Reduce Cost Overruns and Surprises by Avoiding Common Data Migration Pitfalls
Companies that can fully harness the power of their data will outperform their competition.
Data has long been one of the most valuable and strategic assets of an enterprise. Successful enterprises depend on data for effective decision-making, and many have built strong data foundations that are robust and consist of trust-worthy data.
However, even strong foundations can be stressed when organizations need to migrate data, either as a result of installing new IT capabilities or a merger or acquisition. The challenge has become even greater in the last few years as the Big Data explosion has exponentially increased the volume, variety and velocity of data that must be managed. Those that handle the data migration process well will see orders of magnitude returns on their investments.
Unfortunately, data migration projects can hit major snags, especially late in the process when fixes are more costly. An Americas SAP User Group (ASUG) report notes that 75 percent of respondents experienced data management issues late in a data migration process, with 93 percent of those issues considered “significant.”
A well-planned data migration strategy ensures that risks to the business are minimized. With careful execution, it is possible to realize business benefits and ROI from data migration projects in the shortest time possible.
For example, a successful ERP implementation plan, should include the following:
- Project preparation
- Creating a business blueprint
- A separate data track to avoid costly delays and project overruns
- Implementating the actual migration process
- Testing, and
- “Go-Live” with continuing data support.
For instance, IT personnel or systems integrators should first determine if old and new data definitions and formats match, and how to address variances, before deciding how much data needs to be moved. They must establish data standards and business rules for migration and future use.
Determining data quality is critical, especially for data residing in legacy systems. Data most likely will be used differently going forward, underscoring the importance of conferring with data owners and users about whether it is currently fit for use, and if it will support new uses. The time to discuss and rectify data weaknesses that would prevent it from being used for what you would like to use it for is before the project begins. Then, establish data quality baselines to guide standardization, consolidation, harmonization and enrichment, and define key performance indicators and other metrics.
To prevent costly headaches later, validate, redefine and document business rules before migration begins. Now is the time to refine these rules based on future business processes, how and where data will be used, and by whom, bearing in mind regulatory and policy requirements.
Establishing master data governance rules before data migration is essential, as is determining who will have responsibility for the data following migration. Ideally, strategic and operational data stewards should be appointed to ensure that each data object has a data owner. “C-level” management sponsors can provide valuable scope, direction, support, financing and other resources.
Who has to live with the results of your company’s data migration? You, or your systems integrator? Successful migration is the primary objective, but the process doesn’t end there. Therefore, assign company managers with the aptitude and attitude required to manage staff, processes and technology.