Thriving On Data #4 – The Art of Data
The main issue with data is that it is often difficult to both understand and exploit for everyday knowledge workers, as it is often isolated from the actual activities they are involved in. We need to apply Data Art to embed data in the operational fabric and make intelligence to the point, insulated from the underlying data complexities, instantly consumable in the context of the interaction and therefore, instinctive in its application. Think about infographics, accessible visualization, interactive presentation technology and usable metrics as crucial elements of your evolving Data Art Palette.
Come in data science, your time is almost up!
Forget ‘move over Beethoven,’ it’s Einstein who needs to make way in the journey to the intelligent customer-centric organization.
Recent focus on data science and data consolidation has failed to address the real challenge of making information accessible and usable to ‘in-process,’ customer-facing knowledge workers without them being jettisoned into a mass of meaningless analysis, delay and interpretation. With average employees taking over 20 minutes after interruption to resettle into high-value business activity, the future of data rests firmly with data artists (yes, that’s you I am talking to Vincent, Pablo, Claude …)
Acquisition and marshaling of data is now a commodity as underlying data technology reaches a mainstream tipping point and cloud adoption accelerates further. Big data outputs remain married to the complexities of our corporate data silos, and our journey to data enlightenment remains shrouded behind a veil of Ph.D. statisticians.
With our data assets and data science heading for the divorce courts and our users increasingly frustrated by our inability to deliver meaningful insight, data art is the relationship counselor to whom we all need to look.
If we think of data science as our regular banking transactions (in short, capturing the business event data across our points of party interaction), data art is the credit card, as it enables us to make sense of our spend in a format that has personalized context and that enables our knowledge workers to continue to operate at business pace.
Does my report look fat in this? A painting by numbers guide to success
So, you are ready to ‘van Gogh’ and concede that Big Data success now requires more art than science. What are your next steps?
1) Expand your data toolkit with infographics and visualization tools
From infogr.am to easel.ly, through piktochart to visual.ly and quid we need to progressively simplify the complex using accessible visual metaphor technology.
2) Adopt non-linear intelligent presentation approaches
Armed with ‘Dan Roam’ mentality and your printed linear slide decks consigned to the waste bin, try out cloud-based visual presentation technologies such as Prezi, Sliderocket and Slideshare to consolidate your ideas from numerous consumer perspectives via a data-driven, dynamic and non-linear format.
3) Embrace Usable Metrics
With Eric Ries calling to you softly through the background music of ‘Chariots of Fire,’ take progressive action to ensure your reports and visualizations focus on a small but perfectly balanced set of metrics through which you can easily monitor the development of your business accurately and, of course, incrementally.
So whilst data science may provide our corporate data ‘pump,’ data art delivers an organizational ‘smart-meter,’ ensuring the right information is delivered efficiently into the hands of knowledge workers in the right format at the appropriate time to deliver the very best next-generation customer experience.
Moreover, it’s coming to a boardroom near you very soon.
This contribution by Simon James Gratton
Part of Capgemini’s TechnoVision 2014 update series. See the overview here.