Written by PEER DATA
The Modern Ledger's Ancient Roots
Early traders counted bushels of grain to build markets. Today, we count dollars spent on data but miss the rows that could build one.
In the annals of commerce, the story of grain trading offers a compelling vignette. Before formalized exchanges, farmers and merchants haggled over haphazard measures of bushels, leading to disputes, inefficiencies, and limited trade. It was only through the establishment of standardized units, precise bushels graded by quality, with infrastructure for aggregation, storage, and distribution, that grain evolved from a local staple into a global commodity. This precision unlocked vast markets, allowing value to flow from fields to far-flung buyers, rewarding producers based on verifiable contributions.
At PEER DATA, we see echoes of this ingenuity in today's data challenges. Just as those early bushels represented granular units of value, modern data "rows", records with traceable lineage showing how they evolve and connect across systems, point-in-time views revealing where they reside horizontally in a firm's objects, fuel business empires. Yet, our ledgers tally only aggregate costs, overlooking these foundational elements. This oversight fosters misaligned incentives, where data quality erodes and connectivity falters, much like unstandardized trading once stifled growth. This article delves into the roots of commodity markets, their lessons for data valuation, and why rediscovering granular tracking could avert a race to the bottom in our digital economy.
Commodity Markets: Standardizing Units to Unlock Scale
Commodity markets didn't emerge fully formed; they evolved from fragmented, trust-deficient systems into engines of global trade through rigorous standardization. Take early oil trading: before barrels were uniformly defined and graded, deals were local and prone to inconsistencies, limiting scale and fair value attribution. The introduction of standards, such as measurement protocols, classification by type (e.g., crude vs. refined), and infrastructure like pipelines, refineries, and exchanges, transformed oil into a tradable asset. Similarly, soybeans, gasoline, and orange juice markets scaled only after establishing clear units, quality grades, and mechanisms to collect from disparate sources, process centrally, and match buyers with sellers. This not only enabled efficient pricing but also ensured value flowed to where it was created, rewarding farmers for high-grade crops or refiners for quality enhancements.
A parallel can be drawn to the music royalty ecosystem, where centralized registries track songs by writers, performers, and usage, with mechanisms to collect streams, process payouts, and distribute royalties. This clarity allows value to accrue where it's added, whether in composition or performance, fostering investment in quality without overwhelming the creative process.
Applied to data, these examples illuminate a path forward. Like commodity units, data "rows" encompass not just counts but lineage (tracing evolution and connections between objects) and states or inventories (point-in-time snapshots of where data exists across a firm's ecosystem). In pre-standard commodity eras, the absence of such granularity bred inefficiencies; today, untracked data rows lead to similar pitfalls. Without visibility into how data travels or resides horizontally, corrections fail to propagate, silos persist, and investments in enhancements, like machine learning readiness or archival integrity, lack clear ROI justification.
As illustrated in PEER DATA's explorations of data as an asset, this struggle stems from data's intangibility and dynamic nature, much like early commodities before standardization. Traditional models comprehend tangible goods but falter with data's varying quality and fluidity. Consider these parallels:
- Granular Measurement: Commodity traders tracked units to resolve disputes; untracked data rows today invite quality degradation, as value additions go unrecognized.
- Trade Enablement: Standardized infrastructure spurred commerce; modern data ledgers expense inputs without linking to outputs, stifling monetization.
- Market Scale: Precise classification built interconnected systems; ignoring data's lineage and states hinders innovation, echoing early trading's local constraints.
This historical precision underscores our modern blind spot: data's role in business survival remains unquantified, perpetuating a cycle where incentives misalign and potential empires remain unbuilt.
The Modern Disconnect: Dollars Over Rows
In contemporary accounting, ledgers excel at aggregating costs like subscription fees and cloud storage bills, but fall short on the granular "rows" that drive value. This focus on dollars spent ignores data's existential contributions: records that enable revenue through analytics, reduce costs via automation, or serve as collateral in financing. The result? Ghost Counters, those invisible overseers of data, reign unchecked, fostering misaligned incentives where quality slips and connectivity weakens.
Without tracking lineage (how data evolves and links objects) or point-in-time states (horizontal views of data's firm-wide data inventories), downstream impacts compound. Unknown dependencies mean fixes stay isolated, underinvestment in mapping becomes the norm, and data deteriorates for critical uses like AI training. This vicious cycle mirrors early commodity markets before standards: value creation is obscured, rewarding aggregate spend over precise contributions.
The EDM Council's 2023 DataCo point of view offers a conceptual lens here, suggesting innovative structures like independent subsidiaries could help by formalizing valuation and governance, much like commodity exchanges centralized tracking to unlock scale. Building on such thinking, PEER DATA's insights into data as an asset highlight the inherent challenges: its intangibility, dynamic flows, and quality variations demand a shift from cost-centric views.
Modern pitfalls abound:
- Cost-Centric Focus: Dollars are tallied, but rows consumed (in queries or models, with traceable lineage) aren't tied to outcomes, obscuring true impact.
- Incentive Gaps: Absent granular valuation, underinvestment persists, akin to commodity risks from inaccurate measures.
- Existential Oversights: Data's survival-critical role is sidelined, unlike commodity standards that secured market integrity.
At PEER DATA, we view this disconnect not as fate, but as an opportunity to infuse commodity wisdom into digital assets, ensuring value flows where it's created and rewarded.
Bridging Eras: Lessons for Today's Data Valuation
To bridge this divide, we must introduce commodity discipline: standardize data "rows" through observability that captures lineage, evolution, and point-in-time states. This enables market-like monetization, aligning incentives and bolstering quality without radical overhauls. Just as music royalties provide a clear ledger of contributions, allowing payouts to flow to creators and performers, data tracking could clarify where value is added, directing rewards accordingly.
This synthesis halts the race to the bottom, enhancing connectivity, ROI visibility, and asset treatment. Drawing from commodity infrastructure, we can build data systems that standardize units to facilitate finance and trade.
PEER DATA's conceptual frameworks, like those exploring data-backed obligations, point toward this evolution, addressing intangibility while unlocking revenue potential.
Actionable lessons include:
- Granular Tracking: Emulate commodity precision to link data rows (via lineage and inventories) to revenue, justifying quality investments.
- Incentive Reform: Elevate governance, building on ideas like DataCo, to ensure value flows to where it's delivered.
- Connectivity Emphasis: Promote firm-wide flows, mirroring commodity accountability for corrections and enhancements.
Amid unease, these lessons offer hope: organizations can effectively harness data's potential, transforming it from overlooked expense to strategic powerhouse.
Conclusion and Teaser
Commodity markets standardized units to forge global systems, yet modern ledgers tally dollars while missing data's granular essence– exacerbating misalignments and highlighting the need for conceptual evolution in how data is understood. At PEER DATA, we harness these insights to guide a renaissance in data valuation, turning oversight into opportunity.
By bridging eras, we impose the discipline to elevate data from mere cost to market-builder. The reason we advocate for proper attribution isn't just about data; it's about empowering firms to understand where value resides, manage it effectively, and thrive. When organizations grasp data's contributions, much like royalties reward musical creators, value flows to where it's created and delivered, fostering stronger, more resilient businesses.
In our next installment, "Your Internal Data: Already Fueling Someone Else's P&L," we examine how data product managers attribute value internally, turning enablers into recognized assets firm-wide.