In my last post I started to talk about ideas for classifying the data management issues, with the reasoning that it will help to determine the feasibility that the expectation that acquiring a particular solution will actually address the core issues. I actually have used this categorization with some of our customers, and the process of classification does lend some clarity when considering solutions. There are five categories:
- Management and Governance – These are issues having to do with data usability, access, or quality policies, oversight of data standards, business rules, standardized information management processes, and potentially shared services that can be standardized.
- Process – These are issues highlighting gaps, redundancies, or inconsistencies in the processes and the ways that critical address data elements are created, modified, and read.
- Modeling and Information Architecture – These are issues that are associated with absent data definitions, conflicting definitions, inconsistencies in data element formats, overloaded use of common terms, etc.
- Synchronization – These are issues that occur when there are lags from the time that address data elements are created or modified in one system or data set to the time the updates are shared with other business activities or propagated to other applications or data sets, or when changes are not shared at all.
- Technology – These are issues associated with application infrastructure, acquired tools and their configurations, and embedded rules.
I put these is some semblance of an order, but it is valuable to note that the first three of the five categories are not system issues, but are systemic issues in that they reflect challenges that exist within the organizational system. We’ll consider the systemic issues in the next post, and the system issues following that…