Data drives AI. AI drives Business: “The global economy has undergone a structural transformation where the centre of gravity of value has shifted from physical capital to intangible assets, specifically electronic data and information.”
Nevertheless, data assets do not appear on the balance sheet: “During this shift, existing accounting frameworks and national statistical systems haven’t been able to capture the true economic significance of information, treating it as an intermediate expense rather than a durable asset. This measurement gap has led to a substantial value gap in corporate balance sheets and a systematic underestimation of national wealth in the System of National Accounts (SNA).”
It’s time to make data values measurable: The Infonomics methodology categorizes data valuation into two distinct and complementary spheres: foundational metrics and financial metrics. Foundational metrics are utilised to assess the qualitative attributes and operational utility of data, providing a relative score that informs data governance and prioritisation. Financial metrics apply traditional economic valuation principles—cost, market and income—to estimate the monetary value of information assets for balance sheet considerations, mergers and acquisitions and insurance purposes.”
In this week’s Goodread, Rohan Light provides an overview of data valuation metrics:
