Business Issue
The client viewed improved customer service as a competitive advantage in a tight marketplace. They felt strongly that by providing better shipment information that was available anytime on the web, they could achieve a competitive advantage. These new services included: on-line tracking, proactive notifications, historical reporting, and automated documentation services.
However, early on in their efforts to provide these improved services the company realized that much of their internal data was too poor to share directly with customers. For years, the customer service reps and sales personnel had been serving as a filter to provide accurate information. With that filter gone, customers were going to be getting conflicting and inaccurate information from the new systems.
The problem was so massive, it was difficult to get a handle on the issues. The data was collected in all corners of the world and covered many different transportation modes and many different suppliers. The root causes of the errors included process, people and technology issues.
Approach
Because the effort was so massive and cut across multiple functions in the organization, a separate project team was established as the central point of contact for all data integrity issues. This data integrity team undertook the following activities:
- Identified and catalogued all the data integrity issues.
- Prioritized the issues based on ultimate impact to the customer, either by frequency or severity.
- Researched the root cause of the issue which was usually due to one of the following: non-compliance to data entry requirements by employees or vendors, systems error, or inadequate training.
- Assigned teams to address the root cause in order of priority.
- Established metrics to measure accuracy and timeliness.
- Installed penalties for non-compliance with data entry requirements.
Result
The shipping line was able to launch their new services with only a limited delay. Rational decisions could be made about the acceptable level of data integrity prior to the release of new functionality. Customer use of the new services increased as customer confidence in the data quality increased.
