Seven Laws of Information and Its Contextual Reference to IoT

Prashant specializes in Big-Data, Internet of Things, Urban & Rural Informatics and Cloud-powered Wearables.

While exploring research focused on information-as-an-asset, I stumbled upon a paper (dated around 1999 written by Daniel Moody, University of Melbourne and Peter Walsh, Simsion Bowles and Associates) that took an asset valuation approach towards information. In this blog, I've attempted to apply what I had learned through their approach in the context of the Internet of Things, valuation and economic value of data emerging from machines and sensors. Moody and Walsh noted information is a firm's most valuable asset, however very little is done to look at it. They introduced 'Laws of Information' to better understand the emergence of information-as-an-asset. I look to apply these laws in context of IoT since the data generated from all quantifiable sensors is 'information' in some form – visible or discrete. Why not find the maximum value out of the most potent weapon in our times? Information.

In addition to an unvalued asset, Moody and Walsh noted that hardware and software are mere mechanisms used to create and maintain information. Information provides the capability to deliver services, make better decisions, improve performance, achieve competitive advantage and can be sold directly as a product in its own right. They used manufacturing analogies:

  • Data is the raw material
  • Software and hardware are the plant and the equipment
  • Information is the end point that is delivered to the customer

I've included my own takeaways below from Moody and Walsh's "Laws of Information", in the context of the Internet of Things:

First Law of Information: Information is (Infinitely) Shareable

The World Wide Web fits with the first law of information. It's easy to explain how the internet has facilitated transfer and sharing of information without the loss of value to any of the receiving party. It's easy to imagine how "tangible" physical assets don't follow the same share-ability curve. The concept of the Internet of Things only multiplies the information proliferation several times. The same set of information captured through sensors and devices can be consumed by various parties and monetized independent of others. That, however, does not mean duplication of information multiplies financial value of the information set. Sensory information and machine signals can be interpreted in different ways and forms to draw out independent conclusions and decisions.

Second Law of Information: The Value of Information Increases with Use

The value of physical resources reduces with time. Your microwave or bicycle will depreciate with every use over time, thus lowering return to use. Fortunately, data or information doesn't follow this trend. However IoT industry needs tools and techniques to make meaning of the information fed into the decision-making engine. I also see a huge opportunity in the creation of business applications and platforms to make meaning out of this infinite set of information created by machines. How will the business model evolve in reference to the second law?

Third Law of Information: Information is Perishable

Value of information depreciates over time. Speed of loss of value depends upon the type of information. Real-time information processing and the need to analyse high-velocity data to drive immediate decision-making will differentiate a more agile IoT backend system with the rest. Imagine smart community sensors feeding energy consumption sensory data to the smart grid and the application layer predicting a possible power outage based on consumption pattern and real-time usage. Perhaps the third law is most relevant to mission-critical IoT applications than any other domain of Information Technology

Fourth Law of Information: The Value of Information Increases with Accuracy

Thanks to high velocity and volume of data emerging from various devices and sensors, the reliability of application-layer decision-making will improve. Given most urban informatics services will heavily rely on accuracy of such predictive systems, segregating signals from noise will be important. One wrong trigger can have catastrophic effect on the larger supply-chain system. I wonder how the business models will emerge based on data quality between two vendors claiming to deliver high-quality decision making through their analytics platform.

Fifth Law of Information: The Value of Information Increases When Combined with Other Information

Information generally becomes more valuable when it is combined with or compared to other information. Ability to relate two sets of information together is infinitely more valuable from a business viewpoint. In my last blog, I talked about IoT Industry consolidation since combined intelligence of various independent systems will be more beneficial or valuable for business as opposed to standalone units. Data sharing, collaboration and business partnerships between similar IoT service providers will start to emerge shortly.

Sixth Law of Information: More Isn't Necessarily Better

In many cases, the more the resources the better for your business, for example, finance, manufacturing capabilities, people, factories, etc. This isn't true for the information industry especially in reference to this limitless information created by the sensors/machines. How do you know when it is enough? Do you wait for 100% information before you decide? What confidence level will still let you make the right decision? Does the perceived value of information continues to increase beyond the overload point?

Seventh Law of Information: Information Isn't Depletable

In the traditional sense, the more you use, the less you have. However it isn't true for information. It's self-generating. IoT will continue to flood the decision-making engine by this non-stop data.

So how do you apply asset valuation principles to the emerging IoT Industry? How do you create business models that fits various applications of the IoT?

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