Economic characteristics of Data and Information assets

If we are going to consider data and information as assets, we need to consider the economic characteristics of those assets (see previous post).

Below is a table of economic characteristics that could have relevance to data and information assets.

We have identified the characteristics, if, when and how Data and Information Assets have those characteristics. We have drawn analogies between every day assets and D/I assets.

Lastly, we have provided an example of the how that characteristic interacts with data assets.

As you can see, data and information are truly unique assets. They somewhat share the characteristics of many assets physical, financial and other types of assets (e.g. IP).

Why are you reading economic concepts on a data asset management software blog?

Because understanding the assets (especially natural person data assets which Pontus Vision focuses on) is the first step in ensuring their importance. If we don't behave like those assets are valuable and have large economic value - then we will not treat them with the right level of respect.

The Economic value of Data & Information assets

At this point of the debate, we will avoid putting an economic value on the data / information asset. Laney's rally against the accountants is wise; engaging with those who know the cost of everything and the value of nothing it a troubling task. 

About the Author

Daniel (Dan) Rolles is the CEO and Founder of BearingNode, where he leads the firm's mission to help organisations unlock the commercial value of their data whilst enhancing their risk management capabilities.

As CEO, Daniel drives BearingNode's strategic vision and thought leadership in data transformation, analytics strategy, and the evolving regulatory landscape. He regularly shares insights through industry publications and speaking engagements, focusing on practical approaches to data governance, AI implementation, and performance transformation in regulated environments. He is one of the key authors of BearingNode's Data and Information Observability Framework.

With over 30 years of experience in Data, Analytics and AI, Daniel has successfully built and led D&A teams across multiple industries including Financial Services (investment, commercial and retail banking, investment management and insurance), Healthcare, and Real Estate. His expertise spans consulting, commercial leadership, and delivery management, with a particular focus on data governance and regulatory compliance.

Daniel holds a Bachelor of Economics (University of Sydney), Masters of Science (Birkbeck College, University of London), and Executive MBA (London Business School).

Based in London, Daniel is passionate about financial inclusion and social impact. He serves as a Trustee for Crosslight Advice, a debt advisory and financial literacy charity based in West London that provides vital support to individuals facing financial vulnerability.

References

Infonomics - Douglas B Laney. Infonomics