December 6, 2018
The Challenge of Good Data
In this webinar, Bryan emphasizes how LPs need a quality dataset for benchmarking. However, LPs still don’t have a source of great quality data. Quality data means having the underlying financial statements of each fund or investment. LP reported data is preferable since GPs have obvious incentives to skew reported performance. Hamilton Lane asks four questions when evaluating data providers:
· Quality – can the provider independently verify the data?
· Completeness – does the provider have a full slate of data points for each fund?
· Industry coverage – does the set cover a critical mass for the strategy in question?
· Institutional coverage – does the set feature performance data from institutional quality managers?
Using Good Data for Benchmarking
LPs can create a benchmark plan that reflects the unique needs and goals of the portfolio. This requires filtering down the dataset in relevant ways to isolate style, geography, or manager. The goal is for LPs to easily determine what is the opportunity cost of investing in a fund relative to where else capital could be allocated?
· How LPs approach metrics, like IRR and TWR, for benchmarking
· Insight into benchmarking your private markets portfolio to the public markets
· Further insight into how investors approach benchmarking