Of course, the photo can also be tagged with the location, and the little angel’s favourite song from Peppa Pig can be added as a vignette. “Shall we add a vintage colour filter as well – that’s just SO original!” Maybe mum will be delighted to see the little angel looking like Rob Zombie in a yellowing photo from 1920. Maybe she’ll be a little bit concerned about the time and creativity that has gone into creating the image, instead of washing the little angel. But she clicks on Like anyway. The evening has been saved, the social codex of always liking pictures of young children has been maintained.
Modern communication platforms have created amazing opportunities for every single person to share their everyday lives with friends and family. Being able to stretch out your legs on a bathing jetty and take a selfie that’s up on Facebook one minute later is really great, and it feels especially satisfying when you take a bit of devious pleasure in the knowledge that most of your colleagues aren’t on holiday yet. And it’s better to lead than to follow; everyone playing the social game understands that. Legs-stretched-out-on-sunny-bathing-jetty MUST be posted online, just as obviously as cute pictures of kittens or children who don’t even need to be cute, but just be, well, children.
The social discourse online has largely replaced chatting over the fence with your neighbour, and it also feeds everyone’s curiosity about neighbours, former colleagues and “Jimmy from primary school, you know, the one who drove the new family car into the ditch”. Gossip has moved online.
A click. A share.
In the field of Business Intelligence we look beyond cute images of kittens – as far as possible. The web-based social discourse generates a lot of noise. Ten years ago this would just have been noise, essentially impossible to put to any worthwhile use.
Now, thanks to Facebook-Facebook, Instagram-Facebook, Messenger-Facebook and Twitter, etc., there is suddenly an opportunity to make connections, where there used to be pure guesswork, an actual understanding of what interests individual people and groups.
We people like to put figures to things. It feels more serious to see the figure 82% than to read a text that says the same thing. We like clarity, simplicity. Measurability.
What communication platforms like Facebook have created is both simple and ingenious. They have created this very measurability in social relationships and interactions. That’s an incredibly big deal! Not only does each individual voluntarily disclose information, they do it with pleasure!
It has to be acknowledged that measurability is particularly obtuse. It is not (yet) possible to rate a relationship on a scale of 1-100 – “Peter and Lotta’s Marriage is currently running at 36” … The question quickly arises, what does that mean? Really? Measurability is primarily (has been) a pure quantification. At a guess, 83 Likes is a bit better than 76 Likes.
Despite everything, this is still a giant step towards the light compared with the dark hole in which we used to be stumbling around. At an individual level this can be pointless, but in the context of a group you end up getting it sufficiently right for it to be incredibly interesting.
By combining different internal and external information flows, you create something that is greater than the parts. Instead of small glimpses of an individual’s preferences, a clearer, more usable image emerges. A search history from Google, group memberships and images you liked on Facebook, Twitter flows you’re following, mobile phone locations – all of a sudden it’s no surprise when you receive a text message from your local supermarket about “special offers on tacos” just as you happen to be standing by the Tex Mex shelf.
Or, for that matter, Resorb if you’ve parked your shopping trolley by the self-medication shelf and there was a party last night.
For banks and insurance companies, the credit and insurance assessment for a new boat can be supplemented with risk appetite in a far better way. For example, the risk class may differ between the two groups “Civil servant in Stockholm, aged 45-50” and “Car and motorcycle enthusiasts with dreams of Formula 1, garage down town and frequent speeding fines, aged 45-50”.
In the last US election, an analysis of Tweets was performed that clearly predicted the outcome of the election. The same kind of predictive analysis can be performed to capture the opinions of groups about public transport, pre-schools or individual products. The only limits are our imagination!
Facebook is an example of the tracks that everyone with an online life leaves behind them. Clicks leave tracks everywhere: Spotify knows which songs you like, Google knows what you look for and sends you adverts for suitable products, a mobile phone mast picks up your mobile phone’s location.
So next time you’re wondering “Who generates all the data, who actually produces that Big Data?”, you already know the answer.
All the Way to Value
It can be hard to know where to start work. Where do we achieve the most business benefit? Enfo is your guide and advisor to running your Business Intelligence initiative all the way to value!
Magnus Hagdahl, Chief Technology Officer / Senior Architect