Doug Laney’s 2018 interview frames big data around volume, variety, and velocity, then asks a more practical question: how can organizations manage information as an economic asset? His answer, infonomics, is a way to monetize, manage, and measure information—not a claim that accounting rules automatically recognize every dataset as a balance-sheet asset.
What did Doug Laney mean by the 3Vs of big data?
In a KDnuggets interview published January 25, 2018, Laney discussed volume, variety, and velocity, the three dimensions commonly associated with his big-data formulation. The interviewer linked the formulation to 2001; the interview repeats that attribution but is not the original publication documenting it.
- Volume is the amount of data an organization handles.
- Variety is the range of forms and sources represented in that data.
- Velocity is the speed at which data is generated, processed, and used.
Laney said velocity was becoming more important as businesses made more operational decisions and automated processes in real time. He treated veracity and other proposed “Vs” as data-management considerations, not as dimensions that define whether data is big. That is his framing in 2018, not a universal taxonomy for every later use of the term.
Is big data still an important concept?
The interviewer explicitly asked whether big data was still important and how many Vs Laney saw. The interview does not establish a current industry-wide answer or a definitive number of Vs. Its useful distinction is between the original three dimensions and additional qualities that may matter when managing data. Organizations can use that distinction without treating every newly proposed V as part of the definition.
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What is infonomics?
Laney described infonomics as “the concept that information is, or should be, an actual enterprise asset.” The phrase “should be” matters: he was making a conceptual and managerial argument, not saying accounting standards formally recognize all information as an asset.
Gartner’s book page for Infonomics describes the concept as “the theory, study and discipline of asserting economic significance to information.” The book catalog lists Doug Laney as author, gives the publication date as September 2017, and identifies the title as Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage (ISBN 978-1138090385). Gartner presents it as guidance for chief data officers and information and analytics leaders, with relevance to executives including CEOs, CIOs, and CFOs.
How does the 3Ms framework work?
Laney organizes infonomics around three activities: monetize, manage, and measure. The sequence is practical: identify ways information can contribute economic benefit, manage it deliberately, and measure its condition and contribution so decisions are informed rather than assumed.
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Monetize information
Monetization means using information to produce economic benefit, directly or indirectly. Selling or licensing a dataset is only one possibility. Information can also support better processes, products, decisions, risk reduction, compliance, or commercial terms. In a 2021 West Monroe Q&A, Laney described monetization broadly, including process improvements, partnerships, enhanced products, and barter. These are possible mechanisms, not guarantees of a return or blanket permission to use data.
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Laney argues that organizations should apply asset-management discipline to information: understand what they hold, who is responsible for it, how it may be used, and what controls are needed. He said a common failure is to neglect measurement and management of information while managing other assets more rigorously. Good governance and data quality matter whether the intended benefit is internal or commercial.
Measure information
Measurement can address data quality and relevance as well as its effect on business indicators and economic value. Laney names three valuation lenses:
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- Cost approach: considers the costs associated with creating, collecting, or maintaining information.
- Market approach: considers comparable market transactions or prices where meaningful comparables exist.
- Income approach: estimates value in relation to economic benefits the information may generate.
These approaches answer different questions and may depend on different assumptions. None is automatically a definitive market price for a dataset. In the 2021 West Monroe Q&A, Laney also recommended a supplemental view of information’s cost, market value, and contribution to income; that is his management recommendation, not a universal accounting rule.
How can a company monetize information?
The interview points to three distinct mechanisms. Their suitability depends on the data, the organization’s capabilities, and the legal, contractual, privacy, and security conditions surrounding its use. The interview does not rank them by return on investment.
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| Mechanism | How value is realized | Capabilities and questions to address |
|---|---|---|
| Direct licensing | Permit another party to use information under agreed terms, potentially in exchange for payment. | Assess data quality, governance, rights to use and share the data, security, and whether distribution is commercially viable. |
| Indirect operational improvement | Use information internally to improve a process or business outcome rather than sell the data itself. | Connect analytics to a business decision or process; evaluate the intended KPI impact and manage access and quality. |
| Barter or better terms | Exchange information or information-enabled value for more favorable business terms or another benefit. | Establish what each party provides, permitted uses, controls, and how the value of the exchange will be assessed. |
These mechanisms do not make every data use lawful, safe, or worthwhile. In particular, the interview is not a recommendation to sell personal data; organizations need to establish their rights and obligations before using or sharing information.
Why does Laney argue information is often undervalued?
His concern is that businesses may treat information as an operational by-product rather than an asset that merits ownership, stewardship, measurement, and investment. Without a view of quality, relevance, cost, and contribution, leaders can overlook opportunities to improve decisions or processes and cannot make well-grounded choices about further investment or external use.
Laney summarized the relationship this way: “you can’t manage what you don’t measure, and you can’t monetize what you don’t manage.” The quotation comes from the 2018 KDnuggets interview. It captures his argument for measurement and management before expecting information to produce economic value.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What examples and figures did Laney cite?
In the 2018 interview, Laney said Gartner had a compilation approaching 500 real-world stories of information monetization. That was his reported figure at the time, not a current count or an independently audited statistic. In a 2021 West Monroe interview, he said he had compiled more than 500 real-world examples of data and analytics in action; that, too, is his self-reported figure in that interview. Neither number establishes a market size, typical return, or adoption rate.
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The company examples and valuation practices discussed in the 2018 interview should be read as examples Laney cited at that time, not as independently verified descriptions of those companies’ current arrangements.
Further reading
For a fuller treatment of the 3Ms, see Laney’s Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage. Gartner’s catalog identifies the author, September 2017 publication date, and ISBN 978-1138090385. The 2018 interview remains useful for understanding how Laney connected big data’s 3Vs with the infonomics argument.
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