



Bridging the Data Gap in Private Equity and Venture Capital
2022-11-18
If you had to sum up the 2022 private capital landscape in one word, perhaps, that word could be “contradictions.”
The year began with a rather rosy outlook. Venture capital (VC) funds raised $151 billion in the first three quarters of 2022, exceeding any prior full-year fundraising, according to PitchBook Data, Inc. Today, however, both private equity (PE) and venture funds are sitting on a record amount of dry power, as funding contracted this quarter. Another paradox: there is more talk than ever of firms funding more diverse companies and founders—namely, women and people of color—however, the numbers in this realm point in the opposite direction. Indeed, contradictions seem to abound this year.
What does appear to be true, though, is that many firms are using this year’s “messy middle”—a period of enhanced uncertainty—as an impetus to focus not only on right-sized valuations and selective funding, but also on the technologies they’ll employ for competitive advantage. A cornerstone of this effort is a heavy focus on bridging the data gap, so firms can maximize growth opportunities by harnessing the power of data analytics.
The following overview highlights how enabling a data-driven culture can make all the difference at PE and VC firms because now, more than ever, treating data as an asset allows them to more accurately forecast change, innovate quickly, and create advantages to stay ahead in increasingly competitive private markets.
Setting the Stage
Now, let’s be frank—gathering and analyzing private market data is not easy. But, in today’s market, having a data analytics strategy in place is no longer a “nice to have.” It’s absolutely required to drive business operations and digital transformation at private capital firms.
The difficulty in gathering and analyzing private market data is inherent in the way private companies are structured. In contrast, public companies are required to provide data on many aspects of their business—balance sheets, income and cash flow statements, and more—which is then used by financial planners, risk managers and investors. Some economists believe that when all market participants have equal access to company data, equity and debt are priced accurately. However, this also limits the opportunity to use data asymmetry to generate alpha or “beat the market,” since (presumably) everyone has potential access to the same data points.
Yet, part of the ever-growing lure of private company investments is that data—when analyzed tenaciously and correctly—can yield significant competitive advantages for the firms that execute such work. Every firm has an incentive to maintain its data advantage. The most successful firms do this by amassing as much data as possible about private companies and other participants in private markets, while sharing as little data as possible (publicly) about their own portfolio investments.
Collecting data in an expansive world of over 10 million private companies is quite daunting for PE and VC firms. They have some resources at their fingertips—i.e. PitchBook, S&P Global Marketing Intelligence and PE Hub—to name just a few. But, according to a recent Coalition Greenwich study, 62% of investors in the U.S. and Europe said they have difficulty examining the details of the private companies in their portfolios with the data they have.
To overcome this hurdle, some firms have prioritized data analytics, realizing that its crucial to the future of their business. PE and VC firms and their investors have tried to improve the sourcing, standardizing and visualizing of private company data. However, challenges remain in applying actionable insights derived from that data.
Reasons Why a Data Analytics Strategy is Necessary
Here is a non-exhaustive list that highlights why a data analytics strategy is necessary and how it can be applied:
1. Using Data Pre-Deal, In Due Diligence and Deal Origination
Arguably, the biggest opportunity for applying data analytics arises pre-deal, as firms source opportunities, while further conducting necessary due diligence. To date, many firms have not integrated data analytics into deal origination and very few are using data to automate deal sourcing and due diligence, even though more and more managers realize that the use of data in deal origination can be a competitive advantage.
PE and VC firms should apply data analysis in both the pre-deal and due diligence phases to inform key decisions. In doing so, they can confirm or challenge target company assertions, refine valuation model inputs, and identify both commercial opportunities and risks.
However, this is just the tip of the iceberg. Knowing how competitive the market is (and how quickly it can change), firms are now looking beyond just available company data and are increasingly turning to additional data sources—including those offered by research firms, independent advisors, and analytics experts—to refine their investment theses. The data these third parties offer up can help better hone a target company’s existing data pool, since not all target companies maintain the same quality and depth of data.
For example, a PE buyer may leverage third-party online sales data to better assess category trends, pricing and the impact of promotion spend on top-line growth. The application of such additional data can help validate assumptions about a company and its competition before pursuing an asset in the market. A buyer may further extract data points via a research firm by running a series of focus groups that interview current or past employees of the target company.
2. Creating a Data-Driven Culture = Smarter, More Efficient Decision-Making
Building a data-driven culture at your firm helps it plan more strategically, which improves the accuracy and outcomes of decision-making by providing the ‘why’ behind what’s happening—or the driver behind various correlations and trends—versus only the ‘what.’
Without a holistic view, data sets are unable to (figuratively) speak to each other and firms are left without a 360 degree of view of data, which can result in decisions being made on gut instinct, rather than concrete numbers.
These sentiments ring especially true for PE and VC firms seeking to create portfolio value. Now, more than ever, they need to value and treat data as an asset to more accurately forecast change, pivot and innovate quickly, and create an outsized advantage to stay ahead in an increasingly competitive and unpredictable environment.
3. Data Drives Digital Transformation, Value Creation and Value Realization
Data in and of itself offers little to no value if it does not reveal anything. The value is not data alone; it is what is done with the data.
According to Gartner, “Data and analytics are the key accelerants of an organization’s digitization and transformation efforts. Yet today, fewer than 50% of documented corporate strategies mention data and analytics as fundamental components for delivering enterprise value.”
Simply stated, data is no longer just a tool to drive business decisions at PE and VC firms, it’s also the catalyst for driving digital transformation, value creation and value realization. The direct benefits that firms can realize from data analytics include maximized ROI, increased revenue, operational efficiencies, and a decrease in operational expenses.
For example, firms can start by using data to manage business performance, which has a direct impact on driving value and creating an understanding of where portfolio companies (and target companies) can reduce costs.
In addition, data helps firms realize value by:
Generating a 360° view of their portfolio companies (and targets), enabling more custom-tailored approaches to investments.
Increasing productivity through the efficiency of the existing value chain and support systems.
As noted above, data serves as a lever for greater revenue generation because data-savvy firms have a greater likelihood of surpassing revenue goals.
4. Using Data to Tell a Compelling Exit Story
At exit, firms can use data and analytics to support “investment lifecycle storytelling” by demonstrating the value created at a portfolio company; thus, allowing investors (and, potentially, others) to efficiently analyze the business throughout the entire process and the investment outcomes that are achieved.
Potential buyers of companies understandably ask lots of questions during a diligence process and those that are venture-funded looking to go public are highly scrutinized, as well. With a solid, data-driven approach in place, a firm’s portfolio companies may be able to provide information to buyers faster and easier—and even help to package the data they expect the buyer will need. This approach can help instill confidence, avoid surprises, and even likely move buyers toward making bids sooner.
For example, consider a software company in a firm’s portfolio that grew through acquisitions and only tracked basic information across its acquired and legacy business units. Disparate systems and disconnected data would make it difficult for management to demonstrate the value of the bolt-on acquisitions and how those acquisitions made real pull-through opportunities for the company. By integrating business data sets into a common platform, a firm can bring its portfolio company’s growth strategy and margin expansion to the fore with data that will support its trajectory. Such enhanced business intelligence can help a PE firm tell the story of a portfolio company’s strategy for potential bidders upon exit. Similarly, when properly harnessed and analyzed on a common platform, such data can help make the case for additional funding rounds for a VC-backed company.
Bridging the Gap
While some firms remain buoyed by legacy approaches and the notion that tenured, relationship-driven teams will always win the day, yesteryear’s experience alone will not win the best deals and generate the best returns in 2023.
In fact, it’s becoming increasingly difficult for firms to remain competitive if they don’t develop a well-honed approach to data and data analytics. Thankfully, data analysis and science usually yield a type of flywheel effect: the more data that is analyzed, the greater the opportunity to gain advantages in the investment lifecycle. The smartest firms realize that a data-driven culture and advanced analytics frameworks offers an edge in the market, using a combination of company-generated and alternative (third-party) data to drive decision-making and the returns that a majority of investors demand. In virtually any industry and at any stage, PE and VC firms can help unlock additional value with data-driven insights that the competition may have not spotted through just their years of experience alone.
Discover How Asset Class Can Help Your Team
Need help bridging the gap with your data challenges? Not only does Asset Class integrate with dozens of apps in your tech stack including Pitchbook Data, Preqin, Discovery Data, so data can be shared, but we can help you harness the power of your data for increased operational efficiencies and cost savings, while hastening your time to new deals and greater assets under management. Today, Asset Class platforms power hundreds of private capital funds around the world. Whether you’re a PE or VC firm, you can discover how our platforms help make the future of finance frictionless. Schedule a demo with one of our team members today.
Sources:
“The Data Gap in Private Equity,” S&P Global. https://www.spglobal.com/en/research-insights/articles/daily-update-november-3-2022
“Private Capital Investment Value Dips 29% in Q3, After Record-High Deal Activity,” Pensions & Investments. https://www.pionline.com/private-equity/private-capital-investment-value-dips-29-q3-after-record-high-deal-activity
“Three Reasons Why Private Equity Firms—and Their Portfolio Companies—Need a Data Analytics Strategy,” Performance Improvement Partners. https://www.pipartners.com/private-equity-data-analytics-strategy/
If you had to sum up the 2022 private capital landscape in one word, perhaps, that word could be “contradictions.”
The year began with a rather rosy outlook. Venture capital (VC) funds raised $151 billion in the first three quarters of 2022, exceeding any prior full-year fundraising, according to PitchBook Data, Inc. Today, however, both private equity (PE) and venture funds are sitting on a record amount of dry power, as funding contracted this quarter. Another paradox: there is more talk than ever of firms funding more diverse companies and founders—namely, women and people of color—however, the numbers in this realm point in the opposite direction. Indeed, contradictions seem to abound this year.
What does appear to be true, though, is that many firms are using this year’s “messy middle”—a period of enhanced uncertainty—as an impetus to focus not only on right-sized valuations and selective funding, but also on the technologies they’ll employ for competitive advantage. A cornerstone of this effort is a heavy focus on bridging the data gap, so firms can maximize growth opportunities by harnessing the power of data analytics.
The following overview highlights how enabling a data-driven culture can make all the difference at PE and VC firms because now, more than ever, treating data as an asset allows them to more accurately forecast change, innovate quickly, and create advantages to stay ahead in increasingly competitive private markets.
Setting the Stage
Now, let’s be frank—gathering and analyzing private market data is not easy. But, in today’s market, having a data analytics strategy in place is no longer a “nice to have.” It’s absolutely required to drive business operations and digital transformation at private capital firms.
The difficulty in gathering and analyzing private market data is inherent in the way private companies are structured. In contrast, public companies are required to provide data on many aspects of their business—balance sheets, income and cash flow statements, and more—which is then used by financial planners, risk managers and investors. Some economists believe that when all market participants have equal access to company data, equity and debt are priced accurately. However, this also limits the opportunity to use data asymmetry to generate alpha or “beat the market,” since (presumably) everyone has potential access to the same data points.
Yet, part of the ever-growing lure of private company investments is that data—when analyzed tenaciously and correctly—can yield significant competitive advantages for the firms that execute such work. Every firm has an incentive to maintain its data advantage. The most successful firms do this by amassing as much data as possible about private companies and other participants in private markets, while sharing as little data as possible (publicly) about their own portfolio investments.
Collecting data in an expansive world of over 10 million private companies is quite daunting for PE and VC firms. They have some resources at their fingertips—i.e. PitchBook, S&P Global Marketing Intelligence and PE Hub—to name just a few. But, according to a recent Coalition Greenwich study, 62% of investors in the U.S. and Europe said they have difficulty examining the details of the private companies in their portfolios with the data they have.
To overcome this hurdle, some firms have prioritized data analytics, realizing that its crucial to the future of their business. PE and VC firms and their investors have tried to improve the sourcing, standardizing and visualizing of private company data. However, challenges remain in applying actionable insights derived from that data.
Reasons Why a Data Analytics Strategy is Necessary
Here is a non-exhaustive list that highlights why a data analytics strategy is necessary and how it can be applied:
1. Using Data Pre-Deal, In Due Diligence and Deal Origination
Arguably, the biggest opportunity for applying data analytics arises pre-deal, as firms source opportunities, while further conducting necessary due diligence. To date, many firms have not integrated data analytics into deal origination and very few are using data to automate deal sourcing and due diligence, even though more and more managers realize that the use of data in deal origination can be a competitive advantage.
PE and VC firms should apply data analysis in both the pre-deal and due diligence phases to inform key decisions. In doing so, they can confirm or challenge target company assertions, refine valuation model inputs, and identify both commercial opportunities and risks.
However, this is just the tip of the iceberg. Knowing how competitive the market is (and how quickly it can change), firms are now looking beyond just available company data and are increasingly turning to additional data sources—including those offered by research firms, independent advisors, and analytics experts—to refine their investment theses. The data these third parties offer up can help better hone a target company’s existing data pool, since not all target companies maintain the same quality and depth of data.
For example, a PE buyer may leverage third-party online sales data to better assess category trends, pricing and the impact of promotion spend on top-line growth. The application of such additional data can help validate assumptions about a company and its competition before pursuing an asset in the market. A buyer may further extract data points via a research firm by running a series of focus groups that interview current or past employees of the target company.
2. Creating a Data-Driven Culture = Smarter, More Efficient Decision-Making
Building a data-driven culture at your firm helps it plan more strategically, which improves the accuracy and outcomes of decision-making by providing the ‘why’ behind what’s happening—or the driver behind various correlations and trends—versus only the ‘what.’
Without a holistic view, data sets are unable to (figuratively) speak to each other and firms are left without a 360 degree of view of data, which can result in decisions being made on gut instinct, rather than concrete numbers.
These sentiments ring especially true for PE and VC firms seeking to create portfolio value. Now, more than ever, they need to value and treat data as an asset to more accurately forecast change, pivot and innovate quickly, and create an outsized advantage to stay ahead in an increasingly competitive and unpredictable environment.
3. Data Drives Digital Transformation, Value Creation and Value Realization
Data in and of itself offers little to no value if it does not reveal anything. The value is not data alone; it is what is done with the data.
According to Gartner, “Data and analytics are the key accelerants of an organization’s digitization and transformation efforts. Yet today, fewer than 50% of documented corporate strategies mention data and analytics as fundamental components for delivering enterprise value.”
Simply stated, data is no longer just a tool to drive business decisions at PE and VC firms, it’s also the catalyst for driving digital transformation, value creation and value realization. The direct benefits that firms can realize from data analytics include maximized ROI, increased revenue, operational efficiencies, and a decrease in operational expenses.
For example, firms can start by using data to manage business performance, which has a direct impact on driving value and creating an understanding of where portfolio companies (and target companies) can reduce costs.
In addition, data helps firms realize value by:
Generating a 360° view of their portfolio companies (and targets), enabling more custom-tailored approaches to investments.
Increasing productivity through the efficiency of the existing value chain and support systems.
As noted above, data serves as a lever for greater revenue generation because data-savvy firms have a greater likelihood of surpassing revenue goals.
4. Using Data to Tell a Compelling Exit Story
At exit, firms can use data and analytics to support “investment lifecycle storytelling” by demonstrating the value created at a portfolio company; thus, allowing investors (and, potentially, others) to efficiently analyze the business throughout the entire process and the investment outcomes that are achieved.
Potential buyers of companies understandably ask lots of questions during a diligence process and those that are venture-funded looking to go public are highly scrutinized, as well. With a solid, data-driven approach in place, a firm’s portfolio companies may be able to provide information to buyers faster and easier—and even help to package the data they expect the buyer will need. This approach can help instill confidence, avoid surprises, and even likely move buyers toward making bids sooner.
For example, consider a software company in a firm’s portfolio that grew through acquisitions and only tracked basic information across its acquired and legacy business units. Disparate systems and disconnected data would make it difficult for management to demonstrate the value of the bolt-on acquisitions and how those acquisitions made real pull-through opportunities for the company. By integrating business data sets into a common platform, a firm can bring its portfolio company’s growth strategy and margin expansion to the fore with data that will support its trajectory. Such enhanced business intelligence can help a PE firm tell the story of a portfolio company’s strategy for potential bidders upon exit. Similarly, when properly harnessed and analyzed on a common platform, such data can help make the case for additional funding rounds for a VC-backed company.
Bridging the Gap
While some firms remain buoyed by legacy approaches and the notion that tenured, relationship-driven teams will always win the day, yesteryear’s experience alone will not win the best deals and generate the best returns in 2023.
In fact, it’s becoming increasingly difficult for firms to remain competitive if they don’t develop a well-honed approach to data and data analytics. Thankfully, data analysis and science usually yield a type of flywheel effect: the more data that is analyzed, the greater the opportunity to gain advantages in the investment lifecycle. The smartest firms realize that a data-driven culture and advanced analytics frameworks offers an edge in the market, using a combination of company-generated and alternative (third-party) data to drive decision-making and the returns that a majority of investors demand. In virtually any industry and at any stage, PE and VC firms can help unlock additional value with data-driven insights that the competition may have not spotted through just their years of experience alone.
Discover How Asset Class Can Help Your Team
Need help bridging the gap with your data challenges? Not only does Asset Class integrate with dozens of apps in your tech stack including Pitchbook Data, Preqin, Discovery Data, so data can be shared, but we can help you harness the power of your data for increased operational efficiencies and cost savings, while hastening your time to new deals and greater assets under management. Today, Asset Class platforms power hundreds of private capital funds around the world. Whether you’re a PE or VC firm, you can discover how our platforms help make the future of finance frictionless. Schedule a demo with one of our team members today.
Sources:
“The Data Gap in Private Equity,” S&P Global. https://www.spglobal.com/en/research-insights/articles/daily-update-november-3-2022
“Private Capital Investment Value Dips 29% in Q3, After Record-High Deal Activity,” Pensions & Investments. https://www.pionline.com/private-equity/private-capital-investment-value-dips-29-q3-after-record-high-deal-activity
“Three Reasons Why Private Equity Firms—and Their Portfolio Companies—Need a Data Analytics Strategy,” Performance Improvement Partners. https://www.pipartners.com/private-equity-data-analytics-strategy/
If you had to sum up the 2022 private capital landscape in one word, perhaps, that word could be “contradictions.”
The year began with a rather rosy outlook. Venture capital (VC) funds raised $151 billion in the first three quarters of 2022, exceeding any prior full-year fundraising, according to PitchBook Data, Inc. Today, however, both private equity (PE) and venture funds are sitting on a record amount of dry power, as funding contracted this quarter. Another paradox: there is more talk than ever of firms funding more diverse companies and founders—namely, women and people of color—however, the numbers in this realm point in the opposite direction. Indeed, contradictions seem to abound this year.
What does appear to be true, though, is that many firms are using this year’s “messy middle”—a period of enhanced uncertainty—as an impetus to focus not only on right-sized valuations and selective funding, but also on the technologies they’ll employ for competitive advantage. A cornerstone of this effort is a heavy focus on bridging the data gap, so firms can maximize growth opportunities by harnessing the power of data analytics.
The following overview highlights how enabling a data-driven culture can make all the difference at PE and VC firms because now, more than ever, treating data as an asset allows them to more accurately forecast change, innovate quickly, and create advantages to stay ahead in increasingly competitive private markets.
Setting the Stage
Now, let’s be frank—gathering and analyzing private market data is not easy. But, in today’s market, having a data analytics strategy in place is no longer a “nice to have.” It’s absolutely required to drive business operations and digital transformation at private capital firms.
The difficulty in gathering and analyzing private market data is inherent in the way private companies are structured. In contrast, public companies are required to provide data on many aspects of their business—balance sheets, income and cash flow statements, and more—which is then used by financial planners, risk managers and investors. Some economists believe that when all market participants have equal access to company data, equity and debt are priced accurately. However, this also limits the opportunity to use data asymmetry to generate alpha or “beat the market,” since (presumably) everyone has potential access to the same data points.
Yet, part of the ever-growing lure of private company investments is that data—when analyzed tenaciously and correctly—can yield significant competitive advantages for the firms that execute such work. Every firm has an incentive to maintain its data advantage. The most successful firms do this by amassing as much data as possible about private companies and other participants in private markets, while sharing as little data as possible (publicly) about their own portfolio investments.
Collecting data in an expansive world of over 10 million private companies is quite daunting for PE and VC firms. They have some resources at their fingertips—i.e. PitchBook, S&P Global Marketing Intelligence and PE Hub—to name just a few. But, according to a recent Coalition Greenwich study, 62% of investors in the U.S. and Europe said they have difficulty examining the details of the private companies in their portfolios with the data they have.
To overcome this hurdle, some firms have prioritized data analytics, realizing that its crucial to the future of their business. PE and VC firms and their investors have tried to improve the sourcing, standardizing and visualizing of private company data. However, challenges remain in applying actionable insights derived from that data.
Reasons Why a Data Analytics Strategy is Necessary
Here is a non-exhaustive list that highlights why a data analytics strategy is necessary and how it can be applied:
1. Using Data Pre-Deal, In Due Diligence and Deal Origination
Arguably, the biggest opportunity for applying data analytics arises pre-deal, as firms source opportunities, while further conducting necessary due diligence. To date, many firms have not integrated data analytics into deal origination and very few are using data to automate deal sourcing and due diligence, even though more and more managers realize that the use of data in deal origination can be a competitive advantage.
PE and VC firms should apply data analysis in both the pre-deal and due diligence phases to inform key decisions. In doing so, they can confirm or challenge target company assertions, refine valuation model inputs, and identify both commercial opportunities and risks.
However, this is just the tip of the iceberg. Knowing how competitive the market is (and how quickly it can change), firms are now looking beyond just available company data and are increasingly turning to additional data sources—including those offered by research firms, independent advisors, and analytics experts—to refine their investment theses. The data these third parties offer up can help better hone a target company’s existing data pool, since not all target companies maintain the same quality and depth of data.
For example, a PE buyer may leverage third-party online sales data to better assess category trends, pricing and the impact of promotion spend on top-line growth. The application of such additional data can help validate assumptions about a company and its competition before pursuing an asset in the market. A buyer may further extract data points via a research firm by running a series of focus groups that interview current or past employees of the target company.
2. Creating a Data-Driven Culture = Smarter, More Efficient Decision-Making
Building a data-driven culture at your firm helps it plan more strategically, which improves the accuracy and outcomes of decision-making by providing the ‘why’ behind what’s happening—or the driver behind various correlations and trends—versus only the ‘what.’
Without a holistic view, data sets are unable to (figuratively) speak to each other and firms are left without a 360 degree of view of data, which can result in decisions being made on gut instinct, rather than concrete numbers.
These sentiments ring especially true for PE and VC firms seeking to create portfolio value. Now, more than ever, they need to value and treat data as an asset to more accurately forecast change, pivot and innovate quickly, and create an outsized advantage to stay ahead in an increasingly competitive and unpredictable environment.
3. Data Drives Digital Transformation, Value Creation and Value Realization
Data in and of itself offers little to no value if it does not reveal anything. The value is not data alone; it is what is done with the data.
According to Gartner, “Data and analytics are the key accelerants of an organization’s digitization and transformation efforts. Yet today, fewer than 50% of documented corporate strategies mention data and analytics as fundamental components for delivering enterprise value.”
Simply stated, data is no longer just a tool to drive business decisions at PE and VC firms, it’s also the catalyst for driving digital transformation, value creation and value realization. The direct benefits that firms can realize from data analytics include maximized ROI, increased revenue, operational efficiencies, and a decrease in operational expenses.
For example, firms can start by using data to manage business performance, which has a direct impact on driving value and creating an understanding of where portfolio companies (and target companies) can reduce costs.
In addition, data helps firms realize value by:
Generating a 360° view of their portfolio companies (and targets), enabling more custom-tailored approaches to investments.
Increasing productivity through the efficiency of the existing value chain and support systems.
As noted above, data serves as a lever for greater revenue generation because data-savvy firms have a greater likelihood of surpassing revenue goals.
4. Using Data to Tell a Compelling Exit Story
At exit, firms can use data and analytics to support “investment lifecycle storytelling” by demonstrating the value created at a portfolio company; thus, allowing investors (and, potentially, others) to efficiently analyze the business throughout the entire process and the investment outcomes that are achieved.
Potential buyers of companies understandably ask lots of questions during a diligence process and those that are venture-funded looking to go public are highly scrutinized, as well. With a solid, data-driven approach in place, a firm’s portfolio companies may be able to provide information to buyers faster and easier—and even help to package the data they expect the buyer will need. This approach can help instill confidence, avoid surprises, and even likely move buyers toward making bids sooner.
For example, consider a software company in a firm’s portfolio that grew through acquisitions and only tracked basic information across its acquired and legacy business units. Disparate systems and disconnected data would make it difficult for management to demonstrate the value of the bolt-on acquisitions and how those acquisitions made real pull-through opportunities for the company. By integrating business data sets into a common platform, a firm can bring its portfolio company’s growth strategy and margin expansion to the fore with data that will support its trajectory. Such enhanced business intelligence can help a PE firm tell the story of a portfolio company’s strategy for potential bidders upon exit. Similarly, when properly harnessed and analyzed on a common platform, such data can help make the case for additional funding rounds for a VC-backed company.
Bridging the Gap
While some firms remain buoyed by legacy approaches and the notion that tenured, relationship-driven teams will always win the day, yesteryear’s experience alone will not win the best deals and generate the best returns in 2023.
In fact, it’s becoming increasingly difficult for firms to remain competitive if they don’t develop a well-honed approach to data and data analytics. Thankfully, data analysis and science usually yield a type of flywheel effect: the more data that is analyzed, the greater the opportunity to gain advantages in the investment lifecycle. The smartest firms realize that a data-driven culture and advanced analytics frameworks offers an edge in the market, using a combination of company-generated and alternative (third-party) data to drive decision-making and the returns that a majority of investors demand. In virtually any industry and at any stage, PE and VC firms can help unlock additional value with data-driven insights that the competition may have not spotted through just their years of experience alone.
Discover How Asset Class Can Help Your Team
Need help bridging the gap with your data challenges? Not only does Asset Class integrate with dozens of apps in your tech stack including Pitchbook Data, Preqin, Discovery Data, so data can be shared, but we can help you harness the power of your data for increased operational efficiencies and cost savings, while hastening your time to new deals and greater assets under management. Today, Asset Class platforms power hundreds of private capital funds around the world. Whether you’re a PE or VC firm, you can discover how our platforms help make the future of finance frictionless. Schedule a demo with one of our team members today.
Sources:
“The Data Gap in Private Equity,” S&P Global. https://www.spglobal.com/en/research-insights/articles/daily-update-november-3-2022
“Private Capital Investment Value Dips 29% in Q3, After Record-High Deal Activity,” Pensions & Investments. https://www.pionline.com/private-equity/private-capital-investment-value-dips-29-q3-after-record-high-deal-activity
“Three Reasons Why Private Equity Firms—and Their Portfolio Companies—Need a Data Analytics Strategy,” Performance Improvement Partners. https://www.pipartners.com/private-equity-data-analytics-strategy/
If you had to sum up the 2022 private capital landscape in one word, perhaps, that word could be “contradictions.”
The year began with a rather rosy outlook. Venture capital (VC) funds raised $151 billion in the first three quarters of 2022, exceeding any prior full-year fundraising, according to PitchBook Data, Inc. Today, however, both private equity (PE) and venture funds are sitting on a record amount of dry power, as funding contracted this quarter. Another paradox: there is more talk than ever of firms funding more diverse companies and founders—namely, women and people of color—however, the numbers in this realm point in the opposite direction. Indeed, contradictions seem to abound this year.
What does appear to be true, though, is that many firms are using this year’s “messy middle”—a period of enhanced uncertainty—as an impetus to focus not only on right-sized valuations and selective funding, but also on the technologies they’ll employ for competitive advantage. A cornerstone of this effort is a heavy focus on bridging the data gap, so firms can maximize growth opportunities by harnessing the power of data analytics.
The following overview highlights how enabling a data-driven culture can make all the difference at PE and VC firms because now, more than ever, treating data as an asset allows them to more accurately forecast change, innovate quickly, and create advantages to stay ahead in increasingly competitive private markets.
Setting the Stage
Now, let’s be frank—gathering and analyzing private market data is not easy. But, in today’s market, having a data analytics strategy in place is no longer a “nice to have.” It’s absolutely required to drive business operations and digital transformation at private capital firms.
The difficulty in gathering and analyzing private market data is inherent in the way private companies are structured. In contrast, public companies are required to provide data on many aspects of their business—balance sheets, income and cash flow statements, and more—which is then used by financial planners, risk managers and investors. Some economists believe that when all market participants have equal access to company data, equity and debt are priced accurately. However, this also limits the opportunity to use data asymmetry to generate alpha or “beat the market,” since (presumably) everyone has potential access to the same data points.
Yet, part of the ever-growing lure of private company investments is that data—when analyzed tenaciously and correctly—can yield significant competitive advantages for the firms that execute such work. Every firm has an incentive to maintain its data advantage. The most successful firms do this by amassing as much data as possible about private companies and other participants in private markets, while sharing as little data as possible (publicly) about their own portfolio investments.
Collecting data in an expansive world of over 10 million private companies is quite daunting for PE and VC firms. They have some resources at their fingertips—i.e. PitchBook, S&P Global Marketing Intelligence and PE Hub—to name just a few. But, according to a recent Coalition Greenwich study, 62% of investors in the U.S. and Europe said they have difficulty examining the details of the private companies in their portfolios with the data they have.
To overcome this hurdle, some firms have prioritized data analytics, realizing that its crucial to the future of their business. PE and VC firms and their investors have tried to improve the sourcing, standardizing and visualizing of private company data. However, challenges remain in applying actionable insights derived from that data.
Reasons Why a Data Analytics Strategy is Necessary
Here is a non-exhaustive list that highlights why a data analytics strategy is necessary and how it can be applied:
1. Using Data Pre-Deal, In Due Diligence and Deal Origination
Arguably, the biggest opportunity for applying data analytics arises pre-deal, as firms source opportunities, while further conducting necessary due diligence. To date, many firms have not integrated data analytics into deal origination and very few are using data to automate deal sourcing and due diligence, even though more and more managers realize that the use of data in deal origination can be a competitive advantage.
PE and VC firms should apply data analysis in both the pre-deal and due diligence phases to inform key decisions. In doing so, they can confirm or challenge target company assertions, refine valuation model inputs, and identify both commercial opportunities and risks.
However, this is just the tip of the iceberg. Knowing how competitive the market is (and how quickly it can change), firms are now looking beyond just available company data and are increasingly turning to additional data sources—including those offered by research firms, independent advisors, and analytics experts—to refine their investment theses. The data these third parties offer up can help better hone a target company’s existing data pool, since not all target companies maintain the same quality and depth of data.
For example, a PE buyer may leverage third-party online sales data to better assess category trends, pricing and the impact of promotion spend on top-line growth. The application of such additional data can help validate assumptions about a company and its competition before pursuing an asset in the market. A buyer may further extract data points via a research firm by running a series of focus groups that interview current or past employees of the target company.
2. Creating a Data-Driven Culture = Smarter, More Efficient Decision-Making
Building a data-driven culture at your firm helps it plan more strategically, which improves the accuracy and outcomes of decision-making by providing the ‘why’ behind what’s happening—or the driver behind various correlations and trends—versus only the ‘what.’
Without a holistic view, data sets are unable to (figuratively) speak to each other and firms are left without a 360 degree of view of data, which can result in decisions being made on gut instinct, rather than concrete numbers.
These sentiments ring especially true for PE and VC firms seeking to create portfolio value. Now, more than ever, they need to value and treat data as an asset to more accurately forecast change, pivot and innovate quickly, and create an outsized advantage to stay ahead in an increasingly competitive and unpredictable environment.
3. Data Drives Digital Transformation, Value Creation and Value Realization
Data in and of itself offers little to no value if it does not reveal anything. The value is not data alone; it is what is done with the data.
According to Gartner, “Data and analytics are the key accelerants of an organization’s digitization and transformation efforts. Yet today, fewer than 50% of documented corporate strategies mention data and analytics as fundamental components for delivering enterprise value.”
Simply stated, data is no longer just a tool to drive business decisions at PE and VC firms, it’s also the catalyst for driving digital transformation, value creation and value realization. The direct benefits that firms can realize from data analytics include maximized ROI, increased revenue, operational efficiencies, and a decrease in operational expenses.
For example, firms can start by using data to manage business performance, which has a direct impact on driving value and creating an understanding of where portfolio companies (and target companies) can reduce costs.
In addition, data helps firms realize value by:
Generating a 360° view of their portfolio companies (and targets), enabling more custom-tailored approaches to investments.
Increasing productivity through the efficiency of the existing value chain and support systems.
As noted above, data serves as a lever for greater revenue generation because data-savvy firms have a greater likelihood of surpassing revenue goals.
4. Using Data to Tell a Compelling Exit Story
At exit, firms can use data and analytics to support “investment lifecycle storytelling” by demonstrating the value created at a portfolio company; thus, allowing investors (and, potentially, others) to efficiently analyze the business throughout the entire process and the investment outcomes that are achieved.
Potential buyers of companies understandably ask lots of questions during a diligence process and those that are venture-funded looking to go public are highly scrutinized, as well. With a solid, data-driven approach in place, a firm’s portfolio companies may be able to provide information to buyers faster and easier—and even help to package the data they expect the buyer will need. This approach can help instill confidence, avoid surprises, and even likely move buyers toward making bids sooner.
For example, consider a software company in a firm’s portfolio that grew through acquisitions and only tracked basic information across its acquired and legacy business units. Disparate systems and disconnected data would make it difficult for management to demonstrate the value of the bolt-on acquisitions and how those acquisitions made real pull-through opportunities for the company. By integrating business data sets into a common platform, a firm can bring its portfolio company’s growth strategy and margin expansion to the fore with data that will support its trajectory. Such enhanced business intelligence can help a PE firm tell the story of a portfolio company’s strategy for potential bidders upon exit. Similarly, when properly harnessed and analyzed on a common platform, such data can help make the case for additional funding rounds for a VC-backed company.
Bridging the Gap
While some firms remain buoyed by legacy approaches and the notion that tenured, relationship-driven teams will always win the day, yesteryear’s experience alone will not win the best deals and generate the best returns in 2023.
In fact, it’s becoming increasingly difficult for firms to remain competitive if they don’t develop a well-honed approach to data and data analytics. Thankfully, data analysis and science usually yield a type of flywheel effect: the more data that is analyzed, the greater the opportunity to gain advantages in the investment lifecycle. The smartest firms realize that a data-driven culture and advanced analytics frameworks offers an edge in the market, using a combination of company-generated and alternative (third-party) data to drive decision-making and the returns that a majority of investors demand. In virtually any industry and at any stage, PE and VC firms can help unlock additional value with data-driven insights that the competition may have not spotted through just their years of experience alone.
Discover How Asset Class Can Help Your Team
Need help bridging the gap with your data challenges? Not only does Asset Class integrate with dozens of apps in your tech stack including Pitchbook Data, Preqin, Discovery Data, so data can be shared, but we can help you harness the power of your data for increased operational efficiencies and cost savings, while hastening your time to new deals and greater assets under management. Today, Asset Class platforms power hundreds of private capital funds around the world. Whether you’re a PE or VC firm, you can discover how our platforms help make the future of finance frictionless. Schedule a demo with one of our team members today.
Sources:
“The Data Gap in Private Equity,” S&P Global. https://www.spglobal.com/en/research-insights/articles/daily-update-november-3-2022
“Private Capital Investment Value Dips 29% in Q3, After Record-High Deal Activity,” Pensions & Investments. https://www.pionline.com/private-equity/private-capital-investment-value-dips-29-q3-after-record-high-deal-activity
“Three Reasons Why Private Equity Firms—and Their Portfolio Companies—Need a Data Analytics Strategy,” Performance Improvement Partners. https://www.pipartners.com/private-equity-data-analytics-strategy/
Our Latest Articles

Private Capital and Alternatives Market in 2024: The 10 Major Themes that defined the year

Private Capital and Alternatives Market in 2024: The 10 Major Themes that defined the year

Private Capital and Alternatives Market in 2024: The 10 Major Themes that defined the year

Private Capital and Alternatives Market in 2024: The 10 Major Themes that defined the year

How the upcoming Trump Presidency could positively impact the Private Capital Markets

How the upcoming Trump Presidency could positively impact the Private Capital Markets

How the upcoming Trump Presidency could positively impact the Private Capital Markets

How the upcoming Trump Presidency could positively impact the Private Capital Markets

Investor Deal Flow Management with a CRM Platform

Investor Deal Flow Management with a CRM Platform

Investor Deal Flow Management with a CRM Platform

Investor Deal Flow Management with a CRM Platform
Our Modules
Our Modules
Our Modules
Our Modules