaccessible or corrupt data wreak havoc on business operations. For example, if employees can’t access the information they need to complete their job, they become frustrated and are more likely to leave the company. A lack of relevant data can also lead to faulty decision-making and lost revenue.
Navigate M&A data migration like a pro
Mergers and acquisitions will most likely play a critical role in corporate strategies throughout 2022. But without a plan and increased visibility into the scope of your data migration, you risk creating inefficiencies that hamper your ability to achieve key objectives.
Here are three M&A data migration best practices to consider:
Spend enough time planning
Organizations often fail to create a realistic project scope for data migration during the planning phase of an M&A, leading to cost overruns and scope drift. In fact, the critical planning phase lays the foundation for your entire data migration.
Stakeholders from both organizations’ business functions should participate in this step to ensure that diverse perspectives and needs are met during the migration. Engage in conversations in advance about your data structures, sources, and governance standards to resolve any issues before migration.
Planning phase discussions should also provide visibility into changes to data structures, the migration timeline, and the roles and responsibilities of each stakeholder group. Overcommunication is key – it’s much easier to solve problems upfront than to put out fires later.
Rely on third-party tools and expertise
You shouldn’t handle an M&A on your own – and you don’t have to. While most organizations do not have a specific team or department specializing in integration, solution providers and consultants can offer personalized assistance throughout the data migration process.
You should also equip your team with digital tools and solutions that facilitate a seamless migration. When researching various solutions, look for options that support automation, increase visibility, and provide deep analytics capabilities to improve decision making. Imagine you are tasked with adding 500 users to a new system at the company you are merging with. Performing this task manually is time-consuming and error-prone – a great place to incorporate automation.
Don’t rush the tests
Data migration testing ensures a positive user experience for employees after migration. Testing should include data-level validation to rule out discrepancies between old and new databases, as well as application-level validation testing to ensure application functionality. Additionally, test data and applications before and after migration in different environments to ensure that you extract only the data you need and that it translates to the new database.
A data migration shouldn’t get in the way of your merger or acquisition, especially when you’re equipped with the right expertise and tools. From demand planning to customer service, data is critical to the success of your organization. So give your data migration the time and resources it deserves to retain your employees and grow your business.