Author: nsanka

As a citizen of a country and a tax payer one should always be curious to know how their government is spending. Usually, government spending includes all government consumption, investment, and transfer payments.

Every government releases their annual expenditure report and few of their visualizations can be misleading. Let me introduce to a viz called packed bubble chart, the size of the bubble represents the scale of a metric. Simply, larger the bubbles –  larger the values.

Image 1.0 is a reference to a government’s spending in a year. They have spent close to $3.7 Trillion, yes it’s trillion it involves 12 zeros. That’s the huge amount spent by a government body, you could put 8.33 million people through all four years of college with $1 Trillion.

 

 

There are multiple drawbacks of this visualization, the amount spent varies by a scale that is thousands, millions, and billions. In image 1.0, all the expenditure are plotted on a single scale, it’s quite hard to visualize or know what kind of expense it is? The expenses which are in thousands or millions look quite small on this chart.

Secondly, targetted audience should be analyzed before preparing a dashboard. In this case, an FP&A (Financial planning and analysis) head will like to have a bird’s eye view. Where an HR manager would focus on headcount expenses. So, it’s better to who are your targetted audience in advance.is no category of expense, such as defense, administration etc.

There is no proper segmentation of departments. For an instance, there are multiple defense expenses and they all scattered. It’s quite tough to compare the overall drop or increase in defense segment.

The red color in the viz denotes that it has the highest drop in expense compared to last year. There is quite a long range of colors used and it’s difficult for us to interpret them in numbers.

How can we make this viz better?

Creating segments of expenses and form clusters to group them together. Legends should have only three to four to distinguish the scale of expenses so we can simply classify. Prepare dashboards based on targeted audience and restrict them to their respective departments to be accesed.

Source of the article: https://www.pinterest.com/pin/490822059366478830

Nowadays people are working on n-dimensions for a better understanding of data and to get accurate insights. However, an infographic with more than 2-dimensional representation will misguide a user and even creates difficulty to understand.

Let’s walk through a classic example of this scenario, image 1.0 is a column chart but in 3-dimensional representation. It tries to depict sales of widgets monthly, there are 16 widgets that are being sold for 11 months of a year. At first glance, the chart looks really cool with column coming to life and appealing.

Problems: Aesthetic scenes, Distortion, Accessibility.

Let’s take a step back and understand few things before we go ahead, who are the targetted audience and what do they need? I guess that’s for Sales managers who would be the targetted audience for this kind of report. The information they look for is sales for each product, in this case, a widget for a time period (Weekly, monthly or yearly). This list can extend to the region, geo this list goes on.. and is totally dependent on the kind of business a company own.  In this case, all the information is being depicted correctly in this chart but by using a wrong viz.

From a viz developer point of view, aesthetic sense plays a major role in increasing usage. This claim can go wrong if we use a 3D chart which is beautiful and appealing to one’s eyes. As this chart doesn’t help to understand data for the months from April to November as they all overlap on each other. Secondly, there are too many legend colors which create lots of confusion to the reader. In addition to this, we can see that color changes when there is an overlap of bars.

Coming to the metrics that are depicted, they do not reflect any figure of sales i.e. in millions or thousands, as a sales manager one would be really interested in those figures.

Accessibility plays a major role in navigating or drilling through the reports, which is missing in this report. Image 2.0 is a sample sales report which shows how line graph can better interpret sales figures than column chart. Secondly, when you hover on the line we can see the actual sales numbers which give an exact idea of how the team is performing and are the targets met.

Segmentation of products into multiple categories is very important to compare. In image 1.0 we can see that there are more than 15 widgets, they are high in number to compare.

Finally, a person working on viz should first understand who are the audience, what data are they looking for and at what granularity. Interpreting in 3D viz looks and sounds cool but it doesn’t serve the purpose.

Visualization has been a key to depicting lot’s of information by occupying limited space. But, is it been used incorrectly and unnecessarily? Did you ever come across fancy visualizations which convey simple information?

Recently, I came across an article about Drinking ages in Canada and found a viz which portray states with their legal drinking ages. The bar(Image 1.0) has provinces on X-axis and age on Y-axis, we can clearly see that apart from B.C, Alberta, and Quebec rest of the provinces drinking age is 19. This information was explained in a one liner statement. So, the question is do we need a Viz or how can we show it in a better way?

There are multiple flaws in this viz, let’s discuss them in detail. The Y-axis tick label which refers age have a scale of 0.6, usually all the legal permits are made to a certain age which is an integer rather than a running age. Secondly, age will not be in the base of 10s and a year forms from 12 months. In order to rectify the scale, we need to modify the chart to show age in integers like 17,18,19 etc.

Coming to grid lines used in the chart(Image 1.0), they are not necessary. The data we are showing is not varying in decimal values and doesn’t fluctuate and we need to keep in mind that age usually doesn’t vary a lot.

Overall, there are only three provinces which have legal drinking age 18 and rest are 19. Therefore, a bar chart to depict this is a wrong choice or not alt all needed.

What are the ways by which we can improve this chart? If you have any ideas please fell free to add it to comments.

I have a couple of ideas to address this issue, Image 2.0 is an example to show regions, which can be replicated for our requirement. We can denote the legal age of 19 as Orange regions and rest in blue for the legal age of 18. In this chart, the regions are quite clear and the names on that can easily be highlighting.

The second option would be to use a simple table which will be easy to read and understand.

Finally, did you reach to a conclusion to use a viz or not in this scenario? Let me help you, first try to analyze data and do some profiling. This will help you to decide to take a call for viz or no-viz. Secondly, a better understanding of data you have so that you can plan better. If you plan for a chat then the choice of the chart and the way it has scaled should be taken care because it will have a great impact on readers. Else, a table is always a good choice.

Reference – http://www.parklandonline.com/drinking-age-will-remain-19-in-saskatchewan/

Nowadays many visualization enthusiasts are coming up very innovative graph and charts to depict data to their targeted audience with the right information at right time. But a question that arises is, are these viz enthusiast trying to compress lots of information into a single viz that looks like an artifact rather than an infographic.

To better understand this, let me introduce you to a viz which looks super sexy and appealing to the human eye.

What’s the first impression one get’s by looking at this chart? Wow! that really looks cool. A famous idiom “A picture is worth a thousand words“, which tells complex ideas can be depicted using a single image. Any clue what does image 1.0 depicts?

The viz is a snapshot of Android phone release and their sales. The treemap depicts multiple things, by going from right bottom to left top of image 1.0 the size of each rectangle indicates the market share of an Andriod phone model, that signifies the dominance of a specific model and company which has several phones in the market.

Background on Treemap, this is a type of information visualization which is used to display hierarchical data using nested rectangles.

The best part of this viz is that a layman can a understand that Galaxy s3 was having lead in the market but there were many android based phones which cover at least half of the market. If we try to show the same information in a pixel perfect report it would have occupied at least ten pages.

To be very honest, without any description or brief about the viz it would be quite difficult to digest as it has lot’s of information compressed. To better understand or viz this data I would first try to understand who are the audience? How much data do they want to see? What is the granularity at which they want to analyze? Once we have all this question answered, we can decide what is a suitable chart or graph to represent data. For an instance, let’s say a sales guy from Andriod team wants to use this data. Now, we can start thinking what would be the best way to show data.

For an instance, let’s say a sales guy from Andriod team wants to consume this data. Now, we can start thinking what would be the best way to show data. I would create three buckets of all the Andriod phones and classify them as small, medium and large segments and assign a market share of <10%,>15%,>30%. By using this technique a user can better analyze the data which is present in the right half of image 1.0.

Now we can viz these buckets in many ways, First way: Use word cloud for all the three buckets and portray in a single frame. In this viz all the major companies each segment can be evidently showcased.

Second way: Using bar charts and the same concept to split data into three segments. These

As we discussed before, more information in a single viz which cannot be digested easily doesn’t solve our purpose. So, it’s better to enable drill downs to navigate to more detailed information from a main viz.

To conclude reports or charts like image 1.0 are visually attractive but they don’t fulfill business needs and decision making information.

So, Now you can comment whether you’re interested in Infographics or Artifacts?

Reference Article for Treemap (Image 1.0) – https://www.theguardian.com/news/datablog/gallery/2013/aug/01/16-useless-infographics#img-6