Just coming across this now, but it resonates. Of course, I have heard the Data Storytelling concept countless times. It never really resonated with me, perhaps because I took a lot of science classes and telling a story is not part of the scientific method.
Since Data Storytelling demonstrated such resilience, I eventually came to accept it, although with the caveat that the narrative should be non-fiction ;)
"With endless information comes the ability to take information from its context, to tell stories perfectly matched to the intentions of the teller, freed from the complex texture of reality."
– Kerry Howley, from Bottoms Up and the Devil Laughs
Profound point that is seldom mentioned. Do not tell a story about your data analysis for which the ending is predefined (as it usually is for normal stories). Thanks...
However, if data storytelling is not data analysis, then how should you tell the story behind your data analysis? Topic of your next blog? Is it like a story told by Walter Isaacson about Steve Jobs or Da Vinci? ...true to facts but profound in insights? But then, where is the call-to-action? Or, should there be?
In our AI ("Detect & Alert" insights - designed by Aldecis), Data StoryTelling is used to give explanations of why the AI highlighted these particular insights.
Because to avoid the "BlackBox" nightmare of AI, nothing (nor several graphs, nor several tables) is better than an explanation in Natural Language.
Not only the Data StoryTelling provides "explanability", but our Chatbot also help users to answer the next 3 questions
1) Helping the user to find the Root cause (There is no cure without diagnosing the problem first)
2) checking that his action plans are solid enough (to be submited to the panel of experts that decides between several proposals)
3) proposing who should be included in this collaborative decision process (Collective Intelligence)
Jan 3, 2023·edited Jan 3, 2023Liked by Donald Farmer
Data shows virtually everyone would do better buying an index fund but they pay financial “advisors” for less accountability. The story is what the advisor sells and is cover like the story for invading Iraq. Executives won’t buy a chart shaped like a hockey stick or the number of standard deviations. I’ve resorted to art and metaphors in my last article “the cycle continues” because that is what people will read. They find thechart that they want and usually to avoid personal accountability. Latest article on this here: https://www.linkedin.com/pulse/cycle-continues-happy-new-year-2023-john-bowyer
Jan 2, 2023·edited Jan 3, 2023Liked by Donald Farmer
Excellent. This clarity makes it easier for well-grounded data storytelling to be accepted for what it does do well. True, storytelling is a hazardous tool, just as are so many other tools we use every day. Cars, for one. Data can also deceive, thanks in part to its scientific aura. Sometimes even analysts don’t notice the misrepresentations. Storytelling’s hazards are worth it. Its win-loss record before audiences full of bored or uncomprehending spectators no doubt far exceeds stark data analysis. We may have no data to support that, but I’m sure there are stories.
Just coming across this now, but it resonates. Of course, I have heard the Data Storytelling concept countless times. It never really resonated with me, perhaps because I took a lot of science classes and telling a story is not part of the scientific method.
Since Data Storytelling demonstrated such resilience, I eventually came to accept it, although with the caveat that the narrative should be non-fiction ;)
"With endless information comes the ability to take information from its context, to tell stories perfectly matched to the intentions of the teller, freed from the complex texture of reality."
– Kerry Howley, from Bottoms Up and the Devil Laughs
Profound point that is seldom mentioned. Do not tell a story about your data analysis for which the ending is predefined (as it usually is for normal stories). Thanks...
However, if data storytelling is not data analysis, then how should you tell the story behind your data analysis? Topic of your next blog? Is it like a story told by Walter Isaacson about Steve Jobs or Da Vinci? ...true to facts but profound in insights? But then, where is the call-to-action? Or, should there be?
In our AI ("Detect & Alert" insights - designed by Aldecis), Data StoryTelling is used to give explanations of why the AI highlighted these particular insights.
Because to avoid the "BlackBox" nightmare of AI, nothing (nor several graphs, nor several tables) is better than an explanation in Natural Language.
Not only the Data StoryTelling provides "explanability", but our Chatbot also help users to answer the next 3 questions
1) Helping the user to find the Root cause (There is no cure without diagnosing the problem first)
2) checking that his action plans are solid enough (to be submited to the panel of experts that decides between several proposals)
3) proposing who should be included in this collaborative decision process (Collective Intelligence)
Data shows virtually everyone would do better buying an index fund but they pay financial “advisors” for less accountability. The story is what the advisor sells and is cover like the story for invading Iraq. Executives won’t buy a chart shaped like a hockey stick or the number of standard deviations. I’ve resorted to art and metaphors in my last article “the cycle continues” because that is what people will read. They find thechart that they want and usually to avoid personal accountability. Latest article on this here: https://www.linkedin.com/pulse/cycle-continues-happy-new-year-2023-john-bowyer
Love this post! I was a design lead on Excel for seven years (my focus was on charting and data viz) and appreciate this articulation.
Excellent. This clarity makes it easier for well-grounded data storytelling to be accepted for what it does do well. True, storytelling is a hazardous tool, just as are so many other tools we use every day. Cars, for one. Data can also deceive, thanks in part to its scientific aura. Sometimes even analysts don’t notice the misrepresentations. Storytelling’s hazards are worth it. Its win-loss record before audiences full of bored or uncomprehending spectators no doubt far exceeds stark data analysis. We may have no data to support that, but I’m sure there are stories.