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Eva M. Corral Presales Data & Intelligence

How mature is your organisation's data management?

That the pandemic has accelerated the process of Digital Transformation of private and public organisations is not news. The fact that the time lag to advance in this Transformation has been shortened is a clear reality, we have been forced by the situation. But how far has this process progressed in each of these organisations, and more importantly, how has this Transformation process been managed?

One of the ways of knowing this is by analysing the degree of maturity in data management within these organisations, which will allow us to know how integrated technology, processes and people are.

But, before we get into how to obtain this measure, let's start by getting to know the different degrees of maturity of an organisation's data management.

Data management maturity models

Let us think from the point of view of the value of data as strategic assets of the organisation. Then, that is to say:

  • Are they used in the organisation?
  • When the data is exploited, do they provide key value in strategic decisions?
  • Are those who use them able to interpret what they are saying?
  • What is their quality?

Because we know that most organisations generate data and that its growth has been exponential in recent years, but are we getting key strategic value from it?

With these questions in mind, let's look at which of the following levels of data management maturity your organisation is.

Although there are several reports and methodologies that define what the possible levels are, here we will simplify them all into one to understand these concepts and then explain how Izertis helps private and public organisations to be at the highest level.

In the figure above, we can see that the greater the integration between people, processes and technology, the higher the degree of maturity. But what identifies each of these levels?

Inactive

The organisation has data scattered in different silos, but there is no management of them, their usefulness, quality and origin are unknown, so they lack potential. The most that is done is to create some departmental reports that require manual action to generate and distribute them.

Organisations at this level are clear that in order to improve their objectives, it is necessary to boost data management.

Reactive

The organisation understands the importance of the data, but it works in information silos, so its usefulness and quality remain unknown, although the origin remains within the department. They cannot be used at a strategic level, although they solve certain departmental needs.

Organisations at this level are aware of the importance of data at a global level, but there is no plan, no strategies, no methodologies, or dedicated resources

Organisations at this level are aware of the importance of data at a global level, but there is no plan, no strategies, no methodologies, no dedicated resources, however, they are starting to think about this cultural change around data.

Proactive

The organisation has a clear decision to implement a data governance transformation programme. New profiles or figures emerge within the organisation dedicated exclusively to data management. Technologically, the necessary tools have been incorporated to cover the complete data life cycle. Moreover, these technologies facilitate its exploitation at the level of strategic decisions and time-to-market.

Optimised

The organisation already has data governance in place. There is a dedicated data management team. Business decisions are made based on the recorded data.

These organisations are Data Driven and many of them were born with this objective in mind, to get business value from data.

Now that we know the different maturity levels, which one is your organisation at? If you are not clear about your answer, Izertis can help you to obtain this metric through an Assessment of your current situation, the AS IS Assessment. Our Data Governance experts will carry out a global study to assess the current state of your organisation's data management. Once the results are in, you will know how to become a Data Driven organisation, but we will tell you about that in our next post on "How to become a Data Driven organisation".