Data Migration is a critical component of most software implementations and must be addressed early in the project life cycle. And it usually is, but something is often missing.
Most decision-makers, project managers, and consultants have heard about “garbage in, garbage out”. Therefore, while challenging and time-consuming, the technical aspects of data migration are understood, documented, properly planned, and executed.
Data migration activities usually include identifying the source of truth, extracting the data, cleansing, deduplication, data enrichment, other transformation rules, determining what format and where the data should go, choosing the right tools, etc.
On the other hand, the business component of data migration—the “why and for what purpose we need the data”—is often insufficiently addressed or is missing entirely.
For example, the most common approach is to import active customers and vendors and their opening balances, noting that the definition of “active” varies from project to project. Is this the optimal solution for data migration?
It depends!
To choose the right option, it is a must to assess what data is still business-relevant and what is not. At the minimum, you must know the answer to the following questions (and others):
– Are inactive customers kept elsewhere (e.g., a CRM solution, a data warehouse, etc.)?
– Will the business still have access to historical data after going live?
– Is the business running multi-year forecasts? If positive, are historical data readily accessible?
– What data are required to comply with legal and regulatory obligations?
If answers to these questions are mostly NO, you should consider cleansing and migrating at least the following:
– All customers who are not out of business and their contacts; maybe vendors as well, but these are not as critical as customers.
– Sales per customer per month/quarter/year – whatever is relevant for the business
– Monthly movements for your GL accounts to support forecasting and budgeting
– Inventory and sales: knowing best sellers is critical
– All active fixed assets, even if fully depreciated, so they are not misplaced.
Imagine having a former customer who wants to do business again with your organisation, and you have no information about past sales.
While additional data will make the data migration more complex, not having these valuable insights will cripple the business.
In conclusion, a successful data migration strategy evaluates data relevance for stakeholders and ensures alignment between data and business objectives to lay a solid foundation for future success.