You are here:  Home  >  Data Blogs | Information From Enterprise Leaders  >  Current Article

Infonomics and Information Accounting – Part 3

By   /  July 24, 2013  /  1 Comment

by John Ladley

The past two blogs introduced the concepts of Infonomics and information asset accounting – labels are given to the approaches and techniques to treat information as an asset in a formal manner.   I spent a few of your attention cycles on explaining Doug Laney’s work, and added some of my own views.  Now it is time to talk technique. Suppose your boss said “Ok, if we could place the value of our information assets on the balance sheet, what would it say?”  Excellent question.  As promised what follows is a brief overview of some techniques.

But first, some legal and practical stuff:

  1. The material below represents a lot of hard work and research. There is also pending intellectual property activity in the way of trademarks, copyrights and patents in the works. Please do not repurpose this material and claim it as your own.
  2. Don’t assume because you understand the concept that you are ready to apply it. You can really get in the weeds on this stuff so consider some consultation help to get you started. There is a lot more behind the metrics presented below than fit within this blog.
  3. None of this is yet approved by anyone for formal financial statement use. So going to your CFO and asking for a new line item on the income statement or balance sheet could be career altering.
  4. A lot of this reads like an economics textbook. Well, it is economics.  Read it slowly. Sit in your study, iPad in lap, and enjoy. It will help. It may also impress your spouse, roommate, or children.

We presented four perspectives or approaches to valuing information: three from Doug, one from yours truly.   To review:

  1. Market approach -What the market will offer if the information asset is sold, e.g. Facebook or Axiom.
  2. Income approach– What income stream the asset will generate, e.g. revenue that can be generated with greater customer knowledge.
  3. Cost approach-What the replacement cost would be, e.g. the impact if all of your client account information was lost and had to be reconstructed.
  4. Liability approach-What potential loss or set aside of risk is inherent in the data, e.g. law suites from bad documentation, or regulatory fines.

There are several valuation techniques that can be applied within these approaches.  Doug Laney’s are based on an economic view; that is a calculation based on a specific view of value within his three approaches. The calculations used in my practice are deployed similarly, but since I take more of a project-based, accounting and business case driven approach, they seem different. In practice my organization merges Doug’s and mine when a client permits us to do a pro forma review of information asset value.

Alternatively, we use these techniques when we have a client absolutely insist that data governance must be justified on its own subjective merits.  Since our experience has shown that a lack of a business benefit view can greatly diminish the success rate of data governance programs, we develop some proactive financial scenarios.

Ok, here goes more economics talk.  Briefly, Doug’s valuation methods are:

  • Method 1: Intrinsic Value of Information – How good and easy to use is the data versus how likely are others outside the organization to have it also?  This is the view you can call the presumptive value of information, enabling subjective comparisons.
  • Method 2: Business Value of Information (BVI) – The value of information to a business process:  How good is the data? How applicable to the business or a particular business process is it?  How quickly can we get fresh data to the point of the business process? This one is useful if data quality is a big push.
  • Method 3: Loss Value of Information (LVI) – The cost of not having information:  What would it cost to replace the data, and what is the financial impact to the business if the data were lost over a time period? Key to this view of value is not the mechanical cost, i.e. restoring the files. Don’t forget damage to reputation and confidence.  Remember the reaction when Amazon cloud lost (forever) a few clients data?
  • Method 4: Performance Value of Information (PVI) – Value of information to business objectives, represented as key performance indicator (KPI) targets:  How much does having a unit of information incrementally contribute to moving closer toward all n KPI targets over a given period? I really like this one, but it politically hard. It requires a business area to give information management some credit or helping the business. But if you can get by that, this is an excellent metric to have in your pocket.
  • Method 5: Economic Value of Information (EVI) – The bottom-line financial value for the information asset:  The Performance Value of Information (PVI) (see above) for a revenue metric, less the cost of acquiring, administering, and applying the information. To exploit this view, you need to have the prior view in hand. So this is a bit advanced. However it takes the “cost of production” into account, which is economically prudent.
  • Method 6: Market Value of Information (MVI) -The income that can be generated by selling, renting or bartering with this information. How much is a business partner (p) willing to pay for access to this information? I am sure the Google has a version of this somewhere, but they haven’t shared it with me.
  • Method 7: Asset Contribution (ACI) – The value of information as a portion of total asset value. How much of a declared value of assets can we say information use is supportive and responsible for? This is the most difficult, because you are square on dipping into the balance sheet.  Like PVI, if you can get the politics pushed aside and think outside of the box, you get some interesting numbers.

Additional information asset accounting metrics used by my practice are:

  • Method 8: Content liability  – “Anti value,” i.e. the potential liability within a given data set or area of content. What are the possible fines, or have been the historical fines? If you are feeling frisky you can place present and future values around this.
  • Method 9: Overhead Impact – What has been the financial impact of failure to manage data, e.g. data quality assessment impacts would go into this bucket.  Lots of you are already doing this.  But you need to look at it beyond a one-time metric. If it is an on going cost or recurring liability, there is a bona fide financial impact.
  • Method 10: Benchmark Value – Similar to the Intrinsic approach, how are your competitors performing and how do they manage data? What is your cost of doing BI versus what your competitor is doing?
  • Method 11: Income streams by Information Management Dimensions – KPIs or notional calculations based on dividing income stream, such as Gross Income, by the number of knowledge workers, or number of Access data bases per employee.  Alternatively, you can divide cost areas into the same dimensions. For example, Gross Income divided by a count of your Knowledge Workers, gives you a productivity metric.

For almost all of these you can take several calculation paths. For example, Intrinsic or Asset Contribution can be viewed as the contribution of information relative to a total valuation of all assets.  You can calculate Present Value, Future Value or annuitize all of these calculations to arrive at a sense of contribution to organizational well-being.

If the terms “present and future value” and “annuitize” made you glaze over, then get some assistance from a friend in accounting. However, this stuff is becoming real.  The interest of CIOs and CEOs in this material has been tremendous.  Drop Doug or I a line.

The main take away from this series should have been this:  it is not out of our reach to apply some financial concepts to our information assets.  Lack of a formal accounting mandate is not an excuse. We can sit back and take a look at how information is contributing value to the enterprise.  It just requires looking at information differently than we have done historically.

About the author

President, IMCue Solutions John Ladley is a Business Technology Thought Leader and recognized authority in all aspects of Enterprise Information Management, with 30 years’ experience in planning, project management, improving IT organizations and successful implementation of information systems. As President of IMCue Solutions, he leads a consultancy focused on improving a client’s business results through information management and data governance. John is widely published, co-authoring a well-known data warehouse methodology, and a trademarked process for data strategy planning. His books, Making EIM Work for Business – A Guide to Managing Information as an Asset and Data Governance: How to Deploy and Sustain a Data Governance Program, are recognized as authoritative sources in the IM field. He frequently writes and speaks on a variety of technology and enterprise information management topics. His Information Management experience is balanced between strategic technology planning, project management and practical application of technology to business problems. John can be reached by email at jladley@imcue.com; his Twitter handle is @jladley.

  • Thanks for sharing this perspective John. In my view the task of identifying the meaningful value of data is one that is definitely achievable, and your schema really helps communicate this and provide a solid foundation for making it real. The challenge is that it still requires some real conscious effort, and I’m afraid that all too often, business inertia is such that it just doesn’t happen. (Not to mention the generally poor levels of awareness for data practices and information value within the business community).

    I discussed the question of identifying information value in a post last year. Recognising that putting an explicit dollar-value on data can be a bridge too far for many, I propose a salience-based approach that focusses on making the link data to it’s business usage within the business process: http://informationaction.blogspot.com.au/2012/06/concept-of-information-salience-or-to.html

You might also like...

Case Study: Using Data Quality and Data Management to Improve Patient Care

Read More →