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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11In a 2018 interview, information strategist Doug Laney argued that organizations should treat information as an economic asset: manage it deliberately, measure its quality and contribution, and look for ways it can improve results or generate value. His framework—Monetize, Manage, Measure—does not mean every dataset belongs on a balance sheet or should be sold. It is a way to think more rigorously about the costs, uses, and potential value of information.
KDnuggets published Gregory Piatetsky’s interview with Laney on January 25, 2018. The conversation ranges from the familiar “3Vs” of big data to information valuation, analytics, data marketplaces, and ownership. Its examples and forecasts reflect the interview’s 2018 context, rather than a current inventory of company practices.
What did Laney mean by big data’s 3Vs?
Laney identifies volume, variety, and velocity as the original dimensions associated with big data. In the interview, he says velocity is becoming more important as organizations make operational decisions and automate processes in real time. The framework is a way to describe data challenges, not a test that every organization or dataset must pass.
The interviewer asks whether big data is still important and how many Vs Laney sees. Laney treats veracity and other proposed Vs as relevant considerations for managing data, but not as additions that define whether data is “big.” That distinction is his 2018 framing, not a claim that every later use of the term has followed the same convention. The interview associates the 3V formulation with 2001; it is not the original publication documenting that history. Read the interview.
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What is infonomics?
Laney’s central proposition is: “Infonomics is the concept that information is, or should be, an actual enterprise asset.” The qualification matters. He is making a case for how organizations should recognize and manage information’s economic significance; that statement does not establish that accounting standards formally recognize all data as balance-sheet assets.
Gartner describes infonomics as “the theory, study and discipline of asserting economic significance to information.” Its book overview presents the topic as guidance for chief data officers and information and analytics leaders, with relevance also to CEOs, CIOs, and CFOs. Gartner’s book page lists Laney’s Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage, published in September 2017, ISBN 978-1138090385.
How does Laney’s Monetize, Manage, Measure framework work?
Laney describes three complementary practices—the 3Ms. The order is useful: identify potential economic benefit, manage information so it can be used responsibly and reliably, and measure its condition and contribution. In the interview, he puts the dependency succinctly: “you can’t manage what you don’t measure, and you can’t monetize what you don’t manage.”
Monetize: find economic benefit
Monetization is broader than selling a dataset. Laney describes direct licensing, using information and analytics to improve business processes or outcomes, and exchanging information for better commercial terms. In a 2021 Q&A, he also names risk reduction, compliance, partnerships, and enhanced products among possible benefits. These are examples of mechanisms, not proof that a particular use is lawful, profitable, or suitable for every organization.
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Manage: apply asset discipline
Managing information means treating its quality, access, use, and stewardship as business concerns rather than leaving them solely to technical teams. Laney’s 2021 recommendation is for business leaders to act as trustees and advocates for corporate data, rather than treating it only as an IT asset. Good management is a prerequisite for reliable use, but it does not by itself establish that a dataset has commercial value.
Measure: assess condition and contribution
Laney’s measurement approach includes information quality and relevance, its impact on key performance indicators, and its economic value. The purpose is to make costs and benefits more visible to decision-makers. In a 2021 West Monroe Q&A, he recommends a supplemental view of data cost, market value, and contribution to income; he does not present that view as a universal accounting rule.
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What are the main ways to monetize information?
The appropriate mechanism depends on what the information can do, whether the organization can use or distribute it responsibly, and what control it needs to retain. Laney’s examples support three broad routes; they do not establish which produces the highest return.
| Route | How value is realized | Capabilities and questions to address |
|---|---|---|
| Direct licensing or data products | Provide information to another party under agreed terms, potentially for payment. | Assess data quality, rights and permissions, governance, security, and the ability to distribute and support the product. A possible market does not make every dataset appropriate to sell. |
| Indirect operational improvement | Use information and analytics to improve a process, product, decision, or outcome. | Connect the use to a business measure, establish data and analytics capability, and determine whether the observed change can reasonably be attributed to the information-enabled intervention. |
| Barter or commercial exchange | Exchange information for improved business terms or another commercial benefit rather than cash. | Define the value received, permitted uses, access and retention controls, and what happens if the relationship ends. |
These routes are not interchangeable. Direct licensing makes a data product and its terms central; operational improvement depends on using information in a workflow; barter requires evaluating a non-cash return. The interview does not rank them by return on investment. Nor does it support treating the sale of personal information as automatically appropriate or lawful: rights, consent, privacy, contracts, and applicable regulation need to be assessed for the actual use.
How can a company estimate information’s value?
Laney names three valuation lenses: cost, market, and income. They answer different questions, so they should not be mistaken for three routes to one definitive price.
| Approach | Valuation lens | Useful question |
|---|---|---|
| Cost | Considers costs associated with producing, acquiring, maintaining, or managing information. | What resources does it take to create and keep this information usable? |
| Market | Looks to market evidence for comparable information or transactions, where such evidence exists. | Is there a meaningful external reference for what similar information is worth? |
| Income | Considers economic benefit attributable to using or monetizing the information. | What revenue, savings, risk reduction, or other income contribution can be tied to its use? |
The interview names these approaches but does not prescribe one formula or establish that every dataset can be valued reliably. A company can use them as distinct decision lenses: cost helps frame investment, market evidence can inform exchange, and income analysis focuses on realized or expected contribution. Any estimate depends on its assumptions and the particular context.
Why do organizations often leave information’s value unrealized?
Laney’s recurring criticism is that organizations often do not measure and manage information with the discipline they apply to other assets. Without measures of quality, relevance, use, cost, and business contribution, leaders may struggle to distinguish valuable information from data that merely accumulates. That also makes it harder to decide what to improve, protect, share, or stop maintaining.
The interview reports that Gartner had a compilation approaching 500 real-world information-monetization stories; that was Laney’s reported figure in 2018, not a current or independently audited count. In a 2021 West Monroe Q&A, Laney said he had compiled more than 500 examples of data and analytics in action. Those are anecdotal compilations, not industry-wide measurements of adoption, market size, or typical return.
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Laney’s Infonomics develops the Monetize, Manage, and Measure framework and discusses information asset management and valuation models. Gartner’s catalog provides the publication details and an Amazon link. His author site also lists the related book Data Juice; the interview and book catalog do not establish its current edition or listing details. Doug Laney’s author site.
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Sources
- KDnuggets: “Exclusive Interview: Doug Laney on Big Data and Infonomics,” January 25, 2018.
- Gartner: Infonomics book overview and publication details.
- West Monroe: 2021 Q&A with Doug Laney on infonomics.
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