Is your data garbage? Are your attributes fit for the dumpster? Would it be easier to find a document if it were literally in the trash can next to your desk? USDM has a recycling program where we will take all your junk and transform it to beautiful, accessible information- saving time and money.
ECM SYSTEM DATA CLEAN UP
We often encounter clients who complain that their ECM solution does not meet their current needs. Some of the reasons frequently encountered are:
- The initial system was set up poorly,
- Over time the system has grown so large and unwieldy (ECM creep) that it is near impossible to find information.
- Different users use the system differently thus resulting in inconsistent data. This makes navigation and search impossible.
- The system has redundant information with other systems (such as, ERP or LMS). In most cases, there are discrepancies in the data between the systems.
- The complaints are usually directed at the ECM platform when in most cases, the platform itself is not at fault. It just needs a bit of an overhaul.
USDM employs a step-by-step ECM data clean up methodology. Some of the steps are:
- Step 1 DEFINITION: Define "clean" "to-be" environment. Establish requirements for the same. Incorporate additional features such as integration with other systems, new workflows, new metadata, new content to better serve the needs of the users. Ensure robust rules are built to prevent ECM creep or incorrect usage of the system. Ensure strong configuration management is in place.
- Step 2 CONFIGURATION: Set up the "clean" environment. Perform Conference Room Pilots (CRPs) and mock-ups for user feedback. Establish a comprehensive data dictionary that describes each content type stored in the system and what the content means to the end-users.
- Step 3 ANALYSIS: In parallel to Step 2, iterate through each logical content group (by department, by content type, by site) and identify gaps between the existing system and the new system. Identify migration strategy (how to get this particular set of content to the "clean" environment).
- Step 4 MIGRATION: Using a phased approach (by department, by site, by content type) migrate the data over to the new environment.
- Step 5 COMMUNICATION: Train the users of the system thoroughly on the system and the data dictionary and ensure frequent future audits of the data. Implement rigorous configuration management.