Private equity firms whose management teams focus on data and analytics–through building a data strategy, investing in cloud and analytics capabilities, and shifting to a strong data-enabled decision-making framework–will likely outperform competitors.
Private equity (PE) firms are dealing with unprecedented levels of geopolitical and macroeconomic pressures, as well as rising competition, inflation, market volatility, and other pressures. The tried-and-true PE playbook is insufficient to improve value for investors in the face of these challenging market circumstances, and PE companies run the risk of overpaying for new deals as their present portfolio underperforms.
Middle-market businesses looking to advance need strategic partners who can add operational expertise to the C-suite competencies and support long-term investments in operational transformation agendas. PE firms can gain an advantage in this dynamic market environment by utilising their network of operating partners, a wealth of information from their portfolio companies, and investments in operational transformation.
Today's pace of change necessitates an agile attitude for businesses to take advantage of the often-changing market dislocations. PE firms cannot rely on a 3-5 year long-term plan for their investments. PE leaders should use data, analytics, and cloud capabilities to move swiftly, much to how the Internet of Things allowed manufacturers to adjust manufacturing and production facilities in real time. Decision horizons should be reduced from years and months to days and weeks.
Technology limitations were cited by portfolio companies as their biggest difficulty in responding to private equity needs. It's time to quit using data collection and reporting techniques that are manual and ad hoc. PE firms have access to enormous amounts of data, but they frequently don't use or exploit it.
PE portfolio businesses frequently lack (or have rudimentary) data strategies. Today's management teams frequently base their judgements on data that is dispersed, incompletely integrated, and uncleansed. Leading management teams are essential for operational excellence, however, to support a more active value-creation agenda, PE firms and their operating partners are increasingly required to offer strategic advice to the C-suite of the portfolio companies.
Private equity businesses with management teams that prioritise data and analytics are likely to do better. This includes developing a data strategy, investing in cloud and analytics capabilities, and switching to a solid data-enabled decision-making framework. Instead of needing to wait for the financial outcomes to materialise over several months, a robust data strategy enables management and operating partners to assess the effects of strategic moves in close to real-time. Companies can learn more about how preferences like price impact sales and profits from various customers and distribution channels.
PE firms can set up a purposeful, seamless flow of information from portfolio companies that can be consistently mined to advise their management teams, screen new opportunities, and increase returns by leveraging data as their hidden weapon.
To oversee portfolio firms, the private equity sector still largely relies on static information supplied via email and spreadsheets. 54 per cent of responders from portfolio companies mention that they use email attachments to gather information and fulfil requests. 36 per cent respond via email with text-only messages. Digitisation initiatives can quicken value development plans, establish themselves as a significant competitive advantage, and increase the exit value of portfolio companies.
Data collection and use at portfolio companies and across the entire portfolio should not be limited to the infrastructure created by private equity firms. Private equity leaders should look to develop automated, predictive analytics employing artificial intelligence tools that will move conventional dashboards into the future to grasp opportunities in real-time. Dashboards are useful for researching and comprehending businesses. AI, on the other hand, advances these procedures to draw attention to problems and transform data into useful insights. This can help PE firms identify any weak points in their portfolio and fix them immediately.
Real-time hypothesis testing will be possible for PE firms and the portfolio companies they manage with the correct data infrastructure and predictive analytics technologies. Operators and investors should proactively make data-enabled decisions to inform their pricing, channel, and other operational choices to create value on the offence rather than the defence. Investment performance will no longer unfold with explanations of what occurred driving future decisions.
Obtaining data for advanced analytics used to be challenging due to the various, out-of-date systems that were not interconnected. There was no self-evident return on the expenditure required to build the large-scale technologies required to have a single data collection. Adding a new cloud layer has been shown to help save costs, streamline design, and unify operational and financial data as cloud solutions have matured.
PE firms will be able to drive tremendous uniformity and develop their own data management and analytics strategy across their whole portfolio once portfolio companies can harness their data. Businesses that take advantage of the plethora of information at their disposal–on the industries, regions, personnel, end users, and suppliers of their portfolio firms–and can achieve a competitive advantage. PE firms will be able to assess potential target companies quickly, possibly even before they hit the market, and will be better equipped to advise their portfolio companies and provide the C-suite and operational partners with the knowledge and resources they need to build value.
