The document discusses good data storytelling. It emphasizes using a compelling narrative and effective visualizations. For the narrative, it is important to know the audience and questions, build knowledge in layers by connecting questions to answers, and highlight the unexpected. Visuals should direct attention, use position and emphasis strategically, and keep things clean and simple. An example analyzes reasons for missed NHS appointments. It concludes that good data storytelling links insight to action through taking time to thoughtfully craft the narrative and visuals, and involving the right analyst personality types.
4. Data Storytelling
Telling someone about insight derived from data, and
what they can do about it, in a way that they can
remember and retell to someone else.
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I don’t want to begin something, I don’t want to
write the first sentence until all the important
connections in the novel are known to me.
As if the story has already taken place, and it’s my
responsibility to put it in the right order to
tell it to you.
- John Irving
28. Conversation about missing NHS appointments
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2%
2%
4%
4%
6%
7%
9%
10%
14%
21%
51%
Booking/Rebooking
Fear/Stigma
Forgetfulness
Reminder
Transports
Consequences
Delays
Other Health Issues
Inefficacy
Politics
Costs/Charges
THEMES/ REASONS
General Public Patient HCP
46% 25% 62%
24% 5% 10%
6% 19% 5%
6% 11% 5%
1% 15% 5%
7% 3% 5%
2% 9% -
3% 4% 5%
4% 2% 5%
1% 4% -
- 5% -
THEMES BY AUTHOR TYPES
29. -1%
7%
27%
-21%
3%
-2%
3%
16%
Late Patient HCP
How can we help patients keep their appointments?
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Patients in social don’t report forgetting appointments,
but transport is an issue; focus online appointment
services more on transport advice than reminders.
The general public care about NHS costs, but don’t
make the link to the impact of their own missed
appointments; focus messaging on working together
to improve efficiency.
Patient Forgetfulness Transport Issues NHS Inefficiency Cost to NHS
UK
Average
UK
Average
33. “Analyst” Personality Types
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Reserved, quiet
Loathe contradictions and illogicalness
Like to work alone
Have little interest in everyday concerns
Quite independent of social relationships and very self-reliant.
34. Meet some of our social analysts
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Music
industry
Human
Geography
English
Literature
Psychology
Politics
Business
Linguistics
Economics
Marketing
Creative
Writing
PR &
Comms
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Narrative Visuals
Time & Thought The Right People
Hinweis der Redaktion
Read.
Highlighted words – insight…
Reference Tristan
Two themes transcend the medium, but when I talk about visualisation I’ll be referring to static documents.
Reference Ed’s talk
Role
Knowledge level
Culture
Don’t rush the storytelling part, it should get as much attention as the analysis. Leave time for it. Don’t do it in a piecemeal way.
Wait until the end of the analysis
This works for me – some people are visual, some numerical etc, but the concept is the same:
- Write the individual findings down and then look for links between them that build a fuller picture of what’s going on, a more robust supported insight that could link to an action. Form your story not around listing individual findings but through connected memorable themes.
Get into habits of how to present things; trend line first, channel analysis second etc. That’s not helpful in building a story that’s going to have flow and be memorable.
Think about your themes and the findings that support them. Imagine you’ve never seen the data before and think about what order you’d need to hear them in for it to make sense to you, and build trust in the data while maintaining your attention.
Don’t forget the questions you asked in the beginning – if those were asked well then you already know they are what your audience cares about. Make it easy for them to find the answers they need by referencing the questions, linking them to answers and actions.
Every good story has a twist. Social data in particular lends itself to discovering unexpected themes, often the most interesting and memorable part of a piece of research is the answer to the question you didn’t ask, so make sure to highlight these unexpected findings and suggest some next steps for exploring them further.
This is commercial research; your audience doesn’t have a lot of time. They need to be able to find the insights quickly and understand them. Don’t use jargon, be ruthless about your self editing; if it doesn’t add value, take it out. This also ties into how you tell the story in a visually compelling way; large blocks of texts are likely to turn your audience off and lead to your insights getting lost.
Think about what they need to be able to do/understand
Don’t add crazy design techniques for the sake of it.
Focus.
Think about where on the page you want them to look first, then second to tell the story. ESP important in static storytelling. How can we do that…. Well there’s arrows, but also...
Also positioning text alongside relevant graphics to draw together a point
LEFT TO RIGHT
Think carefully about what the key points or graphics are; assign them relative importance and emphasise in that order.
Use colour for a reason:
Emphasis
Association
Differentiation
Connection
Think about your audience
– meaning of colours differs by culture.
- Colour blindness – 4.5% of UK population.
One idea per page. Everything on the page matters, keep clutter away from your story.
Stripped away the noise – the parts not telling the story
Call to action in the title.
Put the third point of comparison, the UK average control group, onto the x-axis. Simplify and emphasise the comparison between Late Patients and HCPs.
Position of legend – I want you to see/know quickly what you’re comparing so it’s in the top right.
Use of colour – limited for emphasis, tying together the two key themes on the slide by connecting the two relevant findings and the findings to the summary.
Proximity of insight to supporting findings on the chart.
What do you see?
Numbers, lots of charts.
19 Men
7 Women
Mysticism and complexity
Not very compatible with data story telling
Not very compatible with social data either
What do you see?
Numbers, lots of charts.
19 Men
7 Women
Mysticism and complexity
Not very compatible with data story telling
Not very compatible with social data either
Compiled this from a collection of online sources claiming these are analyst personality types. Not rigourous academic research, but a reflection of a popularist understanding of analysts.
Some of this rings true for me, but not for others on my team, and that’s the point… analysts are not a homogenous group of people
Way more important than specific knowledge… to us, a company who has that knowledge to share.
Way more important than specific knowledge… to us, a company who has that knowledge to share.
If you want to be interesting, be interested
Job advert: focus on abilities & qualities over direct experience in social analysis.
Screening process: importance of cover letters – why do you want to do this?
Interview:
Analytical & Storytelling task
Questions about how they approach things and how they communicate.