I've been writing about data storytelling for a decade. The concept has grown in popularity; the underlying concepts haven't changed much.
Most courses or books will emphasize the same core concepts: focus on your audience, set up the conflict, lead your reader to resolution and action, use visualizations to deliver your messages.
These are good things if you want to convey a message with data. But if we were to put Data Storytelling on the Gartner hype curve, it would sit somewhere beyond the "Peak of Inflated Expectations" and far short of the "Plateau of Productivity." People love Data Storytelling as a concept. They struggle to make it useful in their everyday work-life.
I think it is time to reconsider and reframe Data Storytelling to make it a useful tool in our modern workplace. A few examples:
Data Storytelling v1.0 --> 🆕 Data Storytelling 2.0
One-directional presentation to an attentive audience --> 🆕 Bi-directional dialogue to an attention-starved audience
The capstone to an analytics journey --> 🆕 A set of techniques used at every stage of the journey
Visuals and language will carry the message --> 🆕 Delivering to an audience must consider Where, When, Channels, Formats.
Comprehensive narratives --> 🆕 Insights as the essential unit of communication
Target your audience --> 🆕 ...and the people your audience will share it with
Data storytellers need a collection of skills --> 🆕 Specific data storytelling skills can be applied selectively by many people