The market context
The production of commodities (fuels, metals, chemicals, construction materials, agriculture) accounts for roughly 20% of global greenhouse gas (GHG) emissions, along with a number of other environmental, social and governance (ESG)-related impacts such as biodiversity, water, and workers’ rights. Although an individual unit of any given commodity might have a significantly different intrinsic or “embedded” ESG profile depending on how it is produced, today’s commodity markets treat commodities equally regardless of their origin or environmental footprints.
Even with increased environmental monitoring and new data technologies, ESG data on commodities are typically siloed in disconnected systems and not flowing to the broader commodity market complex where $US Trillions are transacted. This resulting “ESG information gap” leads to an inability to productize or price ESG factors in commodity markets and ultimately market failure, with two major implications. First, commodity buyers do not have data to differentiate commodities and inform sustainable purchasing choices – despite the growing impetus from shareholders, consumers, and regulators. In turn, future price signals for traded commodities do not account for ESG factors to include environmental impact and related labor rights of the worker affiliated with the generation of said commodity production/harvest. As a result, investing in innovative technologies and more sustainable production is not rewarded.
The role of a description framework
Building on proven, digital migrations in other economic sectors, the Commodity Genome ProjectTM (CGP) defines an open source description framework that helps close this ESG information gap. The framework describes the ESG profile for any given unit of commodity production. It is available license free and extensible.
In the case of CGP, the description framework characterises and organizes the various properties of a commodity (e.g., “point of origin”, “specific gravity”). It defines the relationships between such properties, and provides the basic, interoperable building block of a networked data infrastructure for commodity markets. It acts as a common language for describing both the physical properties of a commodity and also its ESG profile. The language can be used to establish industry benchmarks and define sustainable production practices, empowering market participants to share, register, transact, and ultimately retire ESG-oriented information, certifications, and other derived assets.
Building on principles from the music industry
The CGP draws from the same principles that made the Music Genome the spark that transformed business models in the music industry. In the example below a description framework (e.g., duration, recording artist, title) provides a common structure for detailing a musical asset’s various properties (e.g., 9 mins 22 seconds; Miles Davis; So What).
Note the description framework (e.g., duration, recording artist, title) does not assert what constitutes good or bad properties. It does not assert good jazz must have a specific “duration”, nor assert that a great title should contain a certain number of syllables.
This standardized information about music (metadata, “emotive” attributes, etc.) combined with the actual music in a single format, enabled a standardized classification system and a reference architecture for all future search and discovery mechanisms and eventually enabled greater scale in tagging of assets via machine learning and AI.
Together with technology improvements in recording, data capture and storage, and computing power, these advances led to the evolution of the music business away from transaction and asset ownership to digital stores (e.g., iTunes), subscription and data driven revenue models such as Pandora and EchoNest (Spotify), as well as new services via mobile devices, live event integration, and a slew of other innovations.