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Hate data, love stories!

Do you struggle to get your colleagues to relate to your data analysis? Let’s talk storytelling with numbers. Find out how to apply a narrative to your data to so it’s more interesting and engaging for your audience.

Here at db our mission is to help clients change their digital behaviour. Our starting point is always data analysis; from as many sources as possible. We look for the true, unbiased and objective insights that can help formulate the most illuminating and effective strategies.

The data challenge.

A significant challenge many of our clients face is engaging their colleagues across functions and management teams, which ultimately affects the ability to convey the benefits of insights throughout their organisation. This challenge must be addressed so that the wider organisation can create more unified and effective strategies and make better informed decisions.

Bloody frustrating huh? Why can’t everyone see how amazing the data is, and how important the digital team’s findings are?!? There’s nothing sinister going on, it’s a consequence of common factors – a lack of understanding, people are just too busy, etc. However, there could be another more significant issue: most reporting around data is boring.

As someone taught me a while ago, the responsibility for delivering a message lies with the sender, not the receiver. So, stop complaining that no one asks questions after you’ve circulated the latest spreadsheet of numbers instead, step back and ask yourself:

  1. How can I express the data and insights in a more interesting and engaging way?
  2. How can I deliver these insights in a manner that will guarantee they are consumed and understood?

If you can crack these two challenges, you’ll have an exceptional chance of the data and insights unearthed by your digital team actually being absorbed and used by your wider organisation. And this is a fundamental step towards that wonderful future destination ‘digital optimisation’,  where we all work from the beach whilst web conferencing via the cloud.

Your data needs a story.

To start with you need to know how to go about expressing your data and insights in a more interesting and engaging way. The first question you need to ask is ‘what is the story?

If you want to immerse yourself into creating a narrative, then I suggest you read this article on the classic ‘Hero’s journey’ narrative arc beloved by Hollywood screenwriters, ‘The Karate Kid’ is a perfect application of this structure. I’m a big fan of this approach as it allows you to create a real end-to-end vision. You don’t need to use all of the stages for every story, particularly not if you are trying to build a narrative over time. The process of identifying the world you are in now, the challenges that you face, the factors that may prevent you from addressing the challenges and so on will help you think in a much more dramatic and relevant way about how you can construct a message that will actually touch people.

Another great article I discovered from Fast Co. details a new book by Jim Davies, Associate professor at Carleton University Institute of Cognitive Science. In his book Riveted: The Science of Why Jokes Make Us Laugh, Movies Make Us Cry, and Religion Makes Us Feel One with the Universe  Davies shares an interesting philosophy on what makes content compelling.

What makes a good story?

He identifies 4 key drivers of content which I think are great checkpoints for anyone looking to produce a story that effectively delivers a key message.

  1. Embrace the drama
    Human drama is at the heart of Davies’s theories – he believes that the desire for social knowledge is like ‘candy for the brain’. It doesn’t matter whether the drama is true or fictional we simply relate to characters ‘like us’.
    What’s dramatic about your data story? How can you humanise it and make it relevant to your audience? How can can you help it to sound or feel like ‘them’? Can you bring your story down to the level of its impact on one consumer, family or community?
  2. Play on people’s fears
    We’re genetically programmed to pay attention to potential threats – anything that appears dangerous. Again, it actually doesn’t matter if the perceived threat is real or fictional, immediate or distant – our brains react in the same way. Once aware our brain begins working subconsciously on how you can prevent the danger or how to react if the event occurred.
    I’m not suggesting you make stuff up,  but if you deliver bad news in an empathetic way it will prove compelling. Is your data driving at a real concern? Is it a concern that could be perceived as ‘potentially real’ for your audience?
  3. Conspiracy of hope
    This is the flipside of our fears – our desire for safety and security. These are stories that tell us our aspirations are within reach.
    So what data-led stories do you have that can help people feel like your brand or business is an important part of their journey towards their aspirations? Are your brand users living a better life in anyway? How can you prove it?
  4. Same same, but different
    We like familiarity (patterns, that’s why formula pop music works so well) but we also love incongruity – twists, plots, surprises. How are you surprising your audience? How are you reinforcing familiar themes but adding in an element of freshness? How can you tell a data story across several iterations without it becoming wallpaper? How does your narrative evolve over time?

These 4 points are great to use as reference points. If you see a story emerging and your gut tells you it’s relevant and compelling for your audience, stop and ask; ‘is it dramatic?’ , ‘is it a real concern?’, ‘is it optimistic or hopeful?’, ‘is it surprising?’ If it’s not any of those things you don’t have a compelling story. It’s time to dig deeper.

Now you have some real food for thought as to how you can really engage your colleagues through storytelling. In my next instalment I’ll be looking at how you can present your story in a more engaging way.  Go find your story!

The content and advice contained in this post may be out of date. Last updated on October 29, 2014.

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