Why So Many Ws?
When creating a data visualisation, whether its Tableau, Power BI or even Excel (please don’t use excel). Answering ‘The Four W’s’ is how I set myself up to be able to give a unique perspective on the data. There are 4 questions that you need to be able to answer before even touching your Dashboard/Report. And answering these questions will save you from a hell of a headache later on. When you present your visualisation to a room full of critics.
The What?
‘The What’ gives you a solid foundation to build from and minimises the risk of holes in your story.
— What is the purpose of this Analysing this data?
This may seem simple at first. You may be thinking- ‘my boss gave me this dataset to analyse on the sales from the company’. Easy. But is that going to wow anyone? I sure hope not. To delve a little bit deeper into ‘The What’, you need to find the intricacies that will make your viz pop.
Start of course with your KPIs or key points. Then go a little bit further into some of the finer points, can you utilise your data by interconnecting different areas to fill in any gaps.
Really make sure there’s no cracks in the foundation. You don’t want your Viz crumpling when you get to the top.
With this in mind, make sure you’re not straying away from the initial task and adding unnecessary information.
The Who?
This is all about know your audience.
— Who is this analysis for?
‘The who’ is all about knowing your audience and how you’re going to present the data. You need to have the bread and butter,
Having the ability to explain an idea or concept to a range of different audiences is an invaluable asset to your arsenal as a data analyst. This skill is the bread of ‘the who’.
But the butter? That’s being able to identify your audience and adapting the way the data is being presented to engage the audience. This may sound like a monstrous task on the first read, but it could be as simple as changing your chart types or using industry specific terminology.
The When?
‘The When’ sets the stage.
— When will this analysis be used?
Another question which is deceivingly straight-forward. While although yes, you can answer this simply as it’s for ‘x person’ at ‘x company’ and it’s ‘due in x weeks’. Delving a bit deeper and reading between the lines offers you an upper hand in ensuring your visualisation is well received.
Knowing when your analysis is going to be used is another key piece in knowing your audience. The main question which needs to be answered is- How is the data being used? This will provide insights as to how the data should be displayed to get the full picture.
An example, If the visual is only being visited annually, you may not want to have daily insights. On the flip side, if it’s being used weekly, they will likely need daily insights and a 5-year trend maybe not be as relevant.
Ensuring how the data is displayed in reference to ‘the when’ is the key to setting the stage.
The Why?
This is what’s going to wrap your analysis in a neat little bow.
— Why is this analysis being done?
I know I referred to it as a ‘neat little bow’, but ‘The Why’ is arguably the most important question you need to answer. This is the whole purpose of the analysis.
The why is all about answering the question that was initially presented to you. Why is this happening in my data? Why is ‘A’ my best performer? Why is ‘B’ underperforming despite ‘C’? In order to truly understand the data, ‘The Why’ must be answered. Otherwise, you haven’t truly analysed the data.
It is important to understand, sometimes your answer may be ‘I don’t know’, which is okay. It’s better to be hesitant than blindly confident.
When your answer is I don’t know, this is when you explore how to answer, ‘The Why’. What are some supporting pieces of data which may be able help you answer the why.
If you have to come forward with a visual that doesn’t answer the why. Ensure you’re providing context as to how the question could be answered.
Why So Many Questions?
I know it may seem like a lot of questions to answer before even starting, but most of time you answer these questions naturally. This blog is more of a checklist just to ensure you have missed any massive Qs. That sometimes are missed when you dive straight into the data.
I would recommend trying to answer these questions then compare them with your end product. They won’t always line-up perfectly as you delve into the data and learn more about it. But as long as you’ve answered, ‘The Four Ws’, you’ll have a solid analysis that will raise eyebrows.
