Data-driven tips: avoid spreadsheets and optimize data storytelling

In our year-end blog of 2022, we already wrote that spreadsheets are something to avoid if you want to increase the impact of your data as an organization. But how does that actually work? In this blog, Data Strategy Leader Louis de Roo explains it to you.

Sorting, organizing, and categorizing

First of all: as humans we tend to want to organize complex information flows. This organizing helps us interpret the information faster, because by focusing on the deviations in the resulting pattern we can quickly identify the right data points. By sorting, organizing, and categorizing our data, you find what you're looking for faster.

The downside of wanting to find something is that you'll often have to search for it. And anyone who has ever helped their partner find a lost set of keys, phone, or wallet at home can confirm that one person's search logic can be radically different from someone else's. It's no different with all those sortings, categories, and arrangements: to find what you're looking for, you're completely dependent on someone else's categorization. And just like your socks mysteriously disappear when your partner has done the laundry, you quickly lose track of the information you needed in someone else's list.

It's therefore logical that when working with data, you quickly start making your own spreadsheets. Enter a jungle of different little Excel files… each with just as many versions of the truth.

Logic

Of course, it would be ideal if everyone applied your logic when looking at a list of data. And that they not only look for deviations with the same lens, but preferably also draw the same conclusions from that list as you do. That chance, however, is slim, and the chance that you'll trade your effectiveness and decisiveness for discussion about the data and its interpretation is all the greater.

The solution, of course, is to make sure your data consumer has no choice but to go along with your logic. In the past it was quite a challenge to ensure that your data was visualized the same way every time so that there was no doubt about its interpretation, but for quite some time now, with a few good data visualizations, you can easily transfer your own search logic to your intended audience.

Data Storytelling

This so-called "Data Storytelling" is essentially nothing other than pre-sorting the data for your audience. What do you want them to see? What conclusions do you want them to draw? By visualizing your data smartly and clearly, you make sure there's no longer any doubt about the conclusion. Additional benefit: your users need much less time to get started based on the data, and it's much easier for them to share the conclusions with colleagues, so the desired information spreads faster within your company.

To achieve this properly and without misunderstandings, the most important thing is to try to translate your own search logic into a concrete set of parameters. What exceptions do you look out for? What do you look at when you're searching for deviations in your list? Once you have that logic clear, it's a matter of creating a clear setup for communicating your data. Think of a data house style for your organization, or at least maintaining a number of basic principles when publishing your data. This naturally creates a clear and unambiguous picture, with corresponding decisions — based on data!

Written by Louis de Roo
Data Strategy Leader
E-mergo