“Caress the detail, the divine detail.”
“… move from lifeless information into inspiring knowledge.”
Ok. This is about data storytelling & being a data decipherer <a job I created>. Big data … small data … right sized data … we have always had more information than we have known what to do with in business. That’s why all this ‘big data’ chatter aggravates me.
I buy the fact that with today’s technology I can get better, more granular information <and sweeping trend like information at the same time> than ever before.
I don’t think we are significantly better at using whatever data, and information, than we were in the past. Yeah, yeah, yeah. I know there are Ted Talks and presentations from very articulate dynamic speakers espousing the coming generation of ‘big data.’ I would ask everyone to note a couple of things when these people stand up and pontificate about the potential of ‘big data’ and showcase how it has actually been used:
Their examples are often <most often> anomalies to everyday business.
The information is brilliant … the usefulness is less than pragmatic
Don’t get me wrong … data used well is valuable. I am simply suggesting we love the concept of data so much we are bedazzled with gathering it … but more often have no clue what to do with the data <or misuse it>.
Anyway. I thought about data for a couple of reasons today.
I saw a piece of data research from Spotify with regard to musical tastes.
I saw an acquaintance of mine starting her company and she did a fabulous job articulating WHY you look at data and usefulness derived FROM data.
Let me go to the Spotify research first. Smartly … Spotify analyzes their data <some people in the good ole days would call this “customer research”> and identify what they call ‘taste profiles.’ Simplistically they try and understand their customer’s music tastes based on their listening habits.
“During the teenage years, we embrace music at the top of the charts more than at any other time in our lives.
As we grow older, our taste in music diverges sharply from the mainstream up to age 25, and a bit less sharply after that.”
“We’re starting to listen to ‘our’ music, not ‘the’ music. Music taste reaches maturity at age 35. Around age 42, music taste briefly curves back to the popular charts — a musical midlife crisis and attempt to harken back to our youth, perhaps?”
“Men and women listen similarly in their teens, but after that, men’s mainstream music listening decreases much faster than it does for women.
This is awesome stuff. The best part? I may actually be cool. The research suggests older music fans aren’t necessarily less cool — in fact they may be more cool in many instances. Yup. We older music fans seem to be more likely to discover artists and genres that aren’t as mainstream.
“Listeners discover less-familiar music genres that they didn’t hear on FM radio as early teens, from artists with a lower popularity rank, while they also are likely to return to the music that was popular when they were teenagers.”
My own personal satisfaction in their research aside … this use of data, or research, is an excellent example of how to use data. Working hard using data to understand customers so you can make better recommendations is smart. It sounds like common sense but many companies misuse data or have different objectives <sometimes some absurd objectives>. Working hard to use data isn’t about the amount of data you accumulate but rather identifying what data you want to capture … and how to actually read the data.
Reading data is actually an art not necessarily a skill.
I imagine I could say it is part skill with a big dose of art. Suffice it to say there are a shitload of companies & businesses in today’s business world running around building massive data collection systems, gathering ‘big data’ and then using it improperly.
Ok. Having ended on the idea of how to read data … I will move on to the fabulous articulation of what someone should seek when gathering all that ‘big data’ I mentioned upfront.
This is a nice job articulating WHY you look at data and the usefulness derived FROM data.
My focus at WatersonGarner is to deliver the most important data you may be missing – real stories about real people using your brand.
These stories reveal powerful insights that light the fuse for ideation and creativity. We weave consumer research with storytelling capability to inspire breakthrough business strategy and innovation.
My entire career, I’ve been traveling the world studying how people live, work and play so that companies can get beyond superficial consumer understanding and dig in to really knowing people.
I’ve seen provocative new insights act like a lightening rod for breakthrough business results.
This is one of the fundamental beliefs that led to the creation of WatersonGarner. My partner, Maggie Garner, and I have seen how real human stories can cut through politics and clutter to focus a business on what matters.
We know how a great human insight can build competitive advantage, drive clearer strategies, and inspire breakthrough innovation.
And most importantly, we know that when a great insight is powered by engaging design and visual storytelling, we are lighting a fuse for creativity and activation.
At WatersonGarner, real human stories lead the way to business growth.
Where others see data, we see stories.
Where others see consumers, we see real people.
Where others use corporate buzzwords, we share what people are really saying about your brand.
Where others get lost in too much information, we look for the real human story that brings everything into focus.
This is how we move from lifeless information into inspiring knowledge. This is what Insights with Soul is all about.
Co Founder at WatersonGarner, LLC
While I could haggle over a couple of things … suffice it to say that suggesting data, numbers & trends & analysis, create a human story is absolutely on target. Data sounds so cold & analytical and, well, suffice it to say the world is bigger than numbers & trends.
The world is made up of people who feel things and sense things and make lots & lots of momentary choices. Using ‘big data’ sounds like you throw all the stuff into some big black crystal balls, shake it and the answer pops up in the little screen on the ball.
It ain’t like that. Numbers often tell you where to look but knowledge comes from the nuance. The stories that are found in data are often contextual and the data itself far too often looks only at moments in time … so it takes a data decipherer to reflect upon the scattered context needed to understand the story..
“move from lifeless information into inspiring knowledge”
“focus a business on what matters”
“Where others see data, we see stories. “
Data is alive. Data is living breathing and feeling. Analysis takes a living breathing feeling individual … not just some number cruncher <person or machine>.