Is Data a source of value?

Posted: 2018-10-16

Author: Satyendra Rana

We have always been exposed to natural and man-made events and have wondered and been impacted by their outcomes. Our lives are shaped by the awareness of the phenomenon underlying the events we witness. We might find certain events to be favorable while others unfavorable depending on our interests and aspirations at the time.

Data is simply a descriptive representation of an event captured by a sensory device and/or an interpretive mechanism. Our ability to capture, represent, and share events have increased exponentially, causing an unprecedented growth in data. To survive and prosper in this new data rich environment, individuals as well as businesses are undergoing digital transformations of their conventional operating mechanisms. Such transformations are often guided by the conviction that data has value and thus must be managed like an asset, and more the better.

Data and the concept of value

Is data a source of value? To seek an answer to this question, one will have to first broaden our understanding of the concept of value and how and where does value emanate from.

The concept of value provides an internal reference for what one might consider as beneficial and desirable during the pursuit of their aspirations, and it may span ethical as well as economic dimensions. If a group of people or a business group have common aspirations, they may have a shared understanding of value as it applies to achieving those aspirations. But for the most part, the concept of value is subjective as individual aspirations differ and are often competitive.

Data and value are opposite concepts in fundamental ways. Data is an objective and static representation, notwithstanding the biases introduced by the limitations of the measurement mechanism. Concept of value is subjective dynamic, and contextual. The fact that it is raining today in Austin may be of value to me in deciding whether to pick up an umbrella or not only if I have to step outside today. Knowing about rain yesterday, or in Michigan may not be of any consequence.

Is it than proper to say that data has no intrinsic value in itself? As a rule, the answer is yes but there are few exceptions. To assert that data has intrinsic value in itself, is equivalent to saying that a static entity has always encoded within it a contextual and time-sensitive entity which seems quite paradoxical. So, what are the exceptions?

First exception is when data itself is an object of exchange in an economic activity for which the buyer is willing to pay, than data is a source of value for the seller. For a business which collects and sells data, data becomes an asset. This does not necessarily mean that the acquired data also has an intrinsic value for the buyer.

Second exception is better understood by the analogy of a seed. A seed is a static thing but it has embedded within it the potential for manifesting a tree which is a dynamic and evolving thing. In the context of data, it means that data in its encoding contains the intelligence for deriving value from itself. Most data we collect however does not exhibit this characteristic and thus have no intrinsic value.

Deriving Value from Data

When the data has intrinsic value by virtue of embedded intelligence, extracting that value is a simple matter of activating that intelligence.

In other cases, data has to be paired with other data and intelligence for value. The fundamental difference is that the value now gets attributed to the intelligence for value extraction than to the input data itself. The value extraction intelligence is contextual and furthermore may be self-evolving through built-in reflective and self-learning capabilities.

The above distinction between data, value, and value-extraction intelligence prompts the following observations:

  1. Data collection and management is much easier than developing the required intelligence for value extraction.
  2. Having indiscriminate and more data may hinder rather than support the value extraction process.
  3. Value from data is realized only when the value-extraction mechanisms are triggered in time.
  4. Keeping all data around could be a curse rather than a boon. It helps to have mechanisms not only for remembering but also for forgetting.

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