5 ways to tell a value story with data.

Anscombe quartet for data visualization

Source: Wikipedia. Anscombe’s quartet.

Presenting to decision makers? Always remember it’s not a data story you’re telling, it’s a value story.

First, ask yourself: What is the message? Why is this valuable and meaningful to your audience? Where did the data come from, and why are your conclusions believable? Then follow these 5 tips to get to clarity and credibility:

1. Bold opening statement or question. Begin with a crisp, clear message. If a reader’s time is cut short, what key point should they remember? When opening with a question, be sure to answer it explicitly in closing summaries/conclusions (sounds simple, but oftentimes it’s missed, draining impact from the content).

2. Inverted pyramid. Follow your opening statement with a summary of the key points: What, who, when, where, why. Use the journalism approach of giving away the ending, and then filling in background. Apply the inverted pyramid concept to both writing and data; so for example, present important charts or tables first, and raw data or other supporting data later.

3. Data visualization. Give them some ‘ooh, shiny’, but not too much. Visuals can tell a story that writing cannot: Reference the classic Anscombe’s Quartet graphic above. Anscombe illustrated beautifully how four distinct data sets can have the same mean x, mean y, sample variance, etc. – and that only through visuals do we see their notable differences. Simple descriptive statistics would not tell the whole story.

4. Explain the source. Writing must tell the rest of the value story: Where did the data come from? Why were they analyzed this way? Why is this a valid and useful finding? After providing clarity, now you’re establishing credibility.

5. Engage the skeptics. Essential to establishing credibility. Identify potential challenges and tough questions expected from the audience. When possible, discuss the limitations and acknowledge the gaps in your findings. What questions remain? What further research is needed? By addressing these directly, you can spark a conversation with the audience.

Posted by Tracy Allison Altman on 14-Oct-2017.

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Museum musings.

Pondering the places where people interact with artificial intelligence: Collaboration on evidence-based decision-making, automation of data-driven processes, machine learning, things like that.

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