Plot to go on the quest.
What’s the story that goes along with the data. Not the data alone - need a story to connect data to bigger picture.
Vision:
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Engagement: Use techniques to draw your audience into your story, such as an intriguing plot and strong characters.
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Vision: Set up a clear vision for the future that helps the audience picture real change.
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Authenticity: Communicate your vision with authenticity to build trust and avoid coming across as a sales pitch.
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Contrast: Create contrasts between the current reality and the future vision to highlight the need for change.
Motivating your audience to take action
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Know your audience: Understand what motivates them to tailor your story to their needs.
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Create an emotional connection: Use personal anecdotes to appeal to their emotions.
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Provide context: Explain where you’ve been to highlight the need for change.
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Make the audience care: Develop characters and plot to engage your audience.
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Use metaphors: Make new ideas familiar and less intimidating.
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Use clear contrast: Show the difference between the current state and the desired future.
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Call to action: Clearly state what you want the audience to do differently.
Data Visuals:
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Visuals add to a story but are not it.
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Simplify Visuals: Break data into small, digestible pieces and use high-contrast colors to make it easy to understand.
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Balance Story and Data: Visualizations should enhance the story, not distract from it. Use visuals sparingly and focus on the narrative.
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Audience Engagement: Make a clear distinction between presenting data and storytelling to keep the audience engaged and focused on the larger story. Have breaks in presentations.
Presenting:
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Strip away to just the story
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Eliminate Distractions: Strip away any details in your data visualizations that do not enhance the story.
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Engage Immediately: Start your storytelling session by immediately engaging the audience with something interesting.
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Less is More: Use fewer data visualizations and ensure they are clean and easy to read to keep the audience focused on the story.
Data Science Focus
Less operational more business knowledge. Empirical research, run experiments to see if get closer to better returns
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Data Science Focus: Unlike operational efficiency, data science is exploratory and uses the scientific method to gain business knowledge.
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Asking Questions: Organizations need to ask interesting and higher-degree questions to build organizational knowledge.
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Empirical Research: Data scientists should run experiments, ask questions, and produce well-designed reports to gain insights.