Infonomics

Infonomics is the theory, study and discipline of asserting economic significance to information. It provides the framework for businesses to measure, manage and monetize information as a real asset. Infonomics endeavors to apply both economic and asset management principles and practices to the valuation, handling and deployment of information assets.

The term is a portmanteau of “information” and “economics.”

Origination and History

In the late 1990s, then META Group and now Gartner IT industry analyst Doug Laney coined the term Infonomics to describe his proprietary research and consulting around quantifying information’s value and defining how to manage information as an actual enterprise asset.[1] This concept stemmed from his work with data warehouse pioneer Prism Solutions (now part of IBM) at which he and his professional services colleagues developed information auditing techniques to validate and qualify and quantify source data quality characteristics and potential business value. These methods were formalized into Prism's commercial ITERATIONS data warehouse methodology still offered by IBM.

Laney’s work builds on and intersects with other disciples including:

Principles of Infonomics

The seven principles of infonomics[3] are as follows:

  1. Information is an asset. The primary principle of infonomics is the recognition of information as an enterprise asset. Although generally accepted accounting principles (GAAP) as yet do not require the reporting of information assets on the balance sheet, infonomics deems that organizations acknowledge that information is more than merely a resource.
  2. Information has both potential and realized value. While it is generally accepted that information has value when used in decision making or to fuel business operations, infonomics posits that information, just as GAAP-recognized assets, has a definitive value even when not in-use. The accounting definition of a balance sheet asset being an item of ‘’probable future economic value’’ applies as well to information. Information's value can also be determined in terms of its realized value and potential value.
  3. Information’s value can be quantified. Similar methods for quantifying the value of accepted intangible assets can and should be applied to valuing information assets. These valuation (finance) methods include as applicable and relevant: market approach, the cost approach, and the income approach. As well, non-economic valuation methods that quantify information’s relative value, business process relevance and data quality-related value have application in helping organizations make strategic information-related IT and business decisions.
  4. Information should be accounted for as an asset. Although information is not yet a recognized balance sheet asset, organizations should consider it one for internal reporting purposes. This includes an applying valuation methods on a scheduled basis and when a given information's value may be impaired, and internally reporting information asset value on a supplemental balance sheet.
  5. Information’s realized value should be maximized. Infonomics valuation exercises typically disclose that information is a vastly underutilized asset and that organizations should consider opportunities to improve their capture and deployment of information in generating top-line and bottom-line benefits. This includes decision-making, business process automation, innovation, and even the packaging and direct marketing the organization’s information assets.
  6. Information’s value should be used for prioritizing and budgeting IT and business initiatives. IT and business related initiatives that leverage or secure information assets should be budgeted against the quantified economic value of the information and the cost to acquire, administer and apply the information. Currently such initiatives tend to proceed without this degree of fiscal diligence.
  7. Information should be managed as an asset. Traditional physical and financial assets have a definitive lifecycle and procedures for their effective handling throughout. Infonomics principles suggest that organizations should apply their own expertise, policies and practices in asset management toward the management of information assets.

Benefits of Infonomics

Benefits[4] of applying infonomics principles and practices include but are not limited to:

Thought Leadership

Throughout the 2000s Doug Laney and his colleagues developed and deployed information asset valuation models, information auditing methods, and information asset management practices. In 2010 Laney formed the Center for Infonomics, a non-profit think tank to collaborate on and further the principles and practices, and the associated the Center for Infonomics LinkedIn Group. The same year he began lecturing on Infonomics at leading business schools[5][6][7][8][9][10][11] holding Infonomics workshops[12] and conducting press interviews on the topic.[13]

John Ladley, author and expert on enterprise information management also collaborates with Laney on infonomics research, and lectures on the topic.

In 2010, Informatica's John Schmidt authored a blog series on Data as an Asset.

IT research analysts from Gartner (e.g. Andrew White, Debra Logan, Joe Bugajski, Mei Selvage and Michael Smith, Nigel Rayner), and Forrester (e.g. Andre Kindness, Holger Kisker, Rob Karel) have also written and advised on information value-related topics.

Douglas Hubbard's book, How to Measure Anything features a method for valuing information based on its decision-making ability.

The open source MIKE2.0 Methodology, based on Prism Solutions' ITERATIONS methodology, includes methods and tools for information asset management and a broad-spectrum corporate value-based information valuation.

Deidre Paknad, former Head of Information Lifecycle Governance at IBM has promoted and has written extensively about the emerging concept of defensible disposal.

E.G. Nadahan, HP Distinguished Technologist authors a blog that frequently features information value related topics.

Dave McCrory, SVP at Warner Music Group authors the DataGravity blog (launched July 2013) in which he has posited a formula for data gravity that considers the size of a data set, and its compression ratio (density), the "application mass" (i.e. memory and disk usage, CPU utilization), bandwidth, latency, and number and size of data requests. He suggests reasons to increase or decrease data gravity along with some uses for it.

In 2013, AIIM hosted a Value of Information #infochat on which its editor and community manager Bryant Duhon posted a slideshare entitled: Information as an Asset: 9 Essential Steps. In 2016, AIIM hosted a forum in Washington D.C. to discuss information value.

In 2015, Oracle strategist and former Forrester Research analyst, Paul Sonderegger, starting writing and speaking about "data capital."

Chris Walker's Info Nuggets blog included a couple posts in late 2013 (I Can't, Can You? Valuing Information and I think I Can - Valuing Information Pt 2) along with some follow-on discussion.

In the late 1980s, Marilyn Parker of the IBM Los Angeles Research Center and Robert Benson of Washington State University respectively defined an approach to the evaluation of information systems, called information economics.

Related Academic Programs and Research

Related Articles, Papers and Presentations

2016

2015

2014

2013

2012

Older

Related Books

Alternate and Incidental Uses of the Term

Examples of other organizations using the “infonomics” moniker in one form or another include:

See also

References

This article is issued from Wikipedia - version of the 10/21/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.