Data visualization: making the right decision at scale

Visualizing your data the right way is extremely important if you want to work in a data-driven way within your organization. Data Strategy Leader Louis de Roo explains why in the blog below.

Let me start with a disclaimer: writing about data visualization is like doing macramé about politics: you might manage to get your ideas across, but you keep expressing yourself in the wrong medium. This piece would of course have been much better with a brilliant set of visualizations to give my story some punch. The reason I'm writing about it anyway is that, like most of us, I'm not very good at visualizing data. Sure, perhaps I picked up a bit more of the underlying principles, and I've learned to recognize good and bad examples, but I am still definitely no specialist.

Is visualizing data an unnecessary luxury?

For most of us, visualizing data is a nice extra. Raised on Excel and familiar with the data in front of us, spending time and energy on 'making our data pretty' seems a bit of an unnecessary luxury. The numbers don't lie, right?

The uncomfortable truth is that there is a bit more to it than that. Indeed, numbers don't lie. But making numbers lie is a lot easier than it seems. We often do it unintentionally. And you don't have to be a shady accountant to make some of the information in the numbers disappear.

Why look at data?

Before I start a tirade against the cunning and deceit that slyly manipulates us by showing certain data and hiding other data, it is good to go back to the why. Why do we actually want to look at data? The basic idea behind data-driven working is that we can steer our organization by means of data. The follow-up question is perhaps even more important: how? Steering your company with data is one thing, but do you want to be the only one who understands the data? Or would you rather have your organization across the board have access to the relevant data, and make the necessary decisions based on it?

Data-driven culture

In a true data-driven culture, everyone in the organization has access to the data that is relevant, and everyone is able to make the right decisions based on that data. But the catch lies precisely in that 'being able': where you effortlessly keep an overview of acres of Excel lists, your colleagues may find that a bit harder. Simply because they don't look at the data every day, or have a slightly less sharp feel for the crucial values by which your process should be steered. Of course, with a lot of effort and time you can drill them in exactly what to look out for, but is that really the fastest route to a more effective approach? No company employs only trained data analysts, and besides: the work also has to get done. Preferably without too much delay.

A clear message

By playing with 'what' you show people, you can influence how they will react. In this age of fake news and conspiracy theories, that is not news. But within your own organization too, it is a simple fact that most employees will act faster on a clear, straightforward message than on a complex set of data. Making data and the decisions derived from it accessible and translating them is therefore an important step, and one that can lead to a much wider application of your insights than you could have achieved on your own. Clear messages, clear actions and clear appreciation for what is good or not good enough: visualization ensures that not only the sender but also the receiver understands what the data is saying. With good data visualization you reduce the need for other information transfer in your operational processes, process steps fit together better and everyone works from the same source data towards the same goal.

Visualization standard

An additional benefit is that choosing a good visualization of your data also forces you to think about your own values: What do you consider good and bad, what is important or insignificant? By choosing stronger logic when visualizing your data, you also come across exceptions in your process, which you can then do something about. A visualization standard is thus more than just a pretty 'coat' for your data: it forces you to make more soundly based choices in your business processes, to define clear measurements for your goals, and to take targeted actions and assign responsibilities.

If, as a manager, you don't want to start every working day by handing out a stack of orders to your staff, good data visualization is indispensable. Then it is only a matter of admitting that you aren't good at it, and seeking help.

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