Old Well Labs (OWL)

Capital allocators are investors typically charged with deploying resources on behalf of the institutions they work for in order to meet key organizational objectives and performance goals. Allocators accomplish this by deploying capital across various funds, each of which must be discovered, vetted and monitored over time. As a result, an alloctor’s ability to deliver returns to their institution rests entirely on their ability to find, monitor and connect with the most strategic funds for their portfolio.

The founding team at OWL are no strangers to the challenges faced by allocators. The team developed the initial version of the OWL platform as part of a systematic hedge fund strategy, allowing them to monitor the performance of funds around the world. This tool, which quickly gained popularity among the team’s network of peers, found enough momentum to spin out into a standalone company, Old Well Labs. Today, the OWL platform not only provides holdings data across more than ten thousand funds, but also allows allocators to benchmark performance against their peers, evaluate the organizational history of a fund, and even discover promising new funds right at their inception.

Talent data forms a key part of OWL’s offering, allowing allocators to evaluate and monitor the expertise and experience of the managers behind the funds they invest in. Unexpectedly, OWL discovered that they could also help their users identify the launch of promising new funds by tracking changes in team composition at relevant organizations, particularly as key individuals left to start their own fund.

Having fresh and accurate talent data became essential in order to provide their users with reliable intelligence. However, despite the significant value it offered, sourcing the necessary talent data at scale proved to be particularly challenging.

The OWL team has two main criteria when sourcing data: depth and quality.

For talent data, the team was searching for a dataset that could track the evolving relationships between individuals and the companies they worked for.

To provide their users with the person data they needed, OWL chose to source their data from People Data Labs.

With access to a standardized and regularly refreshed dataset of work history, educational experience and contact information, OWL has been able to dramatically expand their coverage of new and existing funds.

OWL now tracks nearly 10,000 funds on their platform for allocators to find, monitor and connect with. With a scalable solution in place for sourcing talent data, OWL is poised to continue their rapid growth trajectory into the coming years.