The use of alternative data (alt-data) by hedge funds and private equity (PE) firms has grown exponentially in recent years, revolutionizing investment decisions. Historically, alternative data was often seen as peripheral or experimental; today, it is considered a critical tool for gaining competitive insights, uncovering hidden trends, and making more informed financial decisions.
The rising prominence of alternative data underscores a broader transformation in finance. Technological advancements and the intricate dynamics of global markets—such as the increasing demand for real-time analytics in response to market volatility and geopolitical shifts—drive investment strategies toward more sophisticated, data-driven insights.
What is alternative data? Alternative data refers to data not traditionally used in financial analysis, such as company filings, earnings reports, or stock prices. Instead, it comes from alternative data sources like social media activity, satellite imagery, web scraping, and workforce analytics.
In its early stages, alternative data sets were largely experimental and involved limited data points. For example, satellite images of retail parking lots were used to predict quarterly sales figures for major chains. At the time, such data was considered groundbreaking but also niche, only accessible to large institutions with the technological resources to process and analyze it.
In the 2010s, alternative data started gaining more attention, primarily in hedge funds. Early adopters saw alternative data for investment decisions as a way to generate alpha—the excess returns on investments relative to the market. Major funds followed. However, many financial institutions were still cautious, as questions about this data's reliability, cost, and effectiveness persisted.
Fast forward to today, and alternative data has gone mainstream. There are alternative data conferences and a vast array of data suppliers. What was once seen as fringe is now a core part of the toolkit for hedge funds and private equity firms. The market for alternative data has surged, with the global alternative data market projected to reach $135.8 billion by 2030, growing at a compound annual growth rate (CAGR) of almost 50%.
Several key trends have driven this boom:
Today, alternative data is much broader and more sophisticated than the satellite imagery and alternative data web scraping techniques of the past. It includes a variety of alternative data sources such as:
For hedge funds, these alternative data sources help to build predictive models that anticipate market movements. Alternative data analysis allows them to identify patterns and correlations that traditional models might miss, offering a potential edge over competitors. For example, job postings can signal a company’s expansion plans, while reviews on platforms like Glassdoor can provide insights into employee satisfaction and potential retention issues.
Private equity firms have found significant value in using alternative data for due diligence. Aura’s workforce analytics platform has proven crucial in identifying key operational efficiencies within target companies. A recent client shared that leveraging Aura’s headcount benchmarking and labor analysis capabilities reduced the time required for operational due diligence by over 50%, enhancing the accuracy of deal assessments.
PE firms use alternative data for finance to evaluate potential acquisition targets, analyze their portfolio companies, benchmark talent, and assess organizational health. Traditional due diligence processes—relying on financial reports, interviews, and audits—are augmented with real-time insights from alternative data sources. This allows firms to make quicker, more informed decisions and spot risks earlier.
The role of alternative data in financial decision-making is only going to grow. As the volume of data increases, so too will the sophistication of the tools used to analyze it. Hedge funds and private equity firms that once relied solely on traditional financial metrics will continue to integrate alternative data for investment to enhance their strategies, improve returns, and manage risk more effectively.
Looking forward, firms will need to not only gather data but also interpret it correctly. With so much information available, distinguishing signal from noise is increasingly critical. Inaccurate data interpretation can lead to flawed conclusions and costly investment mistakes. This makes the role of AI for alternative data and machine learning even more essential, as these technologies can help to automate the process of identifying the most meaningful data points.
Alternative data represents the next frontier in investment analysis. Hedge funds and private equity firms that embrace this shift will be better positioned to navigate increasingly complex and competitive markets. In a world where every edge counts, the ability to derive actionable insights from alternative data could be the difference between success and failure.
As alternative data continues to evolve, it fundamentally transforms the concept of an information advantage in finance. No longer just a supplementary tool, it has become a cornerstone for hedge funds, private equity firms, and consulting firms aiming to make precise, data-driven decisions. With platforms like Aura, investors can now access real-time, granular insights on company performance, workforce dynamics, and market trends.
From tracking headcount shifts and skill gaps to gauging employee sentiment through sophisticated dashboards, alternative data provides a window into a company's true operational health, well before traditional metrics can signal change. The ability to rapidly interpret these data points allows firms to stay agile, capitalize on emerging opportunities, and proactively manage risks.
As the financial landscape grows increasingly complex and competitive, those who seamlessly integrate alternative data into their strategies will set themselves apart—gaining a lasting edge in making informed, strategic decisions that drive sustained growth and value creation.