2400 years ago the concept of Data Visualization was less known, but even than Plato said “Those who tell stories rule society“.
I witnessed multiple times how storytelling triggered the Venture Capitalists (VCs) to invest. Usually my CEO (biggest BS master on our team) will start with a “60-seconds-long” short Story (VCs called them “Elevator Pitch”) and then (if interested) VCs will do a long Due Diligence Research of Data (and Specs, Docs and Code) presented by our team and after that they will spend comparable time analyzing Data Visualizations (Charts, Diagrams, Slides etc.) of our Data, trying to prove or disprove the original Story.
Some of conclusions from all these startup storytelling activity were:
Data: without Data nothing can be proved or disproved (Action needs Data!)
View: best way to analyze Data and trust it is to Visualize it (Seeing is Believing!)
Discovery of Patterns: visually discoverable trends, outliers, clusters etc. which form the basis of the Story and follow-up actions
Story: the Story (based on that Data) is the Trigger for the Actions (Story shows the Value!),
Action(s): start with drilldown to a needle in haystack, embed Data Visualization into business, it is not an Eye Candy but a practical way to improve the business
Data Visualization has 5 parts: Data (main), View (enabler), Discovery (visually discoverable Patterns), Story (trigger for Actions) and finally the 5th Element – Action!
Life is not fair: Storytellers were there people who benefited the most in the end… (no Story no Glory!).
And yes, Plato was correct – at least partially and for his time. Diagram above uses analogy with 5 Classical Greek Elements. Plato wrote about four classical elements (earth, air, water, and fire) almost 2400 years ago (citing even more ancient philosopher) and his student Aristotle added a fifth element, aithêr (aether in Latin, “ether” in English) – both men are in the center of 1st picture above.
Back to our time: the Storytelling is a hot topic; enthusiasts saying that “Data is easy, good storytelling is the challenge” http://www.resource-media.org/data-is-easy/#.URVT-aVi4aE or even that “Data Science is a Storytelling”: http://blogs.hbr.org/cs/2013/03/a_data_scientists_real_job_sto.html . Nothing can be further from the truth: my observation is that most Storytellers (with a few known exceptions like Hans Rosling or Tableau founder Pat Hanrahan) ARE NOT GOOD at visualizing but they still wish to participate in our hot Data Visualization party. All I can say is “Welcome to the party!”
It may be a challenge for me and you but not for people who had a conference about storytelling: this winter, 2/27/13 in Nashville, KY: http://www.tapestryconference.com/ :
Some more reasonable people referring to storytelling as a data journalism and narrative visualization: http://www.icharts.net/blogs/2013/pioneering-data-journalism-simon-rogers-storytelling-numbers
Tableau founder Pat Hanrahan recently talked about “Showing is Not Explaining”. In parallel, Tableau is planning (after version 8.0) to add features that support storytelling by constructing visual narratives and effective communication of ideas, see it here:
Collection of resources on storytelling topic can be found here: http://www.juiceanalytics.com/writing/the-ultimate-collection-of-data-storytelling-resources/
You may also to check what Stephen Few thinks about it here: http://www.perceptualedge.com/blog/?p=1632
Storytelling as an important part (using Greek Analogy – 4th Classical Element (Air) after Data (Earth), View (Water) and Discovery (Fire) and before Action (Aether) ) of Data Visualization has a practical effect on Visualization itself, for example:
if Data View is not needed for Story or for further Actions, then it can be hidden or removed,
if number of Data Views in Dashboard is affecting impact of (preferably short Data Story), then number of Views should be reduced (usually to 2 or 3 per dashboard),
If number of DataPoints is too large per View and affecting the triggering power of the story, then it can be reduced too (in conversations with Tableau they even recommending 5000 Datapoints per View as a threshold between Local and Server-based rendering).