The bar chart is dead, long live the bar chart

The bar chart is dead, long live the bar chart

Key elements of this article:

·         Bar chart structure

·         Data visualization expansion

·         Defining the purpose of data gathering

·         Making the correct decisions and actions for change

Have you noticed how infographics and other new methods of data visualization is penetrating  our daily lives? It is hard to look at a news channel website without finding interesting sources of information to click and explore in this extended data journalism form.

Pinterest has grabbed the imagination of millions of users through their media platform and indeed offers millions (yes millions) of infographics. Our own Pinterest account has over 7000 followers keen to re-pin, like and engage with our content that includes goal setting, KPI management, business intelligence and other areas of interest.

Bar charting has become a “classic”

What do these changes mean for our old classic bar chart? Well the good news is that it is still alive and kicking as the most prevalent form of data sharing I see at client operations. The simplicity of the chart format offers bars in either vertical or horizontal form and is easily viewed and understood by most people across the world. It is used to show and represent comparisons and trends. The heights and lengths of the bars offer to the eye a swift method to see visually the comparative values.

Monthly Sales

Vertical Bar Chart

The above examples of the same data show categorized information. The category chosen for these data sets is grouped into months, however these can change to any label or category defined groups needed by the user.

It is true enough to call the bar chart a classic in today’s environment. It is like a fine vintage wine that has matured well since its first popular use starting from 1780’s.

The rise of data visualization

Data visualization example

Data visualization example

Over the past few years and tidal wave of new software offerings have come to the market to aid transfer raw data into an easier visually understood charted/visual format. If data is simply left as text it becomes too easy to miss important trends, signals and understand the noise and variance of the data provided.

I consider Hans Rosling as the “king of data visualization” check out one of his many great presentations here. This is a leading example of how our expectations from data has grown and extended its need to inform, engage and compel action and decisions in ways that quite frankly have dis-engaged from over exposure to classic bar charts.

Death by powerpoint.

Employe not engaged and suffering from "death by power point"

Employe not engaged and suffering from "death by power point"

There are many words that are understood across the globe such as OK, some basic human interactions bring about cross cultural understanding like a cute cat or silly dance and in the business world “death by power point” is also universally understood. This is the experience we have been placed in front of similar looking images or text, slide after slide. The death of bar charts has also undergone a similar path.

The often cited “if you can see it you can measure it” has generated more bar charts than people wish to see. Thus dis-engagement of the information provided occurs and ultimately this can assist in a critical step of flat lining performance.

Shake it up

Shaking out the unwanted material!

Shaking out the unwanted material!

The increase of possibilities in data collection is increasing daily. Big data, wearable technology and the increasing penetration of the internet of things means it is possible to chart and plot almost anything you wish to measure. Back in the 1970’s one may need to replace your conveyor rollers once parcels became stuck and damaged traveling along its line, in the 80’s it became more possible to measure the number of parcels traveling and implement into a maintenance program and yet today it is possible to measure the condition and vibration caused through the conveyor system to help plan preventative maintenance of the same conveyor line , all plotted in nice graphs projecting issues.

The intent is meant well, however systems have become in most places too complex and over burden staff, leaders with un-required and none core information. Productivity increases in operations and yet in many companies less productive due to over reporting. The need to shake up the reporting structure is important through a periodic review process.

A simple question of why the information is been gathered and what is the purpose and direction of the business will highlight the difference between the wish, wants and needs of metrics, performance management and KPI’s plus their charting.

Long live the bar chart.

Metric tools

Metric tools

When I sit with clients and discuss their needs it is often ironic to point out I leave them with less reporting, less fancy reports than they started with. Often clients start by asking which data visualization software they should invest in to make the smartest reporting and performance management outputs. Through a series of questions including some I highlight above, it often becomes clear that the business is suffering from “analysis paralysis” and no longer capable of understanding the true value and impact of its current reports.

The outcome from many cases is a reduction of reporting, charting and considerable savings in software investments as the client understands and falls back in love with the simplicity and power of bar charts and the decisions they can help management make. I am starting to think maybe I should change the JAMSO tag line to “the bar chart is dead, long live the bar chart”

Further Reading and Reference Material on graphs and charts

Understanding the difference between a histogram and a bar chart.

Countdown of 10 reasons to never use a pie chart – by Orcacle

Download this pdf from University of Leicester on Histograms (includes outline guide of issues and fixes for histograms in Excel)

IBM offers a great service through its Many Eyes tools for charting and visual contexts

Slideshare data visualization report for 2015 by IBM