Adding business value by adding up data’s value

When Moderna began developing its COVID-19 vaccine in early 2020, the company’s secret weapon wasn’t just its mRNA technology – it was decades of meticulously valued and curated research data. By understanding the true worth of their experimental data sets, Moderna had invested heavily in data management systems that allowed them to design their vaccine in just two days. This success story highlights a crucial truth: organizations that understand and value their data gain extraordinary competitive advantages.

The hidden asset on every balance sheet

Traditional balance sheets tell only part of an organization’s story. While physical assets, from manufacturing equipment to office buildings, are meticulously valued and depreciated, data – often an organization’s most valuable resource – remains conspicuously absent from financial statements. This oversight isn’t just an accounting quirk; it fundamentally misrepresents modern business value.

Consider a regional healthcare provider that collects patient outcomes, treatment efficacy, and operational metrics. These datasets meet all the criteria of a legitimate asset: they can be owned, they generate measurable benefits, and they can be exchanged for value. Yet their worth remains invisible on financial statements, leading to systematic underinvestment in data management and protection.

Benefits of data value scoring

Implementing a data value scoring system provides organizations with a structured approach to assessing and prioritizing their data assets. One key benefit is that data consumers across the organization can directly discover useful data assets. By assigning a value score to datasets, employees can easily identify high-impact, high-quality data, reducing the time spent searching for relevant information. This improves efficiency and ensures that critical data is leveraged effectively in decision-making.

Additionally, data value scoring helps organizations prioritize data management efforts, allocate resources more effectively, and identify opportunities for monetization or operational improvements. By treating data as a measurable asset, businesses can enhance data-driven strategies, improve governance, and increase overall return on data investments.

The dimensions of value

Think of data value like a diamond — it has multiple facets that together determine its worth. The first dimension is inherent quality: how complete, timely, and accurate is the data? Just as a diamond’s clarity affects its value, the cleanliness and reliability of data directly impact its utility. The second dimension is practical application: how frequently is the data used, and how do users rate its effectiveness? The third dimension is scarcity: how unique or irreplaceable is the dataset?

These quality indicators serve as leading indicators of financial value. When a global manufacturer discovered their warranty claims data was more valuable than previously thought, they invested in advanced analytics that reduced warranty costs by 23%. Their success stemmed from understanding both the qualitative and quantitative aspects of their data’s worth.

From insights to income

The financial impact of data flows through multiple channels. Revenue generation might come from data-driven marketing strategies or new product development. Cost savings emerge through operational efficiencies and risk reduction. Market value reveals itself when other organizations seek to license or purchase data assets.

A retail chain recently discovered that their customer behavior data, when properly cataloged and analyzed, could predict inventory needs with remarkable accuracy. This insight led to a 15% reduction in stockouts while simultaneously reducing excess inventory. The financial impact was clear and measurable, but it only became apparent after they implemented a formal data valuation framework.

Building your valuation framework

Successful data valuation begins with clear objectives aligned with business goals. A major financial services firm started by identifying its most critical data assets – customer profiles, transaction histories, and risk assessments. They then developed specific metrics to track how each dataset contributed to business outcomes. Finally, they implemented technology to automate these measurements and share insights across the organization.

The process revealed unexpected opportunities. Their fraud detection data, when combined with machine learning algorithms, not only reduced losses but created a new revenue stream through a service they now offer to smaller banks. This discovery came directly from understanding the multi-faceted value of their data assets.

The path forward

As data continues to grow in importance, organizations face a choice: continue treating data as an intangible resource of undefined value or embrace frameworks that recognize its true worth as a strategic asset. Those who choose the latter path position themselves to thrive in an increasingly data-driven economy.

The Moderna story, and others like it, demonstrates that understanding data’s value isn’t just about accounting – it’s about recognizing data as a fundamental business asset that can transform entire industries. Organizations that develop clear frameworks for measuring, managing, and maximizing their data’s value will find themselves better equipped to navigate an economy where data increasingly drives competitive advantage.

Final thoughts and next steps

Data is one of the most valuable assets an organization holds, yet it often goes unrecognized and underutilized. Assigning a tangible value to data is essential for positioning it as a strategic resource and unlocking its full potential. When organizations grasp data’s true worth, they can make more informed decisions, allocate investments effectively, and discover new opportunities to optimize or generate revenue from their data assets.

Doug Laney is a renowned data, analytics, and AI advisor and researcher, consulting to business, data, and analytics leaders on conceiving and implementing new data-driven value streams. He originated the field of infonomics and authored the best-selling book, “Infonomics” and the recent follow-up, “Data Juice: 101 Real-World Stories of How Organizations Are Squeezing Value From Available Data Assets.”  Doug is a three-time Gartner annual thought leadership award recipient, a World Economic Forum advisor, a Forbes contributing author, and co-chairs the annual MIT Chief Data Officer Symposium. He also is a visiting professor at the University of Illinois and Carnegie Mellon business schools and sits on various high-tech company advisory boards. Follow and connect with Doug via LinkedIn and #infonomics.