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Best Practices Using Improvement Charts And Data

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data analysis for business

Improvement Charts and Data – improve how you analyze and present your results.

Business owners rely on improvement data because it is the only way to know whether they are on the right track.

Data tracking over time reveals insights on progress and areas needing improvement.

Also noteworthy is that the information is the backbone upon which the executives make important decisions about the business.

Anyone who has collected data knows how much information piles up. Quantitative and qualitative data can fill hundreds of pages and spreadsheets. Thanks to technology, there are software solutions that can help with that.

Data collection and analysis can provide valuable insights to help organizations make informed decisions and progress their ideas.

It is also innovation management software that assists helps organizations do something worthwhile with it, including:

  • Improve performance
  • Make informed decisions
  • Improve efficiencies
  • Measure the impact of initiatives

Best Practices Improvement Charts And Data

Of course, all improvements must start with data collection, analysis and presentation. Let’s explore best practices for analyzing and presenting improvement charts and data.

1. Decide On the Right Chart Type

Data visualization options are numerous, one of the most powerful being charts. Choosing the right type is critical depending on the information that will be part of the presentation.

Popular options include scatter plots, bar charts, pie charts, and line charts.

Line Charts

Line charts are excellent for showing trends over time. It becomes easy to see the changes in variables. For instance, use line charts to know how sales have improved or declined within a specific time.

Bar Charts

Bar charts make comparative analysis and visualization easy. They allow users to compare the sales of one region against another.
Scatter plots show relationships between two variables. They are handy for pattern or correlation identification in multiple data points.

Pie Charts

Pie charts are great for the straightforward presentation of percentages or proportions. Use them to show how customer groups, services, or products contribute to the overall business revenue.

2. Determine Appropriate Data Scaling

Data scaling ensures two things. The first is that the information on the chart is accurate. Second, it must be appropriate to the receiving audience. So, if presenting to non-management level staff, use simple, easy-to-understand language and visualizations.

Scale Type

Data scaling does involve a level of complexity because data must make sense. It requires users to decide on the appropriate scale type to present the correct data visualization. For example, take the reporting on earthquake magnitudes. A logarithmic scale may be much better than a linear scale.


Plus, data scaling requires the scale-to-data to be clarified proportionality. Insofar as it must maintain a consistent distance between any two points as per the data, regardless of the points on the scale.

Consider the audiences

Finally, data scaling must consider the audiences when choosing skills depending on their familiarity with the data. Management might have a good idea of what the data is all about simply because they commissioned the collecting. But, lower level staff members may be seeing or hearing about it for the first time. The onus is on the presenter to ensure simpler scales for easier understanding.

Data exaggeration or distortion

Ensure the avoidance of data exaggeration or distortion. For example, a good idea is always to start a scale at Zero. Anything above that can result in differences in how the values appear vs. how they actually are.

Appropriate Intervals

Allocate appropriate intervals for any data in the charts. Let’s take the example of dollar value. It will be easier for audiences to understand gaps like $100, $200, and $300 depicting 100 intervals. Values that bring in complexity, like $85 or $1,115, can bring in some confusion.

3. Labeling and Highlighting Charts

Correctly label the chart and axes using descriptive titles and labels that accurately depict the chart data.
Highlighting relevant points draws the audience’s eyes to specific areas requiring attention. Annotations, colored highlights, and bold or slightly larger fonts are some easy-to-use methods.

4. Avoid Inaccuracies and Provide Context

A vital role of the data analyst is to ensure the proper generation of relevant and accurate insights. Technology has availed statistical software that can help with this step. Remember, the insights from improvement data are critical for so many purposes. Only accurate results can help make the right decisions that positively impact the business.

Providing context requires giving audiences sufficient information to help them understand the presentation. That can come from background information and benchmark comparisons. Take it a step further by providing in-depth explanations of critical areas.

Stick to the one simple rule for any presentation. The language must be concise, clear, and devoid of complex terminology or technical jargon.

Summing Up

Data collection and analysis can be a powerful tool for organizations looking to progress their ideas. By using data to inform their decisions and identify opportunities for growth and improvement, organizations can achieve their goals more effectively and efficiently.

Analyze and Present Improvement Data like A Chart Pro

Charts are excellent tools for improving data analysis and visualization during presentations. Pay attention to specific best practices to get the most out of them. Choose the right charts and determine appropriate data scaling with the audiences in mind. Also, ensure data accuracy, avoid technical jargon, and highlight salient points in charts.

Finally, give proper context, even providing additional information outside the charts. At the end of any presentation, no one should leave scratching their head, wondering what the whole thing was about.