Replacing legacy claim systems and re-configuring core claims management systems are complex projects with high risk factors. Once it has been determined that a new core system will be put in place insurers are faced with the task of moving data from one system to another. Mapping out a solid plan for a successful data conversion can’t be emphasized enough. A great start to putting together a plan is identifying who should be involved. The data conversion team should consist of but are not limited to IT personnel, business analysts, underwriters (if it is a policy admin conversion), data architects, claim supervisors, and representatives from each department. The root issue of most failed data conversion projects has been because conversion plans were not clearly mapped out.
Creating a data conversion checklist prior to moving the data creates a methodology that will help in creating possible solutions for problems that could occur. Keep in mind these limitations that can occur prior to beginning a data conversion project:
- Has the new IT system or IT process been fully described?
- What is the hardware or software environment?
- What will be the end-user environment?
- Is there an existing interface or process that is mandatory?
- What are the data depository and distribution requirements?
- What is the allotted amount of time required for the full conversion?
- Are there any security requirements?
- How much data in total needs to be converted?
When mapping the data’s conversion from the legacy system to the new model your next step in analyzing the source data will be crucial. With the ever changing insurance industry, carriers are now recognizing the importance of big data. Data is now used more tactfully and has become a high priority source to shed light on trends, and market changes. There will be risks that can affect the technical performance of the converted system including data quality problems. Data quality limitations included:
- Mismatched fields
- Duplicated content
- Using multiple programs to compile data (i.e. Excel, Access)
- Data variations prior to system upgrades
- Unorganized documents
- Corrupted data
Take into account all possible data variations and differentiation issues that may come up when converting data to a modernized claims processing system. Insurers are now using their data repository as a strategic advantage. A well-articulated plan needs to be put in place to map out how the data will be moved, the quality of the data, and how it will be used for historical analysis.