Choosing a Suitable Visualization

Objective

After completing this lesson, you will be able to decide on suitable data visualization

Visualizing survey data

After the data analysis, the next step is to create the charts for the results report. A suitable and compelling visualization facilitates the discussion process based on the data and helps to convey key insights and messages to the project stakeholders.

Banner image of several people sitting side by side using a smartphone, laptop, and tablet, with the headline ‘RECAP: What you’ve already learned’.

Example for a Result Visualization

In the first phase of the 4S project, Sandra and Paul have already conducted several change surveys. The chart below is part of the visualization of the business readiness assessment and a good example of illustrating a high-level result overview.

The chart summarizes a business readiness survey. On the left, survey topics are grouped into three areas (knowledge about the SAP project, satisfaction with support activities, and readiness for the SAP project). On the right, mean values on a 1–5 Likert scale are shown as line charts for three target groups (Plant Porto, Plant San Diego, Finance Operations), with a green dotted line marking 3.5 as the threshold for positive results.

Let’s have a look at the different elements of the chart:

On the left side, the different survey topics listed and clustered into categories.
On the right side, the mean values for all survey topics are depicted in line charts for the different target groups of the survey (e.g. "Plant Porto").
A green dotted line has been added at a mean value of 3,5. On a 5-point Likert scale, values, this threshold divides the results into strength (mean values higher than 3,5) and weaknesses (values lower than 3,5).
The legend at the bottom of the chart provides all relevant information to understand the chart.

Hint

If you want to revisit this content in the learning course "Acting as Professional Change Manager in SAP Cloud Projects", follow the link Mitigating Go-live Related Risks and scroll down to the "Enhance the Business Readiness" section.

Professionalizing the Result Visualization

Paul already feels well prepared for creating overview charts to visualize survey data. However, he is eager to further professionalize his skills. Therefore, he schedules a call with Mira to learn from her extensive experience.

For an aggregated overview of different chart types and practical recommendations regarding their application, have a look at the slides below. Slide one focusses on pie charts, bar charts, and line charts.

The slide provides an overview of three chart types and recommendations for using them. On the left, it shows examples of a pie chart, a bar chart, and a line chart. On the right, it lists practical guidance: pie charts should use a maximum of six segments, combine very small segments into ‘Others’, start with the most important segment at the 12 o’clock position, and otherwise sort segments by size. For bar charts, the slide recommends keeping spaces between bars smaller than the bars themselves, using the most intensive color for the most important value, rounding numbers in data labels, and displaying scale values on the horizontal axis above or below the chart. For line charts, it recommends using thicker data lines than axis/grid lines, avoiding too many lines (“spaghetti” charts), choosing varied colors when multiple lines are shown, and using different symbols for each line to distinguish data points.”

The next slides provide recommendations for using column charts and scatter charts.

The slide presents two chart types—column charts and scatter charts—along with recommendations for their use. It highlights that column charts should have clear spacing, emphasize the most important column, and may include rounded data labels, while scatter charts are used to show relationships between two variables and should use appropriately sized data points, optionally include a trend line, and be explained with a clear title and legend.

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