The 18 Generally Agreed-Upon Information Principles

The 18 Generally Agreed-Upon Information Principles

Since many organizations, including their CDOs, still struggle somewhat to formulate a comprehensive enterprise strategy for data, I thought I'd share the set of 18 Generally Accepted Information Principles I developed as part of the research for my book on Infonomics. They're based on the way we measure, manage and monetize other assets--or should be. And those familiar with accounting practices might notice I shamelessly borrowed from GAAP to frame them in terms of a set of Principles based upon basic Assumptions and tempered by a set of Constraints.

I'm keenly interested in what others think. Are they practical, adaptable, comprehensive? Can/should they form the basis of any enterprise data strategy? Should they define the CDO's role to some degree? And ultimately, how much would an organization adopting them raise its data & analytics game?


Assumptions are agreed-upon basic beliefs about information. They guide our understanding of how information assets can and should be perceived, managed, and deployed.

1. Asset Assumption: Information is an asset because it meets each of the criteria of an asset.

2. Proprietorship Assumption: An organization’s information assets include all forms of data and content of discernible identifiability for which it can claim ownership and/or exclusive control.

3. Appraisal Assumption: Information has realized, probable, and potential cost and value. 

4. Dominion Assumption: The practice of internal information “ownership” limits its potential value to the organization, and thereby the performance of the organization itself.

5. Benefit Assumption: Information has uses well beyond its original purpose, does not deplete when used, and can be used simultaneously for different purposes.


Constraints are generally agreed-upon information regulations, confinements, or bounds. They acknowledge the limits of how well or precisely information assets can be monetized, managed, and measured, and therefore restricts how absolutely the principles which follow can be applied. 

6. Specificity Constraint: The groupings of data or content that comprise an “information asset” will vary from one organization or use case to the next.

7. Recognition Constraint: Information cannot be represented in auditable financial statements, nor be capitalized as other assets (per current accounting standards).

8. Jurisdiction Constraint: The provenance, lineage, ownership, and sovereignty of an information asset may be difficult to determine or legally establish.

9. Valuation Constraint: Valuation and other measurements of an information asset will be inexact but useful, just as are valuations of other kinds of assets. 

10. Resource Constraint: Tradeoffs among information asset quality, availability, and accessibility are inevitable.


Principles are generally agreed-upon axioms that dictate how information assets should be managed, and should lead to more detailed guidelines, policies, procedures, and standards specific to the organization.

11. Relevance Principle: Information assets should be managed with at least the same discipline as other recognized assets.

12. Inventory Principle: Information assets should be cataloged, described, classified, related, and tracked.

13. Ownership Principle: By default, information assets belong to the organization, not any application, department, or individual.

14. Authorization Principle: The quality requirements, access, use, protection, and other rights and responsibilities for any information asset, even within the organization, should be contractually established by or with a sanctioned and empowered trustee.

15. Assessment Principle: The quality characteristics, cost, value, and risks of any information asset should be knowable at any point in time, and used for prioritizing and budgeting information-related initiatives.

16. Possession Principle: An information asset should be acquired or retained only if its actual or planned value is greater than its cumulative cost, or as required by laws or other regulations.

17. Replicability Principle: An information asset should be duplicated or derived only to improve its utility or availability, and only if doing so also increases its net value.

18. Optimization Principle: a. The business is responsible for optimizing the usage and understanding of information; b. the data management organization is responsible for optimizing information’s availability and utility; c. the technology organization is responsible for optimizing information’s accessibility and protection.

How well has your organization embraced principles like these intuitively or explicitly? How would you get your organization to do so? Are there other principles you might suggest? Perhaps later I'll suggest some new ones conceived by my brilliant Infonomics students at the University of Illinois Gies College of Business.

Douglas Laney is the Data & Analytics Strategy Innovation Fellow at West Monroe where he consults 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: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage.” 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. Doug posts regularly using the hashtag #infonomics.

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