It's much easier to find out if you've got a problem with your workplace pension's data, than you think. This short presentation helps employers and trustees discover the quality of service they are getting from their administrators.

1. Data Diagnostics
Analysing the quality of scheme data

2. Measures
• Any gaps in the data
• Text and number formats are respected
• Consistency in the manner data is recorded
• Removal of any duplicate records
• Integrity issues that would undermine results
• Inaccurate record keeping
What are we looking for in our data quality assessment?

3. Overview

4. Outlier Categories
Typically seen when members transfer out but remain in the dataset
Impossible IRR figures & other data anomalies such as dates in the future
Implausibly high IRR figure that needs verifying
Implausibly low IRR figure that needs verifying

5. Further Analysis
Short
contribution
history
Outliers
Number of new
members
High IRR
• Number of
members
• Total NAV
Low IRR
• Number of
members
• Total NAV
Inaccurate record
• Number of
members
• Number of records
• Total NAV
0 NAV
• Number of
members
• Total contributions
High IRR
• Number of
members
• Total NAV
Categories
• Timeframe
(months) until
score is available
• Total value per
timeframe

6. • Internal Auditing
• Dashboard readiness
• Part of VFM quality of service measure
Use cases