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Data Literacy Mindsets: The Importance of Challenging Assumptions

Kevin Hanegan, Chief Learning Officer, Qlik & Chair, Data Literacy Project Advisory Board


Have you ever heard the quote: “We don’t see things as they are, we see them as we are”? Assumptions are necessary and we all make them every day. But they can also be dangerous, both in our personal and professional lives. This is why it is important to learn how to challenge assumptions.

Have you ever heard the quote: “We don’t see things as they are, we see them as we are”?

This is the perfect introduction to this blog, and our Data Literacy Mindsets blog series. People aren’t perfect and we often don’t have the context for everything that happens around us. We’re also emotional beings that make judgements based on past experiences and what we see happening around us in real time. But at some point, we hit a knowledge threshold where we don’t have all the information needed to make a decision.

Let’s look at this another way. Imagine your brain has enough information to uncover 50 pieces of a 150-piece jigsaw. Based on your previous experiences and beliefs, you fill in the blanks for those missing pieces. Most of the time this is somewhat accurate, but sometimes it isn’t and we make assumptions or jump to the wrong conclusions based on the limited knowledge we have. This could manifest in an action or decision that we make time and time again which is wrong, but is so ingrained that we don’t even realize we’re constantly making the same mistake.

Assumptions can be dangerous 

Don’t get me wrong, assumptions are necessary and we all make them every day. But they can also be dangerous, both in our personal and professional lives.

Firstly, let’s examine what assumptions are. Assumptions are inferences and meanings we assign to the observed facts based on values, needs, vested interests, and experience. There are two types of assumptions:

  • Implicit assumptions: these are not said out loud. They haven’t been articulated by you or by someone else. They are influenced by our personal experiences and backgrounds. A very basic example could be if an organization is working with a mix of paid employees and volunteers. There could be an implicit and again, unstated assumption that the paid employees are the real experts, and therefore better at their role than the volunteers. It’s never stated, but it could be easily assumed.
  • Explicit assumptions: these have actually been expressed and shared. They’re still the same assumption, except they’ve been overtly brought into the thought processes of those observing. For example, if an organization has a written policy that says only people with a certain job title can check datasets, the explicit assumption is that those without that job title are less skilled and unable to do the work.

But the world is changing at a faster pace than ever, which can lead to big problems. A lot of strategic assumptions are made based on evidence of how the world worked yesterday, and not how it works today. That’s why it’s critical to not only acknowledge these assumptions, but to challenge them. To do this, we can use the following steps:

  • The first key thing to do is recognize that everything is a perspective to us. What I assume could be very different to what you assume, and by this logic our whole lives are shaped because of these differing experiences. I would go as far as to say the one and only truth of a situation doesn’t really exist. Therefore, it can be useful to list all of our assumptions, even the ones that are implicit. They are arguably even more important to expose early on in any decision-making process, so they’re acknowledged from the very start.
  • Once you bring those assumptions to the fore, you can start to challenge them by reframing them from a statement to a question. Instead of saying “this is not true”, we should reframe to “how could this not be true?”.
  • Once we reframe these assumptions, we should try to make the challenge a reality or even an opportunity. A good tool to use is the ladder of interference – a tool that explains how we make decisions. The ladder of inference works by placing us at the top of the ladder and asking us to work backwards to recognize the initial assumption and belief. Before you take action, you can ask “am I drawing the right conclusion? Why did I assume this? Is my conclusion based on facts? Can I do it in a different way?” It gives you good context for how you might be able to climb down the ladder and put yourself in a position where you’re not stating something that could be misunderstood or incorrectly assumed.

We all have assumptions, but by carefully the selecting inputs and scrutinising the outputs that inform our decisions, we can draw conclusions and incorporate individual preferences and beliefs without making assumptions. Being fully aware of each step on this ladder can prevent the wrong decisions from being made.

Look out for the other posts in our Data Literacy Mindsets series. If you would like to learn more about how to challenge your assumptions and draw the right conclusions that drive impactful decisions, check out the resources via the Qlik Continuous Classroom.