Mining company resolves data challenges to move to outsourcing

This mining company, with history dating back more than 185 years, finds, extracts and processes copper, gold and molybdenum. They are focused on their people, promoting an inclusive work environment and encouraging employees to share ideas that drive innovation.

The Challenge

The company had administered their pension plan internally for years and had significant concerns around data quality and their ability to consolidate data from multiple sources in order to move to outsourced administration. They had tried unsuccessfully to outsource their administration in the past and knew they had to address these data issues in order to move forward. With the upcoming retirement of a key internal administrator, the client was planning for the future and looking for a partner who could assist with data concerns and provide a high-quality pension experience for both administrators and participants.

The Solution

As part of our proposal for pension outsourcing, we knew the client needed direction and support for how to best document their data sources and how to extract, reconcile and consolidate the data needed for future outsourced pension administration needs. Along with our outsourcing services, we were the only vendor that demonstrated expertise at the level of our Data Solutions team as well as provided a substantive framework for data extraction and enhanced data conversion backed by a proprietary review tool. Our high-touch call center and outsourcing capabilities, combined with our data expertise, were critical to being awarded the project.

The Results

The project resulted in data aggregation from several sources (including multiple systems, paper files, and Excel spreadsheets) and more than 1,000 individual files to complete employment history for all participants. The immediate benefits include:

• Review of processes and identification of improvements reducing the administrative cost annually
• Improved system automation and ability for more participants to use employee self-service tools
• Reduction in future costs related to data research, manual calculations and potentially higher call volumes
• Significant reduction in administrative burden, including the elimination of the requirement to maintain multiple data sources and less reliance on internal resources
• Improved data quality
• Reduced risk of errors and omissions