Reporting Best Practices

Using Color to Communicate Risk-related Data

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What happens when you use more than seven colors to display data in a report? Visual overload. As much as you want to liven up your reports with 256 hex colors, it doesn’t mean that you should, especially regarding GRC reporting.

Why? Because the eye is unable to discern what’s truly important from a gratuitous rainbow of colors, so the brain rejects the information. This could be a problem if you’re trying to communicate risks, likelihoods, and financial implications across your business using multi-color reporting. However, with the right use of color in charts and graphs, reporting becomes a powerful decision-making tool.

When color is unhelpful in reporting

Let’s first unpack where people go wrong when applying color to charts and graphs in reports. Flexible and robust data intelligence tools like Onspring provide color options for users to apply when building reports. This color palette variety provides hue, saturation, brightness scales and customization, designed to serve many reporting needs and branding requirements for end-users. But when the entire color palette is applied as a rainbow in a single data visualization, color doesn’t serve its purpose for end-users.

Example below: A “rainbow” display of colors creates confusion and causes end-users to lose the meaning behind the data.


How to use color in reporting and dashboard design

The purpose of color in reporting and dashboards is to guide an end user’s attention to help them analyze information to take the necessary action as quickly as possible. Color is a tool for data engagement.  So applying color in data visualization charts and graphs requires strategy and planning. While this tiny detail may seem inconsequential and based on personal preference at the outset, it will ultimately provide the visual cues needed to communicate insights from your data.

Like building individual programs that support an organizational GRC structure, you start with a strategy for each supporting GRC program, and the strategies are each focused on achieving a set of goals. A similar planning process should occur when brainstorming the reporting needs of any GRC program, like operational risk, internal audit, third-party/vendor risk, business continuity, ESG, or others.

As you build reports in Onspring, first decide what you need to communicate with the data and what actions a viewer should take away. These two decisions will help you strategize how color will be applied in your charts and graphs.

Best practices when applying color in reporting

Single color reporting

Using only a single color in data visualization charts and graphs can be a powerful way to focus users’ attention to data quantities when the items being measured are equitable. This color application is best applied in reports when the data needs to communicate timelines, volume, or project workloads and status.

In the example report below, the end-user immediately understands the distribution of audit projects by their stage in the audit lifecycle.


This single-color treatment can also provide an immediate view into areas of your business or business lines that continuously drive risk or give managers insights into workload distribution across a team.

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Multi-color reporting

Also known as sequential coloring, multi-color reporting is the most common type of data visualization and the most widely misused. If the purpose of your data visualization is to communicate differences between data sets. The best way to visually communicate those related differences is to select complementary colors within the same warm or cool color families.

For example, utilize greens, blues, and purples together and avoid using oranges, reds, and yellows on the same chart. Your goal with this type of color application is to highlight differences or similarities and avoid drawing attention to data points that aren’t relevant.

In the example below, multi-color reporting in a cool color family communicates the volume of active SOX controls and immediately compares the control type. If non-key SOX controls outweighed critical SOX controls, the end-user could immediately see this from color cues and take action to investigate.

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Semantic color reporting

Data visualizations using semantic colors are incredibly effective in governance, risk, and compliance reporting because of the ability to focus users on the status of specific data points against your thresholds. Semantic colors are used for standard value states, such as neutral, good, bad, or warning. Each semantic color choice should have the same general meaning in all your uses. In Onspring, you can customize semantic color selections based on list values or a sliding scale.

With this customization, warning or alert colors, like orange and red, can be set for high-risk data points, while a yellow caution color can be applied for potential issues. Semantic colors quickly communicate data insights, particularly when your data is time- or risk-sensitive.


Semantic color reporting can also complement single-color reports by providing a deeper level of meaning without distraction.

Referencing the “Open Audit Projects by Status” single-color report, semantic colors can be added by changing the display setting within Onspring to show a data table. By doing so, end-users can dig into the details of the largest column, “Draft Reporting,” to see its specific audit projects as well as progress and budget status in the corresponding table.


Be consistent in color usage

Whether you choose colors that reflect your organization’s brand or the out-of-the-box color palette options available in Onspring, how you apply color should be consistent across the board. Each color should have the same meaning or context in each data visualization. This consistency avoids confusion and helps users navigate from report to report faster while still deriving insights from each graph and chart.

Onspring brand colors are used throughout reports and dashboards in our solutions:

  • Shades of blue and green communicate neutral data points.
  • Red communicates overdue tasks, over-budget projects, and high levels of risk.
  • A sliding scale of orange and yellow further communicate tasks coming due, projects nearing budget, or increasing levels of risk.

For example, in Onspring’s Third-party/Vendor Risk Management Solution, customers can manage the full vendor lifecycle from onboarding through renewal and offboarding. A report showing vendors by stage in the onboarding status uses orange to denote any vendors who were rejected during the review process.


The user’s eye is drawn to the bright orange, which is important because it will provide information on which vendors were rejected and supporting information on why.

Singling out status levels with a contrasting, semantic color saves users time and effort, enabling them to get to core decision-making faster.

Using color to communicate better

Going back to the original “rainbow” chart shared early in this article, the colors could and should be updated based on what needs to be communicated.

A single-color chart will provide the most direct and simple display if the goal is to communicate the overall scores of individual ESG programs simply.

If the goal is to communicate to ESG business owners or if corrective action needs to be applied to a specific ESG program, then semantic coloring should be applied using a sliding scale based on list values that define acceptance thresholds.


“Rainbow” report: Fails to communicate specific, direct information.  

Single color report: Communicates explicitly which ESG programs are performing well and those that are not.

Semantic color report: Communicates which ESG programs need corrective action.

Determining what type of colors are used in your reports is often a strategy of choosing what should be emphasized versus what should be de-emphasized. If the data being shown is important to communicate a holistic review of data sources or points, but it doesn’t drive decision-making, then that data should be de-emphasized.

In addition to planning color use on individual reports in Onspring, you should also plan how you lay out your reports on a dashboard (or a consolidated page of reports). Your graphs and charts should work together and build on one another to tell a comprehensive story that enables your end-users to consume, interpret, and act.

For insights on Onspring capabilities, check out our article on Live Report Filtering and Live Dashboard Filtering.

Example reports in this article only reflect a few charting options available in Onspring. If you’d like to see all the chart and graph options, you can utilize in Onspring reporting, simply schedule a quick demo.

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