Measuring What Matters in Data Products (#2/6)
Creating Sustainable Business Value
Executive Summary:
Organizations today face a critical challenge: despite significant investments in data infrastructure, they struggle to create proportional business value. While many focus on measuring data quality scores, tracking usage statistics, or counting the number of data products created, these metrics often mask whether real business impact is being achieved. This article explores how organizations can implement data products to create meaningful change rather than just technical outputs, examining both strategic principles and practical approaches that enable sustainable success.
Beyond Traditional Metrics
The journey to effective data products begins with understanding a fundamental distinction: the difference between what we produce and what value we create. Organizations often measure what's easy to track - data volumes processed, quality scores achieved, or products delivered. While these metrics are important, they can create an illusion of progress without delivering real business impact.
Consider how most organizations approach data initiatives today. They meticulously track technical metrics, maintain extensive dashboards, and celebrate when numbers move in the right direction. Yet something crucial is often lost in this pursuit of measurable results: the ability to understand whether all this activity creates meaningful change in how the organization operates and competes.
Understanding True Value Creation
Creating sustainable value through data products requires understanding three distinct elements:
The data capabilities we produce (outputs)
The behavioral changes these capabilities enable (outcomes)
The business results these changes create (impacts)
Consider a customer data product: While we can easily measure data quality scores or API response times, the true value lies in how it changes decision-making behavior and ultimately improves customer relationships. When organizations focus primarily on outputs, they often create environments where teams optimize for metrics rather than actual value creation.
Bridging the Business-Data Divide
Traditional approaches to data management often create an artificial separation between business operations and data capabilities. Organizations build extensive data warehouses and lakes, yet struggle to maintain the rich context that gives data its meaning. This separation often results in data assets that are technically sound but business-irrelevant.
Data products address this challenge by maintaining data's business context while making it accessible for broader use. Unlike traditional approaches that extract data from business systems and move it through various transformations, data products preserve the rich relationships and meaning that make data valuable. This enables both operational and analytical teams to work with data that maintains its business relevance.
The Power of Decentralized Creation
Successfully implementing data products requires rethinking how organizations manage and control their data assets. Rather than enforcing standards through central teams and manual processes, data products embed controls directly into the infrastructure. This automated governance transforms how organizations balance control and innovation.
The key lies in establishing clear guardrails that define boundaries while enabling freedom within them. When teams understand these boundaries and have automated tools to stay within them, they can focus on creating value rather than navigating bureaucracy. This transforms governance from a constraint that slows teams down to an enabler that helps them move faster with confidence.
From Exploration to Production
Organizations need both the ability to explore new possibilities and to reliably deliver proven value. Data products enable this through complementary patterns that combine exploration and production capabilities. The exploration pattern enables teams to discover new ways of creating value from data, while the production pattern ensures reliable delivery of proven capabilities.
Crucial to this approach are regular "Stop! Think!" moments where teams reflect on whether they're creating real value, not just delivering features. As explored in The Outcomes Paradox, these reflection points help teams break free from focusing solely on outputs to understand whether they're creating meaningful change. Similarly, the structure provided by these patterns, as discussed in The Paradox of Autonomy, enables rather than constrains teams' ability to innovate effectively. These reflection points transform traditional progress reviews into opportunities for deeper learning about how data creates business value.
Building the Foundation
Creating effective data products requires infrastructure that enables teams to work independently while maintaining necessary standards. This self-service infrastructure embeds organizational knowledge and requirements into reusable patterns, making it easier for teams to do the right thing.
More importantly, this infrastructure enables teams to focus on creating business value rather than solving technical challenges. By providing proven patterns for common needs, it helps teams move faster while maintaining quality and consistency.
Measuring What Matters
Creating sustainable value with data products requires transforming how we think about success. Rather than focusing solely on technical metrics or feature delivery, successful organizations create space for teams to understand and measure meaningful change.
This starts with shifting our questions at three levels:
From technical outputs to business outcomes:
Instead of "How many data products have we deployed?" ask "What business decisions have improved through our data products?"
Beyond "What's our data quality score?" explore "How has better data changed our ability to serve customers?"
Rather than "How many teams are using our data products?" ask "How has data transformed our ways of working?"
From individual metrics to value chains:
Instead of "How fast can teams access data?" ask "How has faster access changed our response to market opportunities?"
Beyond "How many dashboards have we created?" explore "Which insights are driving meaningful business changes?"
Rather than "What's our platform adoption rate?" ask "How have our data capabilities created competitive advantage?"
From usage statistics to business impact:
Instead of "How many API calls did we serve?" ask "Which processes have been transformed through data access?"
Beyond "How many users do we have?" explore "What new business capabilities have we enabled?"
Rather than "What's our data coverage?" ask "Where has better data led to better outcomes?"
This shift doesn't mean abandoning traditional metrics - it means enriching them with deeper understanding of how data products enable organizational transformation. Through these questions, teams can better understand whether their work creates lasting impact rather than just technical achievements.
Sustainable Evolution
Unlike traditional data management approaches that often require large, disruptive changes, data products enable continuous adaptation and improvement. This evolutionary capability comes from how they combine clear boundaries, strong contracts between producers and consumers, and automated controls that can evolve with the organization.
This approach enables organizations to start small, learn from experience, and gradually expand their data product capabilities. Teams can move at their own pace while maintaining connections to the broader organization. Most importantly, they can continuously adjust based on real evidence of value creation rather than predetermined plans.
Looking Forward
As organizations continue their digital transformation journeys, data products provide proven patterns for creating sustained value from data assets. Success requires moving beyond simple metrics to understand and enable meaningful change. In our next article, we'll explore how organizations can structure themselves to effectively deliver and maintain data products, examining the roles and relationships needed for success.