Is Your Research Team Drowning in Data Bottlenecks?

Many quantitative research teams face a critical challenge that quietly erodes their competitive edge: data infrastructure bottlenecks that strangle research velocity. While the symptoms are easy to spot, the hidden costs extend far beyond delayed projects.

Five Warning Signs of Data Infrastructure Problems

Research teams experiencing infrastructure constraints typically exhibit several telltale signs:

Data request backlogs: Tickets accumulate faster than they can be resolved, creating growing queues that frustrate researchers and slow down discovery.

Extended time-to-backtest: When research projects consistently require three weeks or more before generating a first backtest, infrastructure friction is hampering innovation.

Tool limitation complaints: Quantitative researchers repeatedly voicing frustrations about platform constraints signal that existing systems can’t keep pace with analytical needs.

Engineering resource drain: When engineering teams dedicate 80% or more of their time to pipeline maintenance rather than building new capabilities, infrastructure becomes a liability rather than an asset.

Provisioning delays: Simple questions like "Can we test this signal?” are met with responses about IT provisioning timelines, indicating that data access has become a procedural obstacle rather than an enabler.

The Real Cost: Undiscovered Alpha

Organizations experiencing three or more of these symptoms face infrastructure challenges that actively limit research potential. However, the most significant cost isn't the visible delay in completing current projects—it's the strategies that never get explored because accessing the necessary data proves too difficult.

When data provisioning becomes prohibitively time-consuming or complex, research teams naturally gravitate toward investigations using readily available data rather than pursuing potentially more promising avenues that require additional infrastructure work. This invisible opportunity cost compounds over time, potentially representing far more value than the efficiency losses in existing workflows.

A New Approach to Research Infrastructure

Leading quantitative firms are fundamentally reimagining their approach to research infrastructure, collapsing data provisioning timelines from weeks to days. This transformation eliminates infrastructure as a constraint on research velocity, allowing teams to pursue investigations based on strategic merit rather than data accessibility.

Modern solutions focus on removing friction from the research process, enabling quantitative teams to spend their time generating alpha rather than waiting for data or working around platform limitations.

Contact us to learn more about how forward-thinking firms are solving these data infrastructure challenges and accelerating their research velocity.