How To Present Quantitative & Qualitative Data Together In Reporting

Reporting can be a monster. For many organizations, reports take an inordinate amount of time to create and present but are soon forgotten because the data simply doesn’t seem to be useful. It’s hard to interpret lots of data and many leaders struggle to derive clear actions from the numbers on the page.

It doesn’t have to be this way. If you can effectively present qualitative and quantitative data as a cohesive narrative, your management reports will become the most valuable tools in your organization.

Differentiating Between Qualitative & Quantitative Data

As you’ll see later in this article, there can be overlap in the definitions of qualitative and quantitative data. But in the strictest sense, these are two distinct categories.

Quantitative Data

Traditionally thought of as black-and-white numbers, quantitative information can also be thought of as “countable” or “chartable.” Numbers, statistics, percentages, and any other figures that are fixed and measurable are considered quantitative. This type of data is also easily replicable because it’s generated by using objective calculations or formulas.

We’ll explain more in the next section, but keep in mind the goal of management reporting is to present high-level, easy-to-understand summaries of what’s happening in the organization. Tables and charts can be good for some types of information, but don’t always tell the full story. Those numbers, while important, must convey meaning to be useful to your leadership team.

Qualitative Data

Typically, quantitative information is supported by qualitative research to help interpret the numbers. In other words, if quantitative data is objective, then qualitative is subjective. This is an overgeneralization but helps to differentiate the two.

The purpose of qualitative information is to provide context to hard numbers so management teams can get an in-depth understanding of the factors that may be influencing operational data and employee statistics. Qualitative data includes ideas and hypotheses to advance quantitative findings. It’s more exploratory in nature, as well as dynamic, interpretative, and negotiable. This may sound a bit flimsy, but these interpretative explanations are critical to uncovering links between variables and trends over time. Most importantly, qualitative data provides rationale for strategic decision making, which is why you’re tracking information in the first place. Using qualitative elements is storytelling with data.

Benefits Of Presenting Qualitative & Quantitative Data Together

As we’ve already hinted, management reports must include both qualitative and quantitative data to successfully tell the story of how an organization is performing. Both types of data bring out the best in each other, lessening ambiguity and providing greater meaning.

For example, if a report only included quantitative data, the audience would inevitably get bogged down on a few data points and miss a high-level summary or analysis. If only qualitative data was presented, the audience would have no “proof” or clear metrics to understand how conclusions were drawn or ideas generated.

Quantitative data is the “what” and qualitative is the “why” and “how.” When presented together, reports are more meaningful and engaging. This often initiates a cyclical process of rethinking strategies—it will be clear which approaches aren’t working or initiatives have stalled. Plus, the combined data makes it much easier for organizations to practice transparency, sharing progress and results in a format that’s digestible for both internal and external audiences.

3 Rules For Presenting Qualitative & Quantitative Data

If we’ve convinced you of the importance of reporting qualitative and quantitative data together, the next step is to make sure you present the data well. Again, the primary goal of management reporting is to communicate results in a manner that can be used to make decisions. Here are some general rules to follow:

1. Know your audience. If you’re reporting to leadership, you’ll likely provide more big-picture strategic information, versus the tactical, operational results that would likely appear in reports for department managers. Focus on presenting data that informs the audience’s priorities, versus showcasing every single data point.
2. Use visuals such as charts, diagrams, and images whenever possible to make hard data more comprehensible. A picture tells a thousand words (or numbers).
3. Provide a logical flow from quantitative to qualitative data so your audience can see how the numbers and interpretations are connected. Within your reporting software, this is likely an actual link between data that helps tell your story. For example, you can tie quantitative measurements and progress indicators with analyses, which ladders up to performance on your overarching strategic objectives.

Presenting Qualitative & Quantitative Data With ClearPoint

ClearPoint’s strategy software takes management reporting to a whole new level. We know reporting is a huge priority for our clients and our tools are built to help you track qualitative data AND quantitative data in one place.

Excel, PowerPoint, and similar platforms take work—too much work—to generate reports. Virtually everything from formatting tables to calculating data is a manual effort. ClearPoint offers both standard report templates and custom reports that intuitively combine both qualitative and quantitative data, linking and arranging it to present a clear story that focuses attention where it matters most. With easy drag-and-drop functionality and good-looking layouts, it only takes a few minutes (not weeks) to create unique reports for any number of audiences.

Here’s a quick snapshot of ClearPoint’s management reporting features, including examples of qualitative and quantitative data presented together.

Report Templates

ClearPoint is stocked with a variety of report templates, all of which can be easily tailored for your organization. Use these templates to generate and reproduce reports at any time interval you choose—the reports will automatically pull in the most current data. Qualitative and quantitative data is presented side by side, in a clear, digestible format. Our reports are designed to display information cohesively, so audiences can discern trends and make informed decisions.

Custom Reports

Need to create unique reports for different audiences, using the same underlying data? Easy. ClearPoint offers a custom report option, where you decide what data to display and build each report using a simple drag-and-drop interface. Create custom fields to track critical qualitative and quantitative data, adjust the flow of information so it makes sense for your audience, and even add your organization’s language. Any custom report can be saved for future use. ClearPoint will adapt to your specific reporting needs and can enforce your process to ensure consistency across your organization.

RAG Status Indicators

RAG (red, amber, green) status indicators are used in reports to demonstrate progress over time. Applying the same principles as traffic lights, you know at a glance whether initiatives are moving forward, proceeding slowly, or stopped (and likely at risk). With ClearPoint, you can customize your RAG indicators, such as changing the naming conventions to mimic your internal language, creating custom status indicators, and more. This aids understanding and provides more finely tuned visual cues to convey meaning, faster.

Gantt Charts

A popular project management tool, Gantt charts track a project and its milestones. You can create a Gantt chart directly within ClearPoint, providing a visual guide of start and end dates, status (with colors that align to RAG status indicators), and completions for different project activities. Our platform is adept at leveraging Gantt charts to help you manage multiple projects, multiple owners of project milestones, and alignment between projects and your strategic objectives.

Custom Charts

Don’t force your reports to fit a mold that doesn’t work for your organization. In ClearPoint, you can customize any chart to display qualitative and quantitative data in the manner you think is best. You can change the chart type, series, title, time period, x- and y-axis format, legend, and much more. If your customization needs go beyond just editing existing charts, it’s easy to add and save new charts. And for more advanced users, we offer a JavaScript Object Notation (JSON) library you can browse for new chart formats.

Final Word: Keep Your Data Updated

Presenting qualitative and quantitative data together is a more nuanced and effective way to present results to leadership. But it does involve extra layers of information that go way beyond simply presenting a column of numbers. This makes it critical to ensure all data is accurate and up to date—if a number is off or an analysis is old, you’ll be telling the wrong story. Put processes in place to automate and verify the accuracy of the data you're tracking.

If you’re using ClearPoint, we offer several tools to make updates a snap. ClearPoint Sync allows you to move data in and out of Excel seamlessly, and our DataLoader can automatically pull information from different sources. Our platform is cloud-based and mobile friendly, so using ClearPoint for all your strategic planning and reporting ensures you always have access to the most updated information, including all the qualitative data and quantitative data in your management reports.

FAQ:

Why are quantitative and qualitative data important?

Quantitative and qualitative data are important because they provide complementary insights that help organizations make informed decisions. Quantitative data offers measurable and numerical insights that can identify trends and patterns, while qualitative data provides in-depth understanding of underlying reasons, motivations, and context behind those numbers.

How do you analyze quantitative and qualitative data?

To analyze quantitative data:

- Collect Data: Gather numerical data from surveys, experiments, or databases.
- Organize Data: Arrange data in tables, charts, or spreadsheets.
- Use Statistical Methods: Apply statistical techniques such as mean, median, regression analysis, and hypothesis testing.
- Interpret Results: Draw conclusions based on statistical analysis and patterns.

To analyze qualitative data:

- Collect Data: Gather data from interviews, focus groups, or open-ended survey responses.
- Transcribe Data: Convert audio or video recordings into text.
- Code Data: Identify and categorize themes, patterns, and insights.
- Interpret Results: Understand the context and meanings behind the data through thematic analysis.

How do you integrate quantitative and qualitative data?

To integrate quantitative and qualitative data:

- Collect Both Types of Data: Gather quantitative data (e.g., surveys) and qualitative data (e.g., interviews) simultaneously or sequentially.
- Analyze Separately: Conduct separate analyses for each data type.
- Compare and Contrast: Identify points of convergence and divergence between the findings.
- Combine Insights: Use a mixed-methods approach to draw comprehensive conclusions that leverage both numerical and contextual insights.
- Develop a Unified Report: Present findings in a cohesive manner that integrates both quantitative and qualitative perspectives.

How do you compare quantitative and qualitative data?

To compare quantitative and qualitative data:

- Identify Common Themes: Look for themes and patterns that appear in both data types.
- Evaluate Consistency: Assess how well the quantitative data supports the qualitative insights and vice versa.
- Contextualize Findings: Use qualitative data to provide context to the numerical trends found in quantitative data.
- Highlight Differences: Note any discrepancies between the two data types and explore potential reasons behind them.

How do you differentiate quantitative and qualitative data?

Quantitative data:

- Nature: Numerical and measurable.
- Purpose: To quantify variables and identify statistical relationships.
- Methods: Surveys, experiments, and secondary data analysis.
- Analysis: Statistical analysis such as averages, correlations, and regressions.
- Example: Survey results showing the percentage of customers satisfied with a service.

Qualitative data:

- Nature: Descriptive and non-numerical.
- Purpose: To understand underlying reasons, motivations, and context.
- Methods: Interviews, focus groups, and open-ended surveys.
- Analysis: Thematic analysis, coding, and narrative interpretation.
- Example: Interview responses explaining why customers are satisfied or dissatisfied with a service.