How to address the most common VC data challenges

Data is everywhere. It’s plentiful. It’s vast. Often stored in a plethora of spreadsheets or disparate systems, however, it’s not often immediately available or usable. The impact? Data remains disconnected from those who need it, and VC firms may be limited in their ability to respond to investor requests quickly, hamstrung by operational inefficiencies.

A group of CFOs from leading venture capital firms recently participated in a virtual roundtable to discuss emergent data challenges and how best to address them. Here is a summary of their conversation.

Changing investor expectations and the sheer abundance of tracked information have many firms struggling to keep pace with real-time data demands. The conversation revealed four leading reasons for this data disconnect.

With information originating from different sources to solve different problems, data management can quickly become a ‘Frankenstein’-ed process. One leader shared that “portfolio monitoring has always been the great white whale that we are trying to chase down—especially for our partners—showing how our companies are doing and aggregating everything.”

As the amount of data and the number of data sources available to VCs proliferates, the heart of the data management challenge has become interoperability. When firms use multiple data sources and management tools—whether spreadsheets, accounting systems, or other departmental or enterprise systems—they often struggle to get those tools and systems to connect, to “speak with one another,” and to share data easily, cleanly, and immediately.

Multiple data formats further complicate matters, making sharing information another challenge. Merging data from different sources into a standard format that can be shared has become a significant pain point for firms. As one leader explained: “There's the accounting data source, and there's a company data source…. Merging those two together is one of the main challenges for us.”

Multi-format data, therefore, impedes a VC firm’s ability to automate reporting and create repeatable processes. Factoring in one-off data requests from investors and partners, a firm could end up trying to match and compile the same data multiple times—a time-consuming and error-prone process.

The growing demand for near-real-time data creates notable challenges to compiling, verifying, and sharing data during various phases of the investment lifecycle.

Routine reporting

Whether quarterly or annually, the demand for regular reporting and visibility isn’t new. It’s essential to provide investors with the visibility and insights they need into the performance of their investment portfolios. However, the emerging challenge is to provide LPs with the exact data they want without incurring maximum effort on the part of the VC firm.

One leader said, “Streamlining repetitive processes and joining the data are some of the things I feel are critical right now.”

Bespoke requests

Responding to off-cycle, custom, or one-off requests from LPs stresses VC data management systems and processes, especially when the request involves pulling from disparate sources.

“One thing that we were trying to think about is, ‘How do I get that more automated?’” noted one participant. “Right now, it's done manually, where it's sent to Investor Relations and then our fund administrator to fulfill the requests.… Monitoring all of those requests to make sure they’re taken care of has been the true pain point for me because there are so many—and it’s very manual.”

Fundraising requests

Being able to provide company assessment data to investors during fundraising is imperative to assessing an opportunity properly and, again, not a new type of request. What is a growing challenge is keeping that data fresh or providing updated data in real time. Publishing data once and then needing to refresh at various intervals—whether quarterly, monthly, or whatever the desired cadence—has proven difficult because it typically means cobbling information together from multiple sources, confirming that it’s accurate, and then delivering it in an intelligible format for investors. Fundraising demands an efficient, systemized, and repeatable approach to reporting—and reports that can be customized throughout the fundraising process. And that can be an enormous challenge for lean VC teams.

Audits

As one leader said, the auditing ideal for data is that “data is never written down twice. It's written down once, and then it's sent to the right place, the right person, at the right time.” Capturing, managing, or storing data in multiple formats and locales not only violates this ideal but can also pose risks to accuracy, security, and privacy.

Many firms find themselves stuck in spreadsheets. There’s a good reason for that: spreadsheets have been, and can still be, an effective tool for collecting and manipulating data. The hard truth for many firms, though, is that spreadsheets simply don’t meet the demands of modern investors. They don’t easily accommodate data requests or real-time reporting, and they can require a level of user expertise to manage and interpret that many investors may not have.

What’s more, spreadsheets come with three additional drawbacks.

1. Manual management: Capturing and monitoring the amount of data most VCs manage requires multiple spreadsheets. One leader noted that one of the challenges “of being stuck in spreadsheets" is that they require manual management that can be time-intensive and error-prone.

2. Errors: Whether it’s an automatic feed error or a data drill-down issue when VCs need timely underlying information on a portfolio company, they often turn to some kind of Excel plugin or automatic feed. Those can be error-prone, as one participant mentioned, especially if the plugin itself isn’t working properly. That, in turn, can lead to additional data errors.

3. Duplicative effort: While many VC teams are comfortable with spreadsheets and their ability to drill down and comment on various data points, pulling information dynamically out of spreadsheets and maintaining a historical record is difficult at best. What’s more, when firms rely on multiple spreadsheets to manage data, the chances of duplicate data tick up. That means increased effort to review the data and remove duplicates. Further, manual clean-up can introduce even more room for human error.

Many firms find themselves stuck in spreadsheets. There’s a good reason for that: spreadsheets have been, and can still be, an effective tool for collecting and manipulating data. They’re easily available, thanks to the near ubiquity of MS Excel, and can be used as a simple data organizational tool or for more sophisticated data manipulation. The hard truth for many firms, though, is that spreadsheets simply don’t meet the demands of modern investors. They don’t easily accommodate data requests or real-time reporting, and they can require a level of user expertise to manage and interpret that many investors may not have.

Time is money, and VC leaders and their teams are particularly prone to run short on it—especially when it comes to managing data. Balancing data management with their day jobs is a challenge for many GPs. So much so, in fact, that one leader commented they’ve assigned a “data steward… somebody who's solely focused on data-related projects.” Another participant said time is the “big pain point” of monitoring data on a real-time basis. Yet another said that when executing their day job, time is the “biggest blocker” for making any kind of data management change.

The roundtable participants agreed that their various data challenges boil down to a single statement: currently, data management tends to be manual, scattered, and lacking efficiency. In response, each offered their ideal vision for data management, highlighting these qualities.

• A single source of truth that empowers users with access to the data they want and need to collaborate easily and securely with partners—without taking time away from the important work of diligence and deal-sourcing to accommodate data requests.

• Real-time availability that’s self-service for everyone who needs it. For instance, when someone wants to know how a portfolio company or potential investment is performing, they can simply access the data they need through a portal without reaching out to anyone else for it. That ensures that the right data is available to the right people when they need it—free from bottlenecks or operational slowdowns.

• The ideal solution is intentionally designed to function as a whole. It is not merely cobbling together multiple systems, patching gaps in systems, or a homespun solution. Instead, it’s a portal of information designed to scale with a growing firm.

• Repeatable, automated reporting. The ideal solution increases efficiency through repeatable processes and automation. That means, that rather than starting from scratch with each investor request, the system can be set up once to enable repeatable, customizable, and automated reports.

• Interoperability. When a specialized product is needed for a specific use case, it must integrate seamlessly with the rest of the VC’s stack, preventing the siloing of data in different systems.

“I think the way it should work,” said one participant, ”is that the data is available in real-time for everyone. So, when anyone wants to know how this company is doing or how that other company is doing, they don't have to ask anyone. They have a bookmark on their browser for a tool, they go to that tool, and they see the data. That's my dream.”

While many of the panelists have tried various AI software, they discussed how AI might be most effectively used for portfolio management and what role it could play. The general consensus is that AI may be most useful in conducting routine assessments or extracting insights at regular intervals.

Take portfolio company assessments, for example. AI could be beneficial in building a score based on portfolio company financials or compiling an executive summary to help investors and VCs assess opportunities and vet risks associated with prospective investments. As another example, AI could be useful in extracting quarterly insights or executive summaries for VCs—perhaps through a question-and-answer approach, as a start.

The caveat? Data must be structured and all in one place for AI to function most effectively. That is, to even start the AI journey, firms need one source of structured data.

Interested in hearing from more industry leaders about the impact of AI? In a recent webinar, Joseph Harrington, Partner at PwC US, Dana Van Wie, Partner at PwC US, and Adam Walker, Industry Principal of Fund Solutions at Juniper Square, explored the challenges facing CFOs as they sort through the power, promise, and potential missteps with bringing on new technology.

The power and promise of data is immeasurable. But when information is trapped in spreadsheets, any attrition on your team or turnover at your fund administrator means the clever workarounds accountants built to manage your fund financials go with them. Data management issues compound, exposing your firm and your reputation to operational risks.

Proper data management requires a single source of truth that empowers users with access to the data they want and need to collaborate easily and securely with partners. Juniper Square puts you in the driver's seat with a shared system for managing, accessing, and securing investment information.