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Best Practices for Charting Data

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As modern business professionals seek to improve their communication skills, one of the most important targets for improvement is their ability to present data in clear and compelling fashion through the use of effective charts.  Business is built on data, and managers often have more data available than they can effectively interpret or present.  This is the challenge of effective data visualizations, to take a mountain of data and present it in a way that immediately tells the underlying story.  Here are some ideas to allow businesspersons to use best charting practices to improve their presentations of key data.

Chart to your audience

When academic researchers present technical data, they often focus on presenting accurate data.  Often, the graphs and charts they present are as unintelligible as the raw data itself.  These authors assume that the target audience has the expertise to understand their charts.  If it takes the readers a few extra hours to study the charts in order to gain a complete understanding, then that is the price they pay to get the information.


Business charts are designed exactly the opposite.  The author must do the work of comprehending and assembling the data.  In turn, the audience must be able to understand the chart completely within 30 seconds.  This is the standard length of a short commercial, which is the average attention span of a person for a single idea.

An author who creates a chart in this fashion overcomes the natural barriers of the audience to understanding the chart.  First, when a technical person presents to laypersons, the audience often expects that the presenter may have poor presentation skills.  They may not make the effort to focus on a poorly constructed chart.  This is particularly true for members of the audience who are managers and may be higher in the organization than the presenter may be.  They may have no problem ignoring charts that they do not like.  The onus is on the presenter to make the audience want to comprehend, and to make it easy for them.

A case in point is a trending chart with an unfortunate outlier.  Suppose the presenter is showing a line chart trending upwards, in order to show the sales growth of a particular product.  In addition, suppose that the data contains an inexplicable outlier that drops to the bottom of the chart right in the middle of the trend line.  The challenge is that the audience will immediately focus on the outlier, and not on the story told by the trend line.  The presenter will use up a lot of time explaining the outlier, and miss the chance to make his or her point.  An academic would not consider removing the outlier.  After all, it may represent important information.  The business presenter does not have that luxury.  He or she has 30 seconds to make a point.  For this reason, the presenter should smooth the outlier.  If necessary, he or she can reference an unsmoothed version of the data.

Why traffic waves and congestion happen


Chart to your Data

Modern business intelligence (BI) software has dozens of chart types available.  The purpose of the data helps determine which tool to use.  Here are three of the most common.

  • Data Comparison – column charts are bar charts are effective for showing highs and lows.  For instance, they can show the highest revenue month or the department with the lowest overhead.
  • Data Transitions – line charts and area charts are appropriate for time-based data, in order to show trends or cycles.  For example, they can show a decrease in the number of accidents on the manufacturing floor, or the seasonal nature of monthly sales.
  • Data Composition – pie charts and waterfall charts show proportions of a whole.  In this way, they can identify strong and weak contributors for a particular parameter.  For instance, they can show each product’s proportion to total revenue.

Charting is a matter of learning effective presentation rules, and becomes intuitive with practice.  By focusing on effective communication, individuals can develop the skill to assemble effective data visualizations, in order to present complex data in a simple and understandable manner.
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Nathan Roberson is a lifelong coffee addict, aficionado of all things punk rock, and is particularly fond of Boxer dogs as well as all things tech, marketing design and internet. follow him on Twitter @theMrobot or add him to your circles on Google +