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The team discovered that international conglomerates must disclose financials for their Danish subsidiaries. This obscure data source allowed them to analyze the Wolt acquisition's performance, confirming market share gains in a way not visible in consolidated reports.
Scrutinize the KPIs a company chooses not to highlight. For instance, Lumine and Topicus eschew standard metrics like EBITDA and ARR, instead framing their performance around a custom "Free Cash Flow Available to Shareholders" metric. This reveals their deep focus on cash generation for M&A, not chasing growth narratives.
A fertile source for undervalued ideas is identifying powerful consumer franchises hidden within a parent company with a boring or unrelated corporate name. The market often overlooks the strength of the underlying brand (e.g., Titleist golf clubs owned by Acushnet) due to this name dissociation.
Monish Pabrai's successful Fiat investment reveals a powerful strategy: find hidden assets within a company. The market valued Fiat Chrysler as a single struggling automaker, but Pabrai saw that its Ferrari subsidiary was a gem being overlooked. By valuing Ferrari separately, he realized the core auto business was trading for almost nothing.
Official financial segments often reflect bureaucracy, not true business economics. By creating a 'Shadow P&L' through deductive analysis, investors can uncover massive hidden costs in non-core initiatives, as ValueAct did with Microsoft's hardware divisions.
To build a unique dataset without massive cost, target the aggregated, non-identifiable 'exhaust data' from software, payments, and telematics companies. These firms often undervalue this data, which they may have been deleting, and might provide it cheaply or exclusively.
The M&A market has shifted. Buyers no longer accept simple revenue aggregation. They now conduct deep diligence to disaggregate organic from inorganic growth, demanding proof of a sustainable growth engine beyond just making acquisitions.
When evaluating an acquisition, buyers weigh the financial profile and the clarity of the company's story. A compelling, data-backed narrative about future growth pathways can be more influential than raw numbers, as a lack of clarity introduces risk and makes it a "harder yes" for the acquirer.
The current M&A landscape is defined by a valuation disparity where smaller companies trade at a discount to larger ones. This creates a clear strategic incentive for large corporations to drive growth by acquiring smaller, more affordable competitors.
Standard metrics like revenue growth are misleading after an acquisition. Metropolis focused on a single variable: the gross profit uplift on a location-by-location basis after deploying their technology. This precisely measured the value created by their tech and proved the M&A thesis.
MDT deliberately avoids competing on acquiring novel, expensive datasets (informational edge). Instead, they focus on their analytical edge: applying sophisticated machine learning tools to long-history, high-quality standard datasets like financials and prices to find differentiated insights.