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The art of questioning data

-What do I have to do to get in? -asked Alicia again, raising her voice. -But do you really have to go in? -said the footman. That's the first thing to be cleared up, you know.

Find out more about the ability to question, explore and discover, transforming data into strategic decisions.

Gonzalo Abalo Álvarez

Reading time: 4 min

The world of data in companies today is extremely complex, almost a labyrinth where it is easy to get lost among so much information. But it is precisely there, among all that tangle of data and information, where the real challenge and the most exciting challenge lies: the ability to ask the questions that will guide us in the right direction. Asking the right questions of the data is essential for the company’s strategy, to find the best way forward.

-Alice, could you please tell me which way I should go to get out of here?
-It depends very much on where you want to go,” replied the Cat.

Ask relevant questions

The first step towards effective decision-making is to ask pertinent questions: What is the purpose of this decision? What information is essential to achieve our objectives?

There has always been data. Decisions (more and less) important have always been made on data. What changes now? We have much more data and much more capacity to process it. The problem is that more data and more processing capacity, more tools, does not necessarily imply better decision-making.

The greatest value of data, its true nature, is to bring value to the business. There is no point in making data-driven decisions if we are not clear about what matters to the business, if we do not ask the really important questions, the really relevant questions. The first thing we need to know is what the data should solve, what question it should answer.

-Alicia: How long is forever?

-White Rabbit: sometimes just for a second.

The ability to ask questions of the data allows them to reveal patterns, connections, trends… answers, in short, that help us to provide the necessary value.

We have to ensure that the data makes sense to solve the challenges we want to solve.

And for these data to allow us to answer the questions we ask them, we must have good data! It is essential to pay attention to everything that surrounds the data: collection method, standardisation, normalisation, security, traceability, classification, accessibility, visualisation, …

And to have good data we need a good structure of everything that surrounds it. The risk of treating data in the wrong way can lead to wrong decisions, and that is where everything can get complicated and we stop understanding the business and what it needs, we lose the ability to generate value.

“Never imagine yourself to be different from what you might have seemed or would have seemed to others if you had seemed to them not to be what you are”.
 -It seems to me that I would understand this better if I saw it written down, but as you say it I cannot follow the thread.

The relationship between causation and correlation

We often make mistakes because of the low quality of the data, because of the difficulty of consolidating several sources, several projects, different time frequencies, different formats, we want the data to give us the solution, and that is not always the case: the data will not show us only part of the way, we will have to analyse and understand the relationship between causality and correlation.

Confusing correlation with causation is a common mistake that can lead to wrong decisions and misinterpretations. In such a complex world, finding the single cause-effect of a phenomenon is an anomaly.

It is crucial to choose the right tools according to the type of problem. Predictive information can be valuable even if it does not imply causality. We need to understand which problems we can solve with data and which require improved prediction, needing a deeper understanding of causality.

We have to ensure that the data makes sense to solve the challenges we want to address. In very few cases will we see that the data we collect is sufficient to answer the business questions, we have to ask the most relevant questions and analyse the result in depth.

-But what are they for? -asked Alicia, in a tone of lively curiosity.

-To protect it against shark bites,” replied the gentleman. It is a system of my own invention.

On many occasions we believe that data is there to feed analysis, but in reality it is the continuous feedback and learning that implies making a differential leap in the use of data.

Remember that the important thing is not the data, it is to make the best decisions with them, always providing value.

The ability to question, explore and discover

The real magic of data management and strategy lies in the ability to question, explore and discover, transforming seemingly chaotic data into informed strategic decisions that deliver business value.

Thanks for reading! See you through the looking glass.


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