Radar Charts (Spider Chart)


What is Radar Chart? A radar chart graphically shows the size of the gaps among five to ten performance areas. The chart displays the important categories of performance and makes visible concentrations of strengths and weaknesses. The relative position and angle of the axes is typically uninformative. Radar charts are visually striking, and can add interest to what would otherwise be a dry data presentation.

Generally used with

– To visually depict the incremental improvements over a period of time

– To measure performance against benchmarks

– As a visual snap shot of progress over several criteria


The following points need to be kept in mind while designing Radar charts.

– Also, with many data points, it becomes difficult to identify the values. In those cases, petal charts are used.

Industry Specific Example?

– Used to plot a players weakness & strength

– Control of quality improvement to display the performance metrics of any ongoing program

– Comparing various cars based on their fuel efficiency, manoeuvrability, pick-up and engine power

Marimekko Charts – Data Visualization


What is Marimekko Chart? A Marimekko chart is a two-dimensional 100% chart, in which the width of a column is proportional to the total of the column’s values. Data input is similar to a 100% chart, with data represented as either absolute values or percentages of a given total.

Marimekko charts are widely adopted in Marketing for example to analyze customer segmentation and market segmentation.

This graph encodes two quantitative variables: one using the height and one using the width of the bars. For example – By attending to the heights of each bar segment, we can see what percentage of each company’s total sales were handled by each of the three sales channels. By attending to the widths of the bars, we can see the relative magnitudes of each company’s total sales. Each company’s sales in each individual channel is encoded through the areas of the rectangles (that is, the individual bar segments).

For instance, comparisons between Reebok’s U.S. sales and Adidas’ International sales can be made by comparing the areas of the two rectangles that represent them.


The following points need to be kept in mind while desiging Marimekko charts

 – Bars should be of the same heights

– Values in the columns to be preset in the percentage format

 Disadvantages of Marimekko Charts?

– Viewing graph as a whole is fine & reveals a lot of insights, but when we want to make comparisons between individual specific boxes, that is generally difficult.

– Marimekko graphs suffer from a problem that plagues any stacked bar graph: It is difficult to accurately make comparisons of the width or height of boxes that are not arranged next to one another along a common baseline.

Industry Specific Example?

– Generally used for marketing analysis all competitors in a particular market segment and individual share of competitors in each of the market segments. For ex – market share of three mobile handset makers (Nokia, Samsung, Motorola) in three segments (feature phone, smart phone, basic phone) and the share of each segment in the market itself using Marimekko charts



What is Bubble Chart? A bubble chart is used to visualize a data set with 2 to 4 dimensions. The first two dimensions are visualized as coordinates, the 3rd as color and the 4th as size. Bubble charts can facilitate the understanding of social, economical, medical, and other scientific relationships.

Bubble chart is often considered as an extension of scatter chart with the size & color factor also being introduced.


Human visual system can feel the difference in the size, but with change in the radii (3rd dimension or variable), the corresponding change in the area is non linear. Hence proper care must be taken so that the change in the area is liner by mathematically altering the change in the radius according to the variables value.

Industry Specific Example?

– Project management to compare the risk and reward among projects. In a chart each project can be respresented by a bubble,the axis can represent the net present value and probability of success and the size of the bubble can represent the overall cost of the project

– Revenue contribution from different products & sales

Example of a Bubble Chart Usage

Pie Chart – Data Visualization


What is Pie Chart? A pie chart (or a circle graph) is a circular chart divided into sectors, illustrating proportion. In a pie chart, the arc length of each sector (and consequently its central angle and area), is proportional to the quantity it represents. When angles are measured with 1 turn as unit then a number of percent is identified with the same number of centiturns. Together, the sectors create a full disk. It is named for its resemblance to a pie which has been sliced. The size of the sectors are calculated by converting between percentage and degrees or by the use of a percentage protractor. The earliest known pie chart is generally credited to William Playfair’s Statistical Breviary of 1801.

When to use :

Its recommended to be used when a piece is to be compared with respect to the total.

Pie charts work particularly well when the slices represent 25 to 50% of the data, but in general, other plots such as the bar chart or the dot plot, or non-graphical methods such as tables, may be more adapted for representing certain information.

Do the parts make up a meaningful whole? If not, use a different chart. Only use a pie  chart if you can define the entire set in a way that makes sense to the viewer.

Are the parts mutually exclusive? If there is overlap between the parts, use a different chart.








Difficult to compare individual pieces

Do you want to compare the parts to each other or the parts to the whole? If the main purpose is to compare between the parts, use a different chart. The main purpose of the pie chart is to show part-whole relationships.

How many parts do you have? If there are more than five to seven, use a different chart. Pie charts with lots of slices (or slices of very different size) are hard to read.

– While designing pie chart, make sure that slices are mutually exclusive; by definition, they cannot overlap. The data therefore must not only sum up to a meaningful whole, but the values need to be categorized in such a way that they are not counted several times.

Research suggests that we look at the angle in the center, essentially reducing the chart to just the crossing lines there. We are not very good at measuring angles, but we recognize 90 and 180 degree angles with very high precision. Slices that cover half or a quarter of the circle will therefore stand out. Others can be compared with some success, but reading actual numbers from a pie chart is next to impossible.

Industry specific examples of Pie Chart Usage :-

If a company has five divisions, and the pie chart shows profits per division, the sum of all the slices/divisions is the total profits of the company.

Pareto Chart – Data Visualization


What is Pareto Chart? Pareto chart is a data visualization tool which contains both bars & line graphs. In this, individual values are represented in decreasing order by bars & the cumulative total is represented by the line. Its named after Vilfred Pareto, an Italian economist and sociologist who conducted a study in Europe in the early 1900s on wealth and poverty. He found that wealth was concentrated in the hands of the few and poverty in the hands of the many. The principle is based on the unequal distribution of things in the universe.

Pareto Chart Example

When to use : Whenever we are having a number of factors, then pareto chart is used to highlight the relative importance (since the bar graphs are also arranged in decreasing order).

See the typical use cases highlighted below

– Used in customer care to show the most coomon customer dis-satisfaction factors

– Can be used in quality control to show common source of defects

The Pareto chart is generally used to you focus your improvement efforts on those issues that: 1.) Cost the most or 2.) Pose the highest risk / liability or 3.) those areas that occur the most often.

Dos & Donts :

If used properly, pareto chart can help a lot in understanding the key factors. The below mentioned factors are to be kept in mind & if used in conjuction, can provide a lot of actionable insight

a. Sub division :- It means, lets say at a customer care post using pareto they have found out that from a specific location maximum complaints are coming. Now, ideally they should further design a pareto for that specific location to get more insights (like in some cases there might be some complaints from a specific part of location because of some miscellaneous factor etc)

b. Multi-perspective analysis :- We should also do a multi-perspective analysis for ideal insights. For examples – if we take above case, not only they should do an analysis location wise but also reason wise & service wise etc. This might give them specific reasons for specific locations & hence counter measure can be taken to sort out the matter.

c. Repeast Analysis :- This depends on case to case or industry to industry basis, but based on their true knowledge & how they think the data dynamics are changing, the pareto charts should be updated & redesigned.

This is generally know as first level pareto analysis, second level pareto analysis (this is pareto analysis of the first bar of first pareto analysis) & third level pareto analysis (this is pareto analysis of the first bar of second pareto analysis)

Industry specific examples of Pareto Chart Usage :-

Below mentioned are some of the real world example usages of Pareto chart usage in industries & business organizations for data visualizations & analysis

  • Marketing – Where are the majority of my advertising dollars going? Which channels produce the most sales leads?
  • Healthcare – What types of infections are the most prevalent? What procedures are associated with the majority of return hospital visits?
  • Sales – Does a small percentage of customers account for a large percentage of revenue? If so, which ones?
  • Customer Service – How can I improve customer satisfaction? What do customers complain about the most?
  • Manufacturing – What defect types are most prevalent & key to improving an inspection process etc

Dashboards & Designing a good Dashboard

A picture is worth a thousand words & when spoken in IT paradigm, a dashboard is worth thousands of GB of data.

A typical definition of dashboard is
“An easy to read, often single page, real-time user interface, showing a graphical presentation of the current status (snapshot) and historical trends of an organization’s key performance indicators (KPIs) to enable instantaneous and informed decisions to be made at a glance.” – source Wikipedia

The concept dashboard originated from automobile dashboard, where driver can look & get all the required information like speed, distance travelled, RPM etc.
Dashboards have became a very critical & important tool for not only CXO but also mid level managers & any other employee for that matter. A normal data will not make sense to any person, & dashboard is just the perfect tool to help a company & employee to make sense out of the humungous data & to draw insights from it. This data can be from multiple softwares like ERP, HRMS, CRM, web service etc. The key benenfit which dashboards gives is

–  View performance information in a graphical format that enables the ability to quickly identify performance issues and study the root causes behind an anomaly.
–  View performance information in an organized format aligned around key goals and objectives.
–  Deliver more timely information by moving away from costly manually intensive    methods of integrating and disseminating information.
–  Dashboards helps in better decision making by reducing operational inefficiencies.
–  Improved bottom line by reducing cost
–  Rapid problem detection, escalation & resolving

A dashboard is not useful until & unless it is linked to the vision & mission of the company. It should be linked to historical data & provide insight. There should be a high level of interactivity in the dashboard, there should be alerts, hover information, drill down & drill through capabilities. Also, a dashboard has to reflect the right KPIs which are relevant to the specific industry & also specific department. In general, finance sales HR & manufacturing are the departments which are found to use dashboards the most in comparison to others.

Dashboards Deliverables Expected :- Generally, below are the most commonly expected deliverables which are supposed to be fulfilled by any dashboards
– Historical information to be present as well
– Information to be upto date
– Customized view according to the department & sector
– Access levels – Security to be implemented
– Mobile capabilities – In today’s world, with more & more of the workforce being on the move, its very essential that the dashboards can be accessed by even a mobile, ipad & tablets
– Interactivity- The dashboards should have high level of interactivity like drill down, drill through, hover capabilities


Designing a good Dashboard :- while designing a good dashboard, the following points have to be kept in mind

– Dashboard should be simple & communicate easily with an end user
– There should be the best use of data visualization techniques so that in one look, end user should comprehend what is happening
– Utmost care should be taken in order to ensure that the most important information is made to stand out as compared to others
– Those text should be put in dark which has to be highlighted (like problematic are or exceptionally good performance)
– Icons draw more attention & hence can be used optimally
– wherever & to whatever extent possible, clicking should provide more information of that specific KPI
– There should never be overdose of information, the visualization should never ever be cluttered. Maximum 4-5 frame information.
– As much as possible, the entire information should be present on a single page without scrolling
– There should be focus on actionable data & insights. Patters should be highlighted on a dashboard
– Exceptions have to be highlighted – Via size, shape, icon, color, boldness, italic, shades
– Most important info to be present on topleft & least one at bottom right in a dashboard
– Giving the chart name can eliminate the need for axis naming & hence can save space
– For showing trends, the height should be bigger than length
– Never show more than 3 time series charts in a single frame
– Dashboard background should be always very light in color
– Negative to postive values should always be in opposite or contrasting colors

A typical components of dashboard which are generally used are bar & charts, map, diagrams, grids, gauges, scorecards, pareto chart, balance scorecards, gauges & scales etc

– For comparison, columns are the best tools to be used
– Databars are helpful to read data magnitude
– Color scales to be used in comparisons of data
– Line charts are the best when used to display trend or pattern
– Bar charts to be used for categorical comparisons. But should not be used for large data sets
– Pie charts generally take lots of space & also there is difficulty to read data in it. Hence, generally to be avoided in dashboards
– Sparkline & bulletgraphs deliver a lot of information without taking too much space
– Maps to be used for demographic information (should be interactive with hover, pointer, text addons, labels, graphs in maps etc)
– Sea should be in very light colors & country boundaries should be in dark colors
– Gauges are best for continous processes like speed, RPM etc
– In gauges & other places as well, the colors can be used to depict whether the current value is falling in good, average or bad range

Following the above mentioned guidelines will make your dashboard more easy to read & visually appealing.

Happy dashboarding