After years of exceptional performance, private equity firms are facing challenges in today's market with macroeconomic headwinds, high financing costs, an uncertain growth outlook, and increased competition. Data & AI-driven strategies have emerged as a critical factor for firms to innovate and differentiate themselves with. Many firms cannot reliably collect and integrate trusted data regularly from their portfolio companies and third parties because of limited infrastructure capabilities, data management process challenges, and limited data governance. Manual data collection and review processes are not scalable, and firms often lack executives accountable for data, governance, and analytics.
Underinvestment in areas like data, AI and analytics infrastructure, business metadata & data quality tooling, and data operating models further hinders effective data collection and usage. Leading firms are starting to collect various types of data to drive reporting and use cases, including portfolio company financial data, customer and supplier data, workforce data, ESG insights and other operational data. With modern data, analytics and AI capabilities, firms can unlock value throughout the deal lifecycle and support their investments. They can use insights to support fundraising, deal sourcing, due diligence processes, investment growth, and overall portfolio monitoring.
By aggregating relevant data of high quality, firms can improve their ability to identify opportunities and provide strategic and tactical operating actions to support their investments. This article from Deloitte United States provides trends, insights and tips for embarking on a data-driven journey, highlighting how private equity firms can dive in and create additional value across the investment lifecycle.
Contacts: |
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Manish Motiani |
Anthony V. Scalese |
Aditya Ganti |
Vinayak Viswanathan |