Founded in 1908, Reed College is a private liberal-arts institution located in Portland, Oregon. Known for its rigorous academic culture and the pursuit of critical thinking and inquiry, the 1,400 strong student body benefits from a close-knit, collaborative community emphasizing a deep commitment to intellectual curiosity and academic exploration. The endowment, which is roughly $1 billion in size, contributes about a 1/3 to the operating budget of the college each year.
Erik Bernhardt joined Reed College in 2019 as its inaugural Chief Investment Officer. Together with his colleague Andrew Lonergan, he oversees the management of the college's endowment. Prior to stepping into the CIO role at Reed, Bernhardt worked at Cambridge Associates, PAAMCO, and Artisan Partners.
As an Oregon resident, his favorite aspect of living there is the Cascade Mountains of the Pacific Northwest, the spectacular free-standing volcanoes that define the region. With Mt. Hood just a short drive from Portland, he enjoys access to seven months of skiing and abundant snowfall. Once the snow melts, the mountain transforms into an ideal destination for multi-day backpacking adventures.
Upon joining the college, Bernhardt recognized an immediate challenge: Reed’s investment data, analytics, and workflows were insufficient for a modern endowment.
Key issues included:
Bernhardt explains:
“One of my main goals was to institutionalize the investment office. We needed stronger systems and processes, and we simply didn’t have the data to perform meaningful analysis. Venn was exactly what we were missing.”
When Bernhardt arrived at Reed, his first priorities were to establish an investment philosophy, develop an optimal portfolio structure for each asset class, and evaluate existing managers while identifying new ones where needed. A large component of this analysis was quantitative, and this is where Venn made a significant difference. For example, the team leveraged Venn for:
Bernhardt needed to validate Reed’s core/satellite public equity structure. By uploading monthly returns into Venn, the team could instantly analyze:
Insights gained through Venn:
“With performance data loaded into Venn, we quickly identified what was working and what wasn't. Our core managers were performing well with appropriate tracking error and strong information ratios. However, some satellite managers were too diversified and, from a factor perspective, too similar to one another.”
Furthermore, using the system's contribution-to-risk metrics—both relative and absolute—Bernhardt implemented a more structured weighting approach. For example, Reed had two managers with similar information ratios but one with a higher tracking error. This insight led the team to reduce the manager’s weighting in the portfolio to better match their overall contribution to risk.
Constructing a hedge fund portfolio is difficult due to constantly shifting exposures.
Bernhardt explains:
“Venn’s ability to demonstrate factor loadings across time periods proved beneficial for understanding the big picture. What I found especially useful was seeing how those loadings changed over time and then easily unpacking the data to identify which managers were driving those changes."
This capability enabled Reed to:
A key part of Reed’s investment philosophy is identifying managers who operate in niche or capacity constrained strategies and demonstrate alpha generation over time within this context.
Venn is designed to make this process significantly more efficient.
"I'm always looking for managers who can generate alpha while fitting into the overall structure and philosophy of the total portfolio. Venn allowed me to validate my hypotheses almost instantly. Analysis related to our US equity profile is a good example here. We had a long standing ‘core’ manager that ran a 130/30 that appeared to run with low tracking error and strong alpha regardless of the market environment. Venn let me test and confirm this belief in a very short period of time. On the other hand, the ‘satellite’ managers need to behave differently; that is, they should demonstrate and we should embrace meaningful tracking error in their long-term return pattern. Our analysis on Venn revealed that some of our managers in the satellite bucket were actually functioning more like core managers, which was not ideal. Venn is incredibly valuable for validating what you intuitively suspect and, importantly, helps provide concrete evidence for the Investment Committee.”
“Venn has become an essential screening tool early in the process for determining whether adding a prospective manager makes sense going forward. I upload monthly returns into Venn and examine the factors to see how they relate to my portfolio’s positioning and existing managers in terms of exposures and correlations. Residual correlation is particularly important to me when evaluating managers for the hedge fund portfolio. "
Thanks to Venn, Reed College’s investment office achieved measurable improvements in analysis quality and operational efficiency.
Impact Highlights
Centralized analytics replaced fragmented spreadsheets
More accurate portfolio insights across asset classes
Faster manager evaluations (minutes vs. hours)
Reduced operational burden for a two-person team
More robust Investment Committee discussions backed by data
Improved ability to structure and underwrite the total portfolio
Reed plans to deepen its use of Venn, especially as the platform continues expanding private markets capabilities.
"Venn has done an incredible job improving and adding new features to the platform. We hope to start leveraging more of what Venn offers, particularly on the private markets side."
"Unlike many of our peers, we are fortunate that we are not experiencing a liquidity problem—even with our private investments comprising roughly a third of our portfolio. The question now is how to take advantage of that strong liquidity profile. We're looking at areas of the market where there’s been dislocation or where there is a dearth of capital due to large allocators pulling back a bit."
Disclaimer: The Venn subscriber featured on this page was not compensated for their statements. As a Venn subscriber, their use of portfolio analytics or other Venn features and their experience could differ from your organization’s due to their particular use of Venn, the version of Venn used, or other factors. Not all subscribers will be equally satisfied. The person providing this testimonial was selected based on a variety of factors, some of which are subjective. This document is for informational purposes only. Not an offer to buy or sell securities. Click here for Important Disclosure and Disclaimer Information