�Data Storytelling (Bercerita Dengan Data)�

Kadir Ruslan

Outline

• Definition and benefits
• Components
• Steps
• Some tips
• Examples

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Data Storytelling?

Data storytelling is the ability to effectively communicate insights from a dataset using narratives and visualizations. It can be used to put data insights into context for and inspire action from your audience.

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The Benefits of Data Storytelling

• Keep the audience engaged: People prefer visuals to plain text or speech. Over the years, multiple studies have found that associating visuals with data boosts both engagement and memory of the information presented.
• Make it easier to drive home key points: Since the human brain is better at processing visual content than numbers, data storytelling makes it possible to present complex topics to audiences who lack technical knowledge.
• Inspire action: A good data story provides the audience with insights that entice them to act. Customizing data storytelling to suit the target audience makes the data even more relatable and impactful.

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The power of data storytelling

• Stories beat statistics in two ways: One, they are more memorable than statistics, and two, they are more persuasive.
• The human brain can be influenced to make decisions through both logic and emotion, so data alone won’t cut it — we need the story behind the numbers to be the bridge that connects our emotional side with our logical side.
• Our brains expect and want a coherent story. It’s not enough to just provide insights; you need to craft an inspiring message that evokes action.

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Components to data storytelling

• Data: Thorough analysis of accurate, complete data serves as the foundation of your data story. Analyzing data using descriptive, diagnostic, predictive, and prescriptive analysis can enable you to understand its full picture.
• Narrative: A verbal or written narrative, also called a storyline, is used to communicate insights gleaned from data, the context surrounding it, and actions you recommend and aim to inspire in your audience.
• Visualizations: Visual representations of your data and narrative can be useful for communicating its story clearly and memorably. These can be charts, graphs, diagrams, pictures, or videos.

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Data

• The figure explicitly demonstrating that the revenue per customer is falling (right) is a better choice than plotting the total revenue and customer side-by-side (left)

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Data

• The market shares of the largest markets become apparent when the smallest markets are aggregated.

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Data

• Often, less is more when it comes to showing multiple charts in one graph.

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Narrative Structure

• A data story begins by setting the scene of the current situation, proceeds by providing insights that lead up to the central insight, and ends with relevant recommendations.

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Use the data storytelling arc

• Set-up & hook — this is where you provide business context and background.
• Rising insights — these are the supporting details that reveal deeper insights into the problem or opportunity.
• ‘Aha!’ moment — the major finding or central insight. This is essentially the key thing you want your audience to remember, and the action you recommend they take. 

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Data Visualization

Data visualization helps transform boundless amounts of data into something simpler and digestible. Here, you can supply the visuals needed to support your story. Effective data visualizations can help:

• Reveal patterns, trends, and findings from an unbiased viewpoint.
• Provide context, interpret results, and articulate insights.
• Streamline data so your audience can process information.
• Improve audience engagement.

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Consider the right data visualization

• Illustrate your narrative with data visuals that can quickly provide the insights your audience wants, enhancing your storytelling and making your data more compelling.
• Be sure to choose formats that are easy to digest and follow, that don’t need much explanation. Let the visuals do the talking.
• You should also think about the right type of data visualizations to use to display different types of information.

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Visuals: Choose the appropriate visualization

• Bar charts are superior to pie charts in communicating differences in proportions

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Visuals: Choose the appropriate visualization

• Pie charts are a better choice when illustrating the sum of proportions across categories

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Visuals: Calibrate the visuals to the message

Pie charts are a better choice when illustrating the sum of proportions across categories

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A comparison of the revenue of individual products across countries, especially for product B

Visuals: Calibrate the visuals to the message

A comparison across products for each segment

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A comparison across segments for each product

Visuals:Focusing the attention of the audience

• The audience pays attention to what stands out in a chart. Highlighting the key points distills the signal from the noise, allowing the audience to garner insights from charts quickly.

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Data Storytelling Steps

• Step1: Defining the Objective: The Compass of Your Data Story
• Step 2: Gathering Data
• Step 3. Analyzing Data
• Step 4. Structuring the Story: Weaving the Data Fabric
• Step 5: Crafting the Visuals
• Step 6. Presenting and Sharing: Bringing Your Data Story to Life

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Step1: Defining the Objective: The Compass of Your Data Story

• Identifying the Purpose
• Persuade: Do you want to convince your audience to take a specific action, adopt a new viewpoint, or support a particular decision?
• Inform: Is your primary goal to educate your audience on a specific topic by presenting factual information and insights?
• Inspire: Do you aim to evoke emotions, spark motivation, or encourage your audience to see the world in a new light?

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Step1: Defining the Objective: The Compass of Your Data Story

• Determining the Target Audience
• Who are they? Are they colleagues, potential customers, policymakers, or the general public?
• What is their level of data literacy? Do they have a strong understanding of data analysis or require a more simplified approach?
• What are their interests and needs? What topics resonate with them, and what information are they seeking?

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Step1: Defining the Objective: The Compass of Your Data Story

• Establishing the Key Message
• Keep it short and concise: Aim for a single, memorable sentence that encapsulates the main point.
• Use clear and simple language: Avoid jargon and technical terms that might confuse your audience.
• Focus on the impact: Highlight the significance of your message and its potential value to your audience.

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Step 2: Gathering Data

• Collecting Relevant Data Sources: Identify data sources aligned with your message. This could involve internal databases, external reports, or even surveys you might conduct.
• Ensuring Data Quality and Accuracy: Double-check the data for errors or inconsistencies. Cleaning and verifying your data ensure the reliability of your story.
• Organizing the Data for Analysis: Organize your data in a way that facilitates analysis. This could involve building spreadsheets, importing data into specialized software, or simply creating clear labels and documentation.

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Step 3. Analyzing Data

• Applying Statistical Methods: Utilize appropriate statistical techniques to uncover patterns, trends, and relationships within the data. This could involve simple calculations like averages or more complex methods like regression analysis.
• Identifying Patterns and Trends: Look for patterns in the data — unexpected spikes, correlations between variables, or consistent trends over time. These patterns form the backbone of your story.
• Using Data Visualization Techniques: Charts, graphs, and other visual elements bring your data to life, making complex information easier to understand and remember. Choose visuals that effectively highlight the identified patterns and trends.

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Descriptive Statistics

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Inferential Statictics

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Step 4. Structuring the Story: Weaving the Data Fabric

• Creating a Storyline
• Start with a hook: Grab your audience’s attention at the outset with a captivating introduction. This could be a surprising statistic, a thought-provoking question, or a relatable anecdote.
• Introduce the context: Briefly provide essential background information about the topic, ensuring your audience possesses the necessary foundation to understand the data presented.
• Present the data and insights: Unveil the data points and key findings, highlighting the patterns, trends, and relationships you’ve identified.
• Explain the implications: Connect the data to the bigger picture, explaining what the insights mean and their potential impact on your audience.
• Conclude with a call to action: Leave your audience with a clear takeaway and, if applicable, a specific action you encourage them to take based on the story’s message.

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Step 4. Structuring the Story: Weaving the Data Fabric

• Deciding on the Narrative Flow
• Linear: This chronological flow presents information in a step-by-step manner, ideal for stories explaining a process or timeline.
• Chronological: Similar to linear, but with a focus on the passage of time, often used for historical or trend-based narratives.
• Thematic: This structure organizes information around central themes, fostering exploration of various aspects related to a single topic.
• Selecting the Most Effective Visualizations
• Clarity is key: Ensure your visuals are clear, concise, and easy to understand for your audience. Avoid complex charts or overwhelming information density.
• Alignment with the message: Each visualization should directly tie back to a specific point in your storyline, reinforcing the key message and avoiding irrelevant information.
• Accessibility: Consider different learning styles and accessibility needs. While visuals enhance your story, ensure the core message is also clear through the accompanying text.

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Step 5: Crafting the Visuals

• Designing Engaging Charts and Graphs
• Clarity is paramount: Ensure your charts and graphs are easy to interpret even for an audience with no prior data analysis experience. Use clear labels, appropriate scales, and uncluttered layouts.
• Embrace contrasting colors: Utilize color strategically to highlight key data points and draw attention to specific trends or comparisons. However, avoid overly complex color schemes that might overwhelm the viewer.
• Choose the right chart type: Different chart types are better suited for different types of data. Select the chart that best represents the relationships and patterns you want to convey (e.g., bar charts for comparisons, line graphs for trends, pie charts for proportions).

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Step 5: Crafting the Visuals

• Choosing a Color Scheme
• Alignment with the message: Select colors that complement your message and resonate with your audience. For example, use warm colors like red or orange to represent warnings or urgency, and cool colors like blue or green to convey calmness or growth.
• Accessibility and color blindness: Ensure your color palette is accessible to viewers with color blindness by utilizing high-contrast color combinations and providing alternative visual cues like patterns or shapes.
• Consistency: Maintain a consistent color scheme throughout your data story for visual cohesion and brand recognition.

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Step 5: Crafting the Visuals

• Incorporating Relevant Images or Illustrations
• Strategic use: Don’t just add visuals for decoration. Use them strategically to enhance your narrative, introduce human elements, or explain complex concepts in a simpler way.
• Relevance and quality: Ensure the images or illustrations you choose are directly related to your data story and are of high quality to avoid pixelation or unprofessional presentation.
• Cultural sensitivity: Be mindful of cultural sensitivity when selecting images that represent diverse individuals or topics.

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Step 6. Presenting and Sharing: Bringing Your Data Story to Life

• Preparing a Compelling Presentation
• Structuring your narrative: Organize the key points and visuals in a logical flow, ensuring a smooth transition between data points and maintaining a clear narrative arc.
• Designing engaging slides: Utilize clear and concise language, impactful visuals, and consistent formatting to create visually appealing and informative slides that avoid information overload.
• Practicing your delivery: Rehearse your presentation beforehand, focusing on pacing, clarity, and addressing potential questions from your audience.

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Step 6. Presenting and Sharing: Bringing Your Data Story to Life

• Tailoring the Delivery to the Audience
• Gauge data literacy: Consider the level of data expertise your audience possesses. Use clear explanations and avoid jargon if necessary, while still providing sufficient depth for a comprehensive understanding.
• Adapt your language: Adjust your vocabulary and complexity of explanations based on your audience’s background and level of understanding.
• Connect with the audience: Use storytelling techniques like relatable anecdotes or personal examples to connect with your audience on an emotional level and enhance their interest.

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Step 6. Presenting and Sharing: Bringing Your Data Story to Life

• Encouraging Interaction and Feedback:
• Pose open-ended questions: Invite questions and discussion after your presentation to gauge audience understanding and address any lingering doubts.
• Welcome feedback: Encourage constructive feedback on your presentation style, clarity, and overall effectiveness of the story. This valuable input can help you refine and improve your data storytelling skills for future endeavors.

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What makes a data story effective?

• It needs to be relevant: The best stories speak to people, and the more specific the person, the better.
• It needs to include good data: The stories are not about what you think your audience should hear, they are about sharing what the objective data says. The data should be from a reputable source and/or collected in a way that truly represents what’s needed to tell a truthful story.
• There needs to be a clear narrative: Use a traditional story arc with a beginning, middle, and end. It’s important to use plain language.
•  It should include intentional visuals: the visuals used should help the audience easily understand what the data means (appropriate for the data, legible, not misleading, well-labelled)

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Data Storytelling Tips

• Adjust the Message for the Audience: A data story will not be effective unless it’s carefully crafted for the target audience.
• Choose the One Main Point: When analyzing the data, there may be numerous exciting insights. But not all can or should be put in the story.
• Outline the Story: A good story is always carefully structured, and data storytelling is no different. This means writing an outline in advance that lays out the story’s structure and how the data will flow.
• Make It Memorable: Stories make data exceedingly more memorable.
• Make It Human: People want to hear something they can personally relate to, whether positively or negatively. Always aim to center stories around the human element.

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Data Storytelling Tips

• Vary Chart Types: Visualizing the data is one of the three primary elements of data storytelling (the other two being story and data).
• Minimize Cognitive Load: Cognitive load refers to the mental burden humans experience when confronted with unconventional, unfamiliar or too-complicated information. This leads to mental fatigue, making it harder to consume a data story.
• Wrap up with a strong conclusion and call to action: Don’t forget to end your story by sharing potential actions and recommendations. Link back to the objectives you defined at the start of your data storytelling and share your suggestions for what actions could be taken as a result of your findings. 

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Benefits of Crafting a Compelling Narrative With Statistics 

• Clarity: Statistics can help to present complex information in a clear way, especially with visual aids such as charts and graphs.
• Credibility: Using data to support your arguments adds credibility to your story and provides evidence to back up your claims.
• Persuasion: Statistics provide objective evidence to support your arguments.
• Emotional impact: By showing how the data relates to real people and real-world issues, you can create a more impactful and memorable story.
• Engagement: Using statistics in your story can make it more engaging and interesting to your audience.

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Benefits of Crafting a Compelling Narrative With Statistics 

• Provide Context and Background Information: Statistics can set the stage for your content narrative and offer the reader a deeper understanding of a topic.
• Illustrate a Point or Argument: Statistics can support a point or argument in your narrative. This method is an effective way to add credibility and depth to the topic and persuade readers to agree with your perspective.
• Create Tension or Conflict: Statistics can highlight a problem or issue in the narrative. Using statistics to create tension or conflict is an effective way to engage readers and draw their attention to the narrative.
• Create a Sense of Scale: Statistics can give a sense of the size or scope of a problem or situation. This can be particularly useful when discussing large or complex issues.

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Example: Combination of Data Visualization and Text Narrative

• Combination of data visualization and narrative can strengthen the data story.
• The narrative and the data visualization must tell the same story and complement to each other.

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Example: Combination of Data Visualization and Text Narrative

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https://www.washingtonpost.com/graphics/2020/world/corona-simulator/

Example: Combination of Data Visualization and Oral Narrative

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References

• https://venngage.com/blog/data-storytelling/
• https://www.netsuite.com/portal/resource/articles/data-warehouse/data-storytelling-tips.shtml
• https://www.y42.com/blog/top-tips-for-powerful-data-driven-storytelling
• https://www.linkedin.com/pulse/from-numbers-narrative-step-by-step-guide-data-uchenna-splendor--j4lpf/
• https://www.datacamp.com/blog/telling-effective-data-stories-with-data-narrative-and-visuals

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