3.7.2 Description

Numbers, graphs, and charts have little meaning without business context. Combining data, visuals, and a narrative has a more impactful influence on decision-making. This is where data storytelling comes in.

Data storytelling is a structured way to communicate and ensure engagement from both an analytical and emotional perspective. It helps provide an engaging and insightful experience of sharing data results with key stakeholders in the Interpret and Report Results domain.

While data visuals and insights are central to data presentations, the story narrative makes data storytelling influential and effective. It considerably increases the odds of the right decision being made at the right time.

To enable clear, robust, and visually appealing communication, data stories follow these key principles:

• Understand the audience: Stakeholder analysis informs how the insight is communicated, what level of detail is included, and how it is represented.
• Provide the context: A strong narrative does two things: it provides business context by associating insights with business events, and it draws out the key insights from visuals. The more invested stakeholders are in the business context, the more impactful the narrative becomes.
• Use space and visuals effectively: The medium to create the visuals is selected to display the visuals in their best light. The right visuals to easily and effectively share the key insights are selected. Consideration is given to the size of the text and visuals, their orientation, and the colours used.
• Communicate as a story: Effective visuals, supported by context and key focus points, are shared in a story format: an introduction, a middle where the plot develops with twists and turns, and the end that includes lessons learned and other key insights.
• Focus attention on key highlights: In the Analyze Data domain, a lot of data is analyzed to draw key conclusions. Primary and secondary data insights are differentiated, and the focus is on the primary insights. Primary insights are those that directly answer the research questions. Secondary insights provide supporting context or rationale. Secondary insights may be included in the narrative, but not included in the dashboard or report.
• Be concise and avoid cluttering: Particular attention is given to each element added to the page or screen. Anything that is not adding value is removed. Reviewing the content helps to ensure that key highlights and takeaways are not lost an overly wordy narrative. The messaging should be simple and succinct, yet impactful.

3.7.3 Elements
 
.1    Audience

It is important to understand who the audience is, what questions they want answered, questions they may ask, as well as what they need to know.

When analyzing the audience, consider:

• the level of detail to include,
• how the results will be communicated (for example, formality, tone, use of technical language), and
• the relationship with the audience (for example, a trusted expert will include next steps while a novice analyst may recommend actions).

.2    Narrative

By keeping data dashboards and presentations succinct, a lot of content from the analysis is not shown. The narrative includes the information that is not included but is important to the story. It also provides the rationale for the dips and spikes in the charts by correlating to specific incidents or events.

Narrative explains the visual and provides context to key insights.

.3    Visualization

To make it easy to discern the meaning of the data, it is important to leverage the appropriate visualization, and use colours and formatting strategically to provide visual cues to the key insights or conclusions.

When creating a visualization, analysts consider:

• the appropriate visualization to use,
• the colours and the manner in which colour contrasting is leveraged,
• size of visuals and text, based on importance, and other text formatting (for example, bold, italics, underline), and
• positioning and order of items on the page or screen.

These design considerations help ensure that the most important insights are easy and quick to discern.

.4    Storytelling

While validated insights may be sufficient to make decisions, the emotional aspect of decision-making is often lacking. Emotions are essential to decision-making. Storytelling aids in bringing out the emotional aspect of perceiving information.

Data storytelling follows the same structure as a story. The introduction sets up the context and introduces key elements, the middle builds on the plot with a focus on wins and challenges, and it concludes with key insights and lessons learned. This format makes the experience more appealing and stimulating. A well-engaged and educated audience, in turn, makes better decisions.

Analysts consider the following principles for influential data storytelling:

• keep the language simple,
• any sentence or part of the narrative that is not contributing value should be eliminated,
• the order of the narrative (spoken and written) should make sense (a disorderly story can lose the audience's attention),
• ensure the purpose of each visual is clear, and
• summarize key points in the conclusion.

3.7.4 Usage Considerations
 
.1    Strengths

• Provides a holistic comprehension of the results.
• Engages the audience emotionally and activates more parts of the brain when compared to solely fact-based presentations.
• Enables the audience to focus on the key insights and takeaways and what they mean in the business context.
• A compelling narrative will influence and drive better decisions.

.2    Limitations

• Crafting a story around the data can be time-consuming.
• Creative story writing is an art and can be harder to write than the traditional messaging around data reporting. The effectiveness of the narrative is dependent on the writer's skills.
• If bias and self-motivated interests drive the storytelling and only data that support their case are shared, then the audience will be misled.