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Roland Berger Consulting Slide Breakdown

by | May 15, 2021

Radar charts are a good idea in theory, but in practice they are inherently flawed and can easily be misused.

In this post I’ll be reviewing a slide from Roland Berger’s 2018 presentation, “Corporate Headquarters Study 2018” (source info below). I’ll explain what I think they did well, what they could have done better, and what we can learn from them about how to build an effective, consulting-style presentation.

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The presentation is all about the role headquarters should play in an organization, and this slide in particular says, “Companies that successfully execute CHQ capabilities are ranked among the top of their peers and deliver better performance”.

Roland Berger chart explanation

“Corporate Headquarters Study 2018” Roland Berger, July 2018

Essentially what they’re trying to communicate is that companies who focus on important CHQ capabilities, tend to also perform better. There’s a nice summarizing title at the top, which I always like to see, a big chart on the left, and then supporting details on the right. All in all it looks like a pretty standard consulting-style slide.

One thing you might have noticed right away is just how plain the slide is. There’s hardly any color at all aside from the lines in the chart. Anytime you build a slide you want to always be thinking about what your audience is going to notice in the first few seconds, because it’s your job as slide creator to guide your audience as much as possible, and color is a really easy way to do that. But of course it’s not the only way.

Here the way they’ve done it is by bolding the text, which you can see in the title and in the text on the right.

Roland Berger chart explanation

It’s not a bad thing to have slides with lots of text on them, especially for this kind of presentation, but you want to make sure you draw attention to the important parts, as they’ve done here. But then equally important, is drawing attention away from the less important parts, such as the chart description, and some of the text down at the bottom of the slide.

I personally would have liked to see a little bit more color, especially in the title. That would have helped it stand out a little more so that when I’m looking at the slide for the first time that’s what I read first. You don’t want your audience to jump right to the details, you want to give them an overview first, which is what your title does (But only if they actually notice and read it).

I also would have liked to see a little bit more bolding in the bullet points on the right. There’s no way I’m going to read through every one of them if I’m seeing this live, so a little visual guidance would have been appreciated.

Then lastly one minor thing, I don’t really like the spacing on the top and bottom of the slide. Not for any real logical reason, I just think it looks weird. There’s too much space on the top, and the bottom feels scrunched.

Roland Berger chart explanation

Alright now let’s talk about the chart, which is obviously a major part of this slide. Like I mentioned at the beginning of this video, radar charts are usually not a good idea, and I’ll explain why down below, but first let’s talk about this particular radar chart.

They’ve taken a set of companies and divided them up into different groups based on their performance. They don’t specify what type of performance they’re referring to, but for our purposes it doesn’t really matter. There is a best-performing group, 2nd best, 3rd best, and then a low-performing group.

Then each of those groups is assessed along a set of variables related to how their headquarters operates. For example, how good are they at providing talent to the rest of the organization? 1 being very poor, and 4 being excellent.

Roland Berger chart explanation

And to their credit, the takeaway here is pretty obvious. The best performing group, also tends to rank highest on each of these variables. There’s a nice correlation. Again, it’s not clear what “best performing” means – it could even be talking about the variables themselves, which would make this chart not very valuable at all – but assuming it’s talking about some other type of performance, it’s a pretty clear takeaway.

But in my experience, radar charts are usually not a good idea. They sound great in theory right? It’s an easy way to get a visual snapshot of a product or a company across a set of variables.

For example, if you have Product A maybe you want to see how it scores on things like price, reliability, ease of use, etc., Product B that you want to compare across the same set of variables. Right away you can get an idea for which product overall is better. In this case it looks like Product A shown in blue, might be the better choice.

Roland Berger chart explanation

Well there’s a few things wrong with this comparison. The first is that sometimes it’s hard for me to know which product takes up a bigger area, because our brains aren’t very good at comparing the size of two things that aren’t the exact same shape.

Let’s mix up the chart just a little bit, and say we’re now comparing two different products, Product X and Product Y. But this time, it’s not quite as clear which has a bigger area. Well actually, these two have the same total score.

Roland Berger chart explanation

Then on top of that, if you move the variables around in a different order, it can play with the shape quite a bit, making it even more difficult to compare. For example these charts all look different, but they were actually made with the exact same set of data.

Roland Berger chart explanation

Another problem with comparing the area of different data sets is that the differences are over-evaluated. What I mean by that is a small change in one of these variables, will lead to a relatively large change in area.

For example if I have two products, and one product scores 2 on everything, and another scores 4 on everything, then it should be considered twice as good right? Well, the area of the larger one is going to be more than twice as big as the smaller one. You see this same problem with pie charts.

Roland Berger chart explanation

With radar charts, you also have the subjectivity of the variables themselves. In this case we’re putting equal weight to each category: price, availability, and so on, but that might not necessarily be the case. You might value one much more than you value another.

It’s even worse when they’re not on the same scale like they are here. For example, if we were comparing two companies you might have one variable that was sales, another that was stock price, or another that was total number of employees. But those are obviously all very different, and they shouldn’t be given the same weight to determine how valuable a company is.

One thing a radar chart is good for is comparing multiple things one variable at a time. For example back to our product comparison, it’s easy to see who is winning on each individual variable.

Roland Berger chart explanation

Product X has better reliability, but Product Y has better performance. That’s very clear. But where it’s more difficult is when you have to compare across variables. For example, in this chart it’s pretty hard to tell which is rated more highly for Product Y – reliability or performance. The gridlines help of course, but it’s still not very intuitive.

Alright so let’s now go back to the slide and take a look at the radar chart again. Again, radar charts are good for comparing one variable at a time, which this chart doesn’t really do. Instead, they focus on comparing the area of each group, which usually doesn’t work very well for the reasons I already mentioned.

Roland Berger slide

But, despite all that, it still sort of works here. The reason why is because the differences between each group are very obvious. It’s very obvious that the best performing group scores higher on every single one of these variables than even the 2nd best performing group. And in fact, there aren’t even any overlapping lines in the whole chart. So the takeaway is very clear.

But if your data isn’t abundantly clear as it is here, I would advise against the radar chart. If you’re just trying to see which product has the better overall score for example, and you don’t care about the weight of each category, you could just use a simple stacked bar chart. This would let you see which did better overall, while also seeing the individual scores for each variable.

Roland Berger bar chart

Or if you wanted to focus on how each product does for each category, you could put them in a set of clustered bar charts, which would show the scores and winner for each variable.

Roland Berger bar chart

In truth there are probably a lot more options in addition to this, and like I mentioned, the use of a radar chart in this slide is not a major mistake, but the overall takeaway still remains: Radar charts are a good idea in theory, but in practice they are inherently flawed and can easily be misus

You can watch a video version of this article on YouTube.

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