How Portfolio Managers Are Using Analytics and Data Visualization to Boost Performance

As recently highlighted in Bain & Company’s 2020 Global Private Equity Report, today’s PE firms face headwinds in the current low-interest-rate environment. With asset prices increasingly diverging from their value, firms need to build new competitive advantages, and speedy data analysis offers a solution.

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However, data is typically a bottleneck for PE firms. Managers have been known to create Excel hell for themselves by manually compiling all of their data into spreadsheets that quickly become unwieldy and impossible to keep up-to-date, especially given how quickly things change in the markets.

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This is exactly why today’s portfolio managers, even at smaller firms, have started ditching their spreadsheets and instead using business intelligence (BI) platforms that can pull in all of the necessary information in near real time, map out all of the data connections on autopilot and display trends using easy-to-digest, interactive visualizations. With today’s leading advanced BI tools, which don’t require any coded queries or tech-heavy interfaces, managers can run their own analytics reports to spot opportunities.

Let’s take a deeper dive into exactly how data visualizations and analytics are helping PE firms to use their data more efficiently.

Better Data Visualization Through Dashboards

In the old way of doing things, the typical analysis workflow involves employees pushing data into Excel pivot tables and creating one-off custom graphs using that data. This process is labor-intensive and requires analysts to spend the majority of their time figuring out Excel instead of using data to draw conclusions that affect portfolio performance.

Today’s advanced analytics platforms support powerful data visualization tools that are intuitive to use. As you can see, there's no need to query databases to retrieve data, since the software prepares and presents relevant information to the analyst. The graphs and charts generated by the software can be configured to react to real-time updates. As a result, firms can quickly spot and move on trends with a few clicks.

By eliminating the need to manually gather data and validate information integrity, PE companies can spend more time focusing on their portfolio transactions. There's no need for analysts to rely on IT departments to run complex queries and wait for results. They can use their intuition to slice and dice data as they wish and present results in visually impactful ways.

Better Data Consolidation

These days, data is produced everywhere, and gathering these disparate sources of data together is a challenge. PE firms usually store information in different databases, depending on the source.

When the time comes for analysis, they rely on IT departments to clean and standardize all of the raw signals. Valuable time is lost in this process, and there's no way a firm can keep up with rapidly changing situations. Data becomes a hurdle, and managers start relying on intuition, which produces poor decisions.

The solution to this scenario is to use an analytics package that draws data automatically from different sources, without the need for manual intervention. Whether the data is from a live pipeline or accessed from an archive, analysts can join and break down large data sets easily. Joining data is easy thanks to visual connectors on the front end. There's no need for IT support beyond the initial connection stage, which is another reason why so many finance teams are planning to double down on their BI activity in 2021.

In fluid situations, analytics software can alert firms to new developments by seamlessly integrating new data into existing reports, irrespective of the source. Firms can react more intelligently as a result.

Enhanced Collaboration

Everyone in an organization brings different skills to the table. Firms can attack issues in creative ways. However, from a data presentation perspective, these different skills pose a problem. People understand and interpret data differently. To unlock insights, data has to be presented in ways that appeal to people's individual approaches, instead of restricting data reporting to a few formats.

Once data is gathered into an analytics application, it can be shared across the organization in multiple formats on multiple platforms. Employees can create reports on the go and also break down existing dashboards to drill further into data. When collaborating, each person can tailor their dashboard according to their preferences, and this drives better insights.

Best of all, investment objectives don't need to be translated into technical terms and then translated back to business-friendly reports. Everyone gets to analyze data their way and bring their unique perspective to the table.

Removes Data Silos

A common occurrence in any large organization is the presence of different databases. Over time, teams begin relying on data that is relevant to them and create their data silos. These silos hamper collaboration, and the resultant reports capture just a fraction of the data.

Even worse, the reports generated from individual silos are rolled into larger reports and presented to upper management as a collective view across the organization. When creating these larger reports, data is checked for duplicates, and data sets need to be validated for integrity. All of this costs time. Given the quality of the final report, it isn't as if this is time well spent.

Data democratization is easy with a single analytics platform. Investment managers need IT support to clean data initially, but once standards are established, it's easy to view data seamlessly. As a result, organizations have more confidence in their portfolio-level decisions. There's no need to roll data from different sources together. By eliminating the number of tasks that have to be carried out when presenting data, organizations reduce potential points of failure in their workflow.

Better Analytics for Better Portfolios

PE firms handle mountains of data, but the key is for them to use these data intelligently. Current workflows contain many points of failure, and a BI analytics package can remove them. As a result, firms can make better decisions and react quickly to fluid environments, no matter where their data comes from.