When Data visualization and Art Collide With the Humble Org Chart
By: Kirell Benzi
Tags: Data Science, Design Process, Organizational Culture, Data Art, Dataviz

“The only thing that is constant is change” — Heraclitus

Today in the business world, we talk about change. The advent of AI is transforming our entire society. Tech companies heavily invest in R&D to stay on top of the game while older industries are trying to catch up on their digital transformation.

There’s a widespread belief that companies which are successful in digital achieve their goals because they have the right internal structures in place. I am intrigued by how you can visualize these structures beyond simple org charts, and whether or not a tangible representation of them reveals insights into the way a company is managed.

As you would imagine, few corporations were willing to let me access their organizational chart under my own data art studio. My only option was to work as a collaborator in a large group to test this idea (among other things). As soon as I joined the Havas group, I got started on this pet project and was eager to discover how each business unit relates to another.

Spoiler: it turns out that the knowledge extracted from this analysis is extremely valuable and can drastically help to make informed data-driven decisions.

Getting the data

Havas recently migrated to WorkDay, an ERP for finance/HR SaaS for large organizations. One of WorkDay’s key features is TalentSpace, which acts as as an internal LinkedIn-type system, through which people can expose their title, physical location, company name, ways of reaching them and their boss: an ideal dataset for us!

Personal private view for each Havas employee

For those who fear leakage of private info, rest assured that as a regular employee, I could only access anonymized GDPR-compliant (no names) information with the consent of the HR department. Note that when I started working on the project not all the subsidies had migrated to the platform (hence the lower number of data points than might be expected).

My own personal hierarchy chain to the top!

As with all new data-driven projects, I started by agglomerating information. One point worth noticing is the gender balance of the organization, with more women in all four branches of the group, 56% to be precise.

Regarding the distribution of managerial functions, we can observe that the top-management is slightly balanced in favor of male executives with a turning at hierarchical level four (0 being the CEO Yannick Bolloré), which roughly corresponds to the executive committee of each individual digital agency that the group manages.

Of course, there is much more confidential information to be shown that I can’t share here, such as the distribution of job titles, the number of managers per agencies and at which level, the subsidies’ location of each agency and how they interact for instance.

When you start adding the job title in the mix, you can also anticipate the shortage/recruitment of talents you need to recruit to achieve your strategic goals.

This is just a bunch of examples but as you can imagine, it is extremely valuable and actionable info when your job is to manage and have a strategic vision of a company.

From data visualization to data art

Visualizing the hierarchy

So far we have talked about the value of collecting organizational info on a company. Let’s remember that we extracted a network connecting all employees to their direct superior. As you know, this simple one-to-one relationship does not necessarily reflect the real chain of command but it is already a good start to build a visualization.

Here is an attempt at revealing the hierarchical levels of the group using a radial tree layout.

A classic and very useful data visualization used to explore the hierarchy of the company from a central node (the root of the tree), here being the CEO. By counting the number of circles we can assess the depth of the tree: how many hierarchical positions we have from the lowest entry point (the interns) to the CEO. Each dot is employee, colored according to the group sub-branches such as Havas Health, Havas Creative, BETC or ekino.

The dataset is too complex to be able to visualize all its dimensions in a 2D representation. As a general rule in a network visualization, proximity on the image does not necessarily imply proximity in the data. In our radial tree, we can clearly see the different hierarchical layers, but we miss a sense of quantity. Indeed, most nodes are drawn almost on top of each other, making it difficult to assess the volume of employees per branch.

When dataviz is not enough

To solve this problem, we have basically two options: adding a companion data visualization (like the barchart on top) to indicate the volume per branch or per sub company or improve/modify our radial tree layout.

First, instead of having a circular shape we could put everything in line like a file system folder view. The problem with this one is that the list becomes very long and boring to look at: you probably need to scroll to see it correctly or unzoom it so far you won’t see anything.

Coming back to our radial chart, we also put more nodes on each line with no overlap and zoom out to even further away. The issue in this case, as with all angle-based visualizations, is that the human visual system has a hard time evaluating angles precisely and thus difficulty counting the number of employees. For the curious reader and avid dataviz designer, this observation led to the famous blog post: “Death to Pie charts”.

This problem is also the perfect opportunity to get creative in the dataviz itself and gradually enter the realm of data art. Because it is already a compromise between different visual features, we could as well introduce aesthetics and emotions in the mix!

To iterate over a design, the dataviz practitioner must ask him/herself questions that criticize the current implementation. For instance:

How would the audience judge its interpretability compared to the previous one?

Is the color palette appropriate for the data at hand?

Is the data-ink ratio adequate?

Does it look more emotionally engaging, if so why?

On top of that, other artistic concerns must be addressed such as:

What is the concept behind this piece?

Is there a sense of harmony, symmetry in it?

How does it compare to previous pieces, too much similar? Coherent with the series?

Is the shape supposed to be figurative or totally abstract?

Do the colors resonate with the tone and idea behind the piece?

Data art to the rescue

These questions led me to create this “fuzzy” radial tree.

A fuzzy radial tree displaying the hierarchy of the Havas group. While the hierarchical levels are harder to discernate, this data viz shows the total number of employees more accurately. Subjectively, it also offers a more interesting artistic shape like a multicolored iris.

A zoom on ekino France, where I currently work. Notice how ekino’s blue is mixed with orange. It is due to the different email aliases belonging to its former organization Fullsix. Hence, some points are still labeled as Fullsix’s orange instead of ekino.

While it is harder to count the number of layers, we have a better sense of the total number of employees and something which stands alone as a image for branding purposes. If you are interested in the technical details, it was created by using the previous radial tree and by applying a bit of a force-directed layout to it.

“Art is never finished, only abandoned” — Leonardo Da Vinci

Once I “finished” this fuzzy radial data artwork, I put it as my wallpaper and moved on to other projects for a few months. I knew it was not in its final stage, yet I had no idea how to drastically improve it. Improving one aspect, such as visual compactness, would make a regression in another, like the interpretability for instance. In addition, I was so used to see a circular representation for these types of datasets that I had a hard time imagining something else.

I had to start fresh, a blank slate so to say, to be able to come up with something new.

Breaking the circle of death

If you are used to working with graph datasets, you know that most layout algorithms have a tendency to create circular-like shapes. It comes from the fact that they try to minimize the distance from the center of mass of the network without overlapping too much.

In layman’s terms, it means that most mathematical formula researchers use to draw networks on screen are based on the same physics model and that it often yields a circular shape.

Despite my love for these circular shapes, I wanted to create something radically different and kickstart creativity without doing a ring.

My first tries were leaning towards isometric shapes, but being a 2D artwork (to be printed) introducing a false sense of perspective didn’t really work for me here. I gradually came up to this triangular shape that I find compelling because it is so unusual in the network visualization world. It clearly shows each individual employee of the group, organized into each sub organization as we had before.