When debating the internal value of data consider the following: How should we treat data so that it brings value to our organization?

To start, we must transform the traditional data value chain into a new value ecosystem. We accomplish this feat by reimagining how to manage both data, its uses and by treating it as an informational asset.

As we have discussed in previous articles, one of the characteristics of an asset is its capacity to generate future benefits. Therefore, if data is an asset, it is potentially a profit generator, and consequently one of the primary objectives for a company should be to manage data in a way that maximizes its value.

The five stages of the Data Ecosystem

To understand how we can measure the value of obtained data and transform it from capture to monetization, let’s analyze each of the five stages of the Data Ecosystem.

If we break down the ecosystem, we find five attributes that lead to eventual decision-making capabilities:


The value of data


  1. QUANTITY: The underlying question is: is more really better? We must be aware that for information management we must have a minimum. From there, we can build according to the different use cases. The next question we must ask ourselves is: what is the minimum? How does this minimum vary for each sector, company, and use case? 
  2. QUALITY: The quality of data for decision-making is impacted by regulations, i.e. GDPR. If customers do not perceive value and trust in organizations, they will not give up their data, which will ultimately reduce value. This is why ethics and the correct use of data are set to become a major competitive advantage.
  3. ACCESSIBILITY: Accessibility to information is closely related to our view on information consumption. Seen from another point of view: accessibility tells us about how we communicate and distribute the information. It also tells us about the culture of our organization.
  4. ANALYSIS: Use cases are the “raison d'être” of data. If the data we have is not used, why capture, clean, and store it? We must ask ourselves what it is we want from our data before organizing a management strategy.
  5. DECISION: If data and its quality are very relevant to provide value, the usefulness of what we do with it is certainly no less so. Utility, applied to uses, can be defined as the coefficient that improves the value of the data if we keep the rest of the elements of the information ecosystem constant.

In the world of data, It's imperative to understand its evolution. From a linear value chain to a multidimensional information ecosystem. The second publication in The Value of Data series gives you the keys to orient your data strategy towards generating value for your business. ↓