The Currency of Information: Measuring the Value of Data (Part Four)

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Data professionals often talk about the importance of managing data and information as organizational assets, but what does this mean? What is the actual business value of data and information? How can this value be measured? How do we manage data and information as assets? These are some of the questions that I intend to address in this series of articles.

In the first article, we talked about the different ways that data and information can be used to create business value. In the second article, we identified data as a special type of circulating asset and discussed its particular characteristics. In the third article, we described in detail the processes of managing data as an asset. The next questions we need to address are: How exactly do we measure the business value of data, and who should do the work of managing data assets and measuring their value?

How Do We Measure the Value of Data?

How do we measure – and account for – the value of data and information assets? We can’t, for example, put “65 terabytes of data” on an accounting ledger and assign a value to it! This is what makes managing data and information more difficult than managing other business assets. As Gartner vice president and distinguished analyst Douglas Laney has remarked, “The head of information strategy for a major government institution proclaimed to me, ‘We have a better accounting of the toilets in the building than our information.”’

But there are ways to address this problem. As shown in the chart above, Gartner[i] has suggested six different approaches to measuring the value of data and information assets:

  • Intrinsic Value of Information (IVI). This measures the correctness, completeness and exclusivity of an organization’s data (essentially, an estimate of the economic value of the data if it were perfect, minus the economic impact or risk to the business of data that is currently bad, missing or suspect)
  • Business Value of Information (BVI). This measures the value created by specific business uses of the data; e.g., the use of specific data to enable order fulfillment
  • Performance Value of Information (PVI). This measures the value of the data that affects key business drivers and KPIs
  • Cost Value of Information (CVI). This measures the cost to the organization if the data were to be lost or corrupted
  • Market Value of Information (MVI). This measures the value that could be obtained by selling or trading (i.e., monetizing) data and information
  • Economic Value of Information (EVI). This measures the direct contribution of data and information to an organization’s bottom line

For each of these measures, the question is: How do we measure the value that data and information contribute? One approach I’ve recommended is to use a data-centric process improvement program such as Six Sigma. Six Sigma uses an organization’s data assets to quantify the value of a business process, as well as the value of improvements to that process. Thus, the value of a business process determines the value of the data that supports and enables that process, and the cost savings of improving a business process determines the value of the data that enables that improvement. We can also calculate the business value of the data that supports a business process as being equal to the loss the company would suffer if that data were lost or corrupted in some way that prevented the process from working.

For business drivers and KPIs, the business value generated by meeting the goal or by improving the KPI, say, 10%, is the value of the data that enables the organization to meet that goal or improve that KPI.

For new business initiatives, for example, a new customer engagement program that requires a “360-degree view” of the customer, or a market expansion, or the introduction of a new product or service, the business value created by the initiative is the value of the data that supports and enables it. And if data is packaged and marketed, of course, then the value of that data is the revenue it generates.

Another suggestion I’ve made is to make use of an organization’s problem reporting and resolution process. Most companies have a process for opening “trouble tickets” when a problem occurs and tracking the root cause and ultimate resolution of that problem. In cases where a business outage or process failure can be traced back to missing or incorrect data, then the value of that data is the business cost of the outage.

Who Should Do This Work?

The last question is: Who should do the work of measuring — and improving — the business value of data and information assets? My answer would be: the organization’s chief data officer (CDO) or his/her delegates. If your organization doesn’t have a CDO (and a supporting data and information management/governance team), it should have one, and that person should report to the CEO or CFO, not to the CIO (CIOs, despite their title, are mostly responsible for deploying and maintaining technology infrastructure, not managing data and information).

In my view, the CDO has three primary responsibilities:

  • Create, package, distribute, and continually improve the quality and usefulness of data and information assets
  • Continually leverage these assets in multiple ways to create and enhance business value
  • Measure, record, and track the business value generated by these data and information assets, and report this value to senior management

The CDO has the responsibility of determining where data and information assets need to be created or improved; creating and managing a data governance team to ensure that high-quality data is available throughout the organization; training workers across the organization on where and how to find, use and manage data; establishing programs to use data and information in ways that generate business value (by streamlining business processes, enabling new business initiatives, managing and improving stakeholder relationships and monetizing data products and Information services); and tracking and publicizing the business value generated by these data and information assets.


The asset value of data and information is something that has long been talked about, but – in my opinion – not seriously thought through. There are serious conversations that need to take place at the highest levels of organizational management – not just in data management organizations.

An awareness of data and information needs to become part of every executive and manager’s thinking when business processes are created, modified, or transformed. Business managers need to understand the importance of data and information to the processes that support the products and services that generate revenue for the company. They also need to understand how adversely revenue could be affected if the underlying data becomes missing, corrupted, incomplete, or out of date.

It needs to be the responsibility of the CDO to establish effective data management and data governance processes to ensure that high-quality, timely, accurate, useable, business-relevant data is always available, and that people know where to find it, how to get it, and how to use it. Data-driven process improvement programs such as Six Sigma can be used to leverage data in ways that directly improve business performance and generate business value. And these business revenues and cost savings can — and should — be tracked and measured, and the business value of data and information continually reported to senior management.

We often talk about the importance of “data-driven” organizations, but before an organization can be “data-driven,” it first needs to become “data-conscious.” And then it needs to learn how to manage the data it has, how to use that data to create business value, and how to measure the value that is generated. What’s measured is what’s managed, and what’s managed is what drives business value.

Our organizations need to focus on managing data and information to create business value, and then on measuring, tracking, and reporting this value. 

[i] Gartner Inc. Why and How to Measure the Value of Your Information Assets. White Paper, August 2015,

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Larry Burns

Larry Burns

Larry Burns has worked in IT for more than 40 years as a data architect, database developer, DBA, data modeler, application developer, consultant, and teacher. He holds a B.S. in Mathematics from the University of Washington, and a Master’s degree in Software Engineering from Seattle University. He most recently worked for a global Fortune 200 company as a Data and BI Architect and Data Engineer (i.e., data modeler). He contributed material on Database Development and Database Operations Management to the first edition of DAMA International’s Data Management Body of Knowledge (DAMA-DMBOK) and is a former instructor and advisor in the certificate program for Data Resource Management at the University of Washington in Seattle. He has written numerous articles for and and is the author of Building the Agile Database (Technics Publications LLC, 2011), Growing Business Intelligence (Technics Publications LLC, 2016), and Data Model Storytelling (Technics Publications LLC, 2021).

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