It will be called an accomplishment, if an organization is able to create data management standards (like universal business rules, universal domain values and universal data models for all data entities), and the new applications follow those standards. Examples are universal standards for customer entity, product entity etc..
Beyond this accomplishment, there is a question on what to do of the data (like customer master as per the old Customer ID structure) and applications (having data validation rules as per the old rules), which exist and are working on a scattered set of old standards?
Creating a big-bang project of changing the existing portfolio as per the new data standards is not an option many organizations would like to choose. One would need to create a funded road-map for this purpose. Here is the mix of tricks which this road-map can use to make it cheaper and faster:
- Ride on the IT business portfolio plan- A large IT initiative may absorb the retrofitting cost.
- Identify and focus on the key data elements which are having widest impact- The criticality will be depending upon the financial, regulatory and productivity impact. It also depends on the cost escalation if you fix it later.
- Use BI environment to enforce the standards- BI through its ETL may provide a work-around, which can avoid the correction in the production (or source systems).
- Try one go change for an application- If you do get to fix it, try to do all the fixes for an application once and for all. Experience tells me that it becomes messy, if we do it in installments.
Though this post is complete in itself, you can refer to more details on this subject in New Data Standards?- What about existing applications in my portal Business Intelligence and Performance Management Institute.
Tags: data standards
