Background

The business was run on a backbone of home-grown software and database applications.  Over time, the business grew rapidly and maintaining detailed documentation of the technical architecture became nearly impossible, and they soon realized that they needed to completely replace their technical architecture with a state of the art CRM platform to keep up with business needs.

Problem

There were at least six legacy sub-systems supporting the operation of the main business unit, serving the US market.  Over time, a second business unit was acquired in Canada.  At this point, a copy of the US applications was created in its own server to support the Canadian operation.  After several years working in this mode, both sets of applications evolved along different paths based on local need, and the data being managed by both systems became increasingly more error-prone.  The new CRM platform was based on an object-oriented design paradigm, while the legacy systems were flat file.  So, not only did we need to figure out how the legacy structures mapped to the CRM, but the data quality was so disparate that we could not simply “code and load”.

Solution

We led our customer through a thorough, pro-active Data Quality Assessment (DQA).  The  result was a standardized set of metrics reflecting the overall accuracy of each data field in the legacy systems.

Once the analysis identified where the problem data was, we completed a cycle of proposing resolutions to the Executive Planning Group and then implemented them upon approval.

Now that the data itself was consistent, we could map the legacy structures to the new platform.

Benefit

Migration Development saved countless hours by eliminating bad data first

Customer was now on a CRM platform that could support their continued growth

Data Quality was improved at launch

Monitoring controls were acquired to prevent future data quality problems