Strength in numbers: changing minds and mindsets with data-driven stories

Strength in numbers: changing minds and mindsets with data-driven stories

In 1854, physician and pioneering epidemiologist John Snow used geospatial data and a map visualisation to evidence the correlation between cases of cholera and a single water pump on Broad Street in London. By challenging prevailing beliefs about the transmission of disease through both evidence and the compelling visual communication of that evidence, Snow prompted an unprecedented investment in clean water and sanitation, ultimately leading to a significant reduction in infant mortality rates.

This is a profound example our speaker Sir Geoff Mulgan shared, of the positive impact that data and data-driven stories can have.

John Snow's map of the cholera outbreak. Black bars represent deaths. Black dot represents the water pump.

Today, with the help of technology, the tools used to gather and visualise data are becoming more and more sophisticated and accessible from open-source data to digital crowdsourcing platforms. Meanwhile, reasons to advocate for big change in areas like climate change are ever-increasing.

How we bring these two things together to be greater than what they do individually is an area that continues to emerge and is what inspired us to come together for our 2nd episode of Collective Conversations 2023: “Strength in Numbers: Changing minds and mindsets with data-driven stories.”

At Brink, in pursuit of our goal to find non-obvious solutions to non-trivial problems and make positive dents in the world, we often implement collective intelligence approaches and turn what we learn into compelling stories. We opened this conversation excited to learn more from our guest speakers Sir Geoff Mulgan and David McCandless, as well as a curated audience with a shared interest in collective intelligence and evidence-driven storytelling for positive change.

David McCandless is best known for his website Information is Beautiful and his books, like Knowledge is Beautiful (2014). David has created more than 1000 graphics that tell the story beneath the story, using data visualisation to convey ideas and bend minds. Sir Geoff Mulgan is Professor of Collective Intelligence, Public Policy and Social Innovation at University College London, and has pioneered many ideas used by governments, civil society and business,  including open innovation and collective intelligence.

The conversation was diverse and full of rich discovery, but we’ve captured just 5 of the many things that we learned on the call. Our hope is you can use these when you're constructing your own data-driven stories for positive impact in your own work.

You should never have data without a story, and never have a story without data.

Geoff shared with us that his mentor, Open University founder Michael Young, instilled within him the principle that data and stories are mutually reinforcing. Without data, stories lack a fundamental component of what’s needed to structure or support a narrative, and without stories, data alone struggles to materialise or become compelling in the human mind.

Our Collective Conversations audience had interesting reflections on this lesson, including the possible trade-offs between accuracy and approachability as different audiences will have their own needs or preferences in the balance between ‘data’ and ‘story’, the powerful and useful role that artists can play in helping people think and feel in different ways, and how multi-disciplinary collaboration can aid impactful evidence-led storytelling.

As Geoff said: “I think what anyone concerned about progressive change needs to do, is essentially what John Snow did 170 years ago: measure the things which really matter, show them in a compelling visual way, and link them to a story of diagnosis and also a story of prescription.”

David went on to outline the three elements necessary for constructing an impactful data-driven story, which he defines as a concept-driven annotated narrative sequence:

Concept: What the chart is saying, and the question the data and its framing are proposing to answer. Think of charts not as charts of data, but as answers to questions.

Annotation: Pointing out what's important, significant, or useful to deepen understanding. This could be actual literal text annotations, or as we experienced with David in our virtual room, someone speaking to and highlighting the significance. This is about cognitive support, to aid the viewer in spotting what's interesting or useful.

Narrative: Showing how everything interrelates, to create meaning and engagement. As David put it, this is about the sequence of views, angles, zooms, or movements used to narrativise the data to the audience.

Collective Intelligence is not new, but new methods and capabilities are emerging all the time

Geoff took us on a whirlwind tour of the history of Collective Intelligence methodologies and approaches revealing that they have in fact been scientifically tested for centuries, and almost certainly existed before that too - 44,000-year-old cave art in Indonesia, for instance, depicts groups of hunter-gatherers working together, we can assume, following the pooling of experience and insight. Or take the famous Galton exercise of getting people in a village to guess the weight of a cow, and finding that the aggregate of collective guesses is actually an incredibly effective way of getting close to the truth. A similar exercise was carried out in 2015 with 17,205 people, with the same result.

A visual representation of the exercise carried out in 2015

Geoff also suggested that there has been a trend towards more collective science over time, and by compiling data about the number of authors contributing to research, he evidenced that trend towards collaborative discovery and authorship from the 1960s onwards.

But this is an always-evolving field: the advent of the internet made collective knowledge repositories like Wikipedia possible, and now LLMs are enabling the instantaneous synthesis of years of scientific research.

In addition to developments in the methods for collective intelligence there is a need to improve how we transform insights from those methods into authentic and trust-worthy data-driven stories so that those insights actually drive change, as opposed to just looking clever or interesting. We are, in many ways, still understanding both collective intelligence and the utility of storytelling as core methods for learning and progress - we have started to codify our emerging principles for collective intelligence.

New methods are helping us make sense of and respond to social challenges

When done well, data-driven storytelling can represent a diversity of perspectives which as a collective allow us to see a system and various lenses on it,  rather than just one view, organisation or programme within it. In turn, this can help us to think and act systemically, working beyond our silos to mobilise resources. Geoff shared the fantastic recent example of the war in Ukraine:

“...where very early after the invasion, The public started using their digital platform to upload the locations of Russian tanks. Teams of people then assessed that information and then guided rockets and drones to shoot out the tanks. This is really a revolution in warfare using collective intelligence and mobilising thousands and thousands of citizens as part of the war effort, but through their mobile phone. And we'll see much more of that I suspect in the future.”

On the other end of the spectrum, Lil, who leads our Storytelling practice at Brink, shared an example of how a big system narrative can be shifted through the continuous sharing of stories and busting of myths. Over the last year, the Better Future’s Oxygen CoLab produced a series of videos that tell the stories of entrepreneurs across the world who are building new technology to reduce a huge oxygen inequity gap. It takes the viewer on a journey of seeing the reality behind data on the availability of oxygen in low resource settings, its link to the data around the global oxygen ecosystem, and a compelling opportunity to do something about this through the implementation of oxygen concentrators. As she explained:

“During the process over the last year or so, we've surfaced some of the narrative barriers which have prevented oxygen from being accessible in low resource settings so far. Consider things like procurement teams who might assume it's purely a tech problem, or tech companies who might assume it's purely a human problem. Entrepreneurs will tell each other that there's no viable, viable business opportunity here. There are funders who only really saw it as a problem after Covid and had to get their head around the fact that it's not exclusively a problem just around that. Through this garnering of collective intelligence and sharing of stories, we've seen that these are not the prominent narratives anymore.”

By visualising what we have come up with, we can challenge our biases

We have talked so far about the power of persuasion through data-driven storytelling but it also has its place in helping us to look objectively at what is in front of us. Particularly when gathering large quantities of intelligence and illustrating with quantitative figures, visualisation allows us to compare alternative perspectives and interrogate our own.

“If you can visualise their viewpoint, you don't have to agree with it, but you can kind of accept it and relate to it, appreciate it.”

Similarly, we have the opportunity to look for what is NOT in front of us. Which perspectives are missing? Is this data reliable? Is it possible that some data has been purposefully selected, and others purposefully left out? How do we integrate different kinds of data, community knowledge, ancestral knowledge and modern datasets? Even if we do our best to create the conditions for everyone to participate in intelligence-gathering exercises, it may only be when we make sense of that data through visuals that we spot gaps or biases.

This emerged as one of the most important points in this session, and further makes the case that the field of data driven storytelling needs to be continually shaped and improved.

Data visualisation is a powerful tool that makes the invisible, visible

Visualisation allows people, and in particular larger numbers of people, to better understand and interrogate data. More than that, the examples of compelling information design that David showed us during the conversation are a powerful tool for illuminating the kinds of complexity that many struggle to make sense of, and that can lead to linear or reductive thinking. As David said,“One thing I love about visualisation is taking the abstract, the ethereal, the celestial, these numbers that are hard to understand, and bringing them down to earth, crystallising and visualising them, and turning them into landscapes that we can explore.”

David shared many examples with us. One that particularly stuck out for the group was his “trilliondollarogram”, which highlighted among others things,  the relative cost for the world to transition to renewable energy versus, for example, the amount of money hidden in offshore tax havens.

“We've got $26.5 trillion hidden in offshore tax havens contrasted with the £16.5 trillion it would take for the world to transition to renewable energy and give us a chance at staying below two degrees global heating.”

It certainly makes you wonder what other transformative facts are hidden in plain sight regarding the allocation of our world's resources, and how visualisations like this might persuade a decision maker or two to think differently about a policy or wide reaching initiative.

Part of the $Trillions graphic -

As long as there is a clear ‘why’ we can all give data-driven storytelling a go

The audience that came together for this discussion have no doubts about the power and importance of data-driven storytelling, whilst acknowledging that the methods and processes we use to mobilise this are forever emergent and imperfect. However given that we continue to stand on the shoulders of giants like John Snow and Florence Nightingale to the growing field of experts that include David and Geoff, there seems no reason not to take a considered and experiential approach to this if you have a curiosity itch that you want to scratch.

Both David and Geoff have demonstrated through their work, if you really want to understand something, answer a question or advocate for change using evidence, there is plenty available to us as individuals, citizens, and communities to give data-driven storytelling a go, either by harnessing open source data or by collecting your own data, using the many free platforms online to bring this to life.

Read more and sign up to the Collective Conversations mailing list get updates and invites to future conversations or drop me a line at [email protected].

Thank you to everyone who came along to listen and participate in the conversation. This blog is a microcosm of collective intelligence, informed by our speakers and by the wisdom of the small but brilliant crowd who came along to listen, discuss, learn and share.

Interested in this topic, want to know more, or have some thoughts? Drop us a line at [email protected] and let's chat!