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Best practices for the modern, data-driven private equity firm

How third-party data can deepen intelligence, and the importance of data stewardship, by Preqin and DealCloud.

This article was originally published on the Preqin website

Every private equity fund manager has come to terms with the importance of data; both the game-changing potential of good data and the pitfalls of poorly managed data. However, few have effectively implemented a data strategy at their firm, and even fewer have found ways to integrate data-powered reporting and analytics into their day-to-day relationship and deal management efforts.

Below are two best practices compiled by DealCloud and Preqin that can have a major impact for private equity firms seeking to unlock the full potential of their intelligence.

1. Keep a clean dataset

Your firm’s ability and willingness to maintain strong, clean data right from the start is critical. Great data stewardship is one of the easiest ways to ensure that every member of your team is getting the most out of their day-to-day activities, and is a crucial element of your firm’s operational success.

All information (whether gathered by human or machine) needs to be checked for quality, corroborated and tied back to reality to be of any use, as explained in Preqin’s recent whitepaper, Don’t Believe the Hype – Collecting Data in a Post-Truth World. Engaged and intelligent human curation will always result in the highest-quality data.

Clean data does not stay clean of its own volition. Your data-cleansing efforts can easily be undone with a few short weeks of careless use. That’s why it’s important to prepare all users to build data curation into their day-to-day processes, no matter the size of your organization. Making a concerted effort upfront to train team members on the importance of avoiding redundancies and errors in the data can significantly impact how useful your system becomes over time.

2. Layer your data, leverage your insights

Even when all the available data has been collected and logged in the dataset, the work has barely begun. Raw data, especially when it relates to real-world activities, can often paint a confusing, fragmented and contradictory picture. This makes it difficult to know how the data relates to what is really going on. That’s why best-in-class private equity firms are skillful in layering and contextualizing the data they collect and report on.

One proven strategy is to take a firm’s proprietary data and layer expert, third-party data on top of it to gather deeper insights. For example, a firm might compile data on its interactions with a given advisory firm (emails, calls etc.). It can then layer third-party data over that, looking at the offices that advisory firm has across the globe. In doing so, the private equity firm can more accurately understand the strength of its relationships with all of the investment bankers at that given firm. This level of detailed information allows the firm to plan targeted business development trips to those cities and countries where their intermediary relationships need improvement.

The possibilities are endless when layering data, and each firm can take a unique approach depending on the data points that are most important to them. Some firms might hinge their strategy on industry specialization, and will layer their own data with third-party insights on sub-sector deal activity or potential talent with deep sector expertise. Others may choose to layer with third-party data based on geography, or deal size, or any of a thousand different categories.

No matter what the strategy is, firms should think critically about where and how third-party data can deepen their intelligence and help them to leverage their proprietary data. Failure to do so will lead to firms succumbing to their competition.