STATE OF PLAY
FINDINGS & INSIGHTS:
STRATEGIC DATA PRIORITIES OFFER BOTH RISKS AND REWARDS
9 minute read time
KEY FINDINGS
55% of all firms would prioritise risk management and compliance through their data strategy
60% of all survey respondents ranked the ability to monitor portfolios as one of the top three areas where data can be used to enhance organisational and investment performance
STATE OF PLAY
FINDINGS & INSIGHTS:
STRATEGIC DATA PRIORITIES OFFER BOTH RISKS AND REWARDS
9 minute read time
KEY FINDINGS
55% of all firms would prioritise risk management and compliance through their data strategy
60% of all survey respondents ranked the ability to monitor portfolios as one of the top three areas where data can be used to enhance organisational and investment performance
From improving operations to unearthing new deals, investment firms are creating data strategies designed with efficiency and accuracy in mind.
What is driving data strategies in investment firms? For most, it is a way to optimise operational processes.
“Measuring the success of our operations is critical,” says the partner in a US-based PE firm with an average target fund size exceeding €1 billion. “We cannot continue with operations unless we know the actual capabilities and introduce methods to increase efficiencies.”
The managing director of another PE firm in the US with an average target fund size of €500 million-€1 billion agrees: “Investment performance can be improved by focusing on operational efficiencies. There may be issues like lack of innovation or lack of emphasis on cash management. These issues are resolved when we adopt a data-driven approach.”
Data priorities across the board
Risk management and compliance is the area of fund management that is most widely prioritised, as highlighted by 55% of respondents with an established data strategy, with 29% singling this out as their top choice.
“Data can be used for improving compliance management,” says the managing director of a PE firm based in Germany with an average target fund size under €250 million. “This is essential because there are so many new regulations to consider, and the complexities of these regulations have increased. We need the support of data and technology to maintain compliance.”
Portfolio/project management is another popular choice, selected by 48% of respondents with an established data strategy as one of their top-three choices (with 21% citing this as their main priority). This is followed by back-office management and fund operations (43%) and deal due diligence (41%).
In some cases, respondents point out that more efficient portfolio/project management translates into faster deal processes.
As the managing director of a real estate investment firm based in Switzerland says, “Usually, due diligence takes up to six months when we use manual procedures, but a data-driven process is quicker and teams can move on to subsequent activities faster.”
Technology has huge potential to streamline and accelerate internal processes, particularly in areas linked to collaboration and due diligence. It is therefore not surprising that respondents are prioritising internal processes in terms of their data strategy.
“Some of the pressure for change is coming from investors,” says Ahmed Khamassi, chief digitalisation officer at Stirling Square Capital Partners. “In our current fund raise, one of the things we noticed is that operational due diligence is taking centre stage. Investors are interested in our processes, in cybersecurity, and how we use and share data. Interest is ballooning on the investor side and there is market pressure to move.”
On top of this, technology platforms for deal administration are a known quantity and readily available in the market. Moreover, they are supported by datasets over which respondents are likely to have control.
"In our current fund raise, one of the things we noticed is that operational due diligence is taking centre stage. Investors are interested in our processes, in cybersecurity, and how we use and share data. Interest is ballooning on the investor side and there is market pressure to move."
Ahmed Khamassi – Chief Digitalisation Officer, Stirling Square Capital Partners
What areas of fund management would fund managers prioritise through their data strategies (or would prioritise if they were to establish a strategy)?
SOURCE: Aztec Group & Acuris Report – Differentiation Through Data (Nov. 2022)
RISK MANAGEMENT & COMPLIANCE
PORTFOLIO / PROJECT MANAGEMENT
BACK OFFICE MANAGEMENT & FUND OPERATIONS
DEAL DUE DILIGENCE
Deal origination through data
The picture is more complex when it comes to data strategies around deal origination. This is a much tougher call, because technology in this arena is still evolving. It also involves acquiring new skills, plus the ability to get hold of and process new types of data.
These challenges could account for the somewhat lower levels of interest in strategic objectives linked to deal origination. For example, deal sourcing is cited by less than a third (31%) of respondents. The picture is similar when seeking to derive insights from traditional and alternative data (27%) or identifying potential market trends (22%).
Despite this, respondents using tech to support deal origination are clear about the benefits: “We can use predictive information to assess the quality of targets,” says the chief strategy officer of a multi-asset fund based in the US, with an average target fund size exceeding €1 billion. “Comparing the data extensively provides relevant information and we can assess which targets can provide the best investment performance.”
The value of data in sourcing deals can also depend on where a firm sits in the investment chain, as Ross Waide, finance and operations partner at venture capital (VC) firm Stride, explains: “One of the big things a VC firm needs to do is source investment deals. But when you think about where Stride is focused—on pre-seed, seed and early-stage investment—there isn’t much relevant or consistent data to go on.
“There are a lot of data sources and automated tools that exist already. You can aggregate and collect information relatively quickly from multiple data sources and we use this for targeted deal sourcing, investment information, market mapping and comparisons. It’s highly directional, relatively high-quality information that guides decision-making.
“You can get market information quite quickly but, ultimately, you have to piece a lot of things together to make an investment decision. Given the nature of early-stage investing, it’s difficult to be data driven in decision-making, you need to use data to guide intuition.”
"You can get market information quite quickly but, ultimately, you have to piece a lot of things together to make an investment decision. Given the nature of early stage investing, it’s difficult to be data driven in decision making, you need to use data to guide intuition."
Ross Waide – Finance and Operations Partner, Stride
The challenge: how could data improve deal-making?
The fact that most firms tend to prioritise internal processes over deal origination when it comes to their data strategies is mirrored by respondent views on how data can be used to enhance organisational and investment performance.
“One area where data is being applied in our organisation is back-office processes,” says Linus Lund, director – fund controller of Nordic Capital Advisors. “The focus is on sharing data effectively between source systems—like our accounting and fund operation systems—and getting data to the people who need it, in terms of controlling and reporting.
“We also use data in front office applications, including investor relations and dealmaking. We do a lot with it in our customer relationship management efforts, tracking relationships with both Nordic Capital’s investors and targets. In addition, we conduct internal tracking on the progress of projects, staffing and portfolio company work, particularly with regard to ESG.”
An interesting point here is that ESG data is increasingly used as a tool to actively improve the performance of portfolio companies during the holding period. In many cases, this goes beyond basic monitoring.
“We have three main use cases for ESG data,” explains Caroline Löfgren, chief sustainability officer at private equity firm Hg. “The first is your own public reporting. The second is providing data for LPs and being able to respond to the questionnaires that we receive from them. But the most important one is to improve our portfolio companies—this is the biggest part of my work.
“Once you get the data, you look at all the gaps and help them to prioritise. For example, portfolio companies need to have an anti-bribery and corruption policy. This is vital to us, so we need to ensure one is in place. There could be less critical things too: do you donate laptops to charities? Portfolio companies prioritise what they think is most important for the business to focus on during the year and then we support them with those changes. ESG data is at the heart of this.”
Data applications that rely on data already held by the organisation are prioritised over applications that rely on external data sources
SOURCE: Aztec Group & Acuris Report – Differentiation Through Data (Nov. 2022)
of all survey respondents ranked the ability to monitor portfolios as one of the top three areas where data can be used to enhance organisational and investment performance
of all survey respondents ranked identifying potential targets as one of the top three areas where data can be used to enhance organisational and investment performance
Can more data sources make a difference?
The ability to increase operational efficiencies and monitor portfolios are both ranked by almost 60% of respondents as one of the top-three areas where data can be used to enhance organisational and investment performance. The ability to monitor financial and operational data is most commonly ranked as the single most important (21%).
What these applications have in common is that they typically rely on data that is already held by the organisation or can be acquired from portfolio companies relatively easily. By contrast, applications that require access to external data sources are less likely to be prioritised. These include identifying potential targets (33%) and uncovering new potential revenue streams (31%).
External data has always played a fundamental role in target selection. The issue facing investment managers now is deciding whether to broaden their range of data sources, and whether to use new data tools to help them make sense of it all.
As the managing director of a US-based real estate firm with an average target fund size of €250 million-€500 million puts it: “Asset quality and management capabilities can be understood when data is used. Big data may be available, but we have to spend more time on sorting, preparing and processing data accurately.”
Christopher Conradi, chief digital officer of FSN Capital, adds that, handled well, data offers unique insights in potential deals that might not be extracted any other way:
“We have every company in our target geography in our database, and we have a few thousand data points per company: financial, LinkedIn, website data, Glassdoor data. We pull data from any source we can.
“Company data is valuable, but data about subsectors is even more valuable because it is one of the biggest predictors of a successful deal. We pick out subsector trends in terms of recruitment, factory building and product launches. That is very important to us.
“It starts with taxonomy. We have about 20 industries defined. That breaks down into about 200 sectors with a further 500 subsectors. That taxonomy is not great. To fix that, we’re downloading the websites of all the companies in our target geography—about two million. Then we do some heavy text analytics to auto-classify industries. When you do that, you identify clusters of companies and then you can start to see trends across those clusters.”
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