By Eoin Kennedy.
Limited Resource, Treated with Disrespect
- As babies we consumed by the now
- In youth we wish we could speed up
- As adults we squander it
- In older years we wish we had it back
Time is obviously really important but how we view it depends on multiple factors from age to circumstance but knowing how, when and where we spent our time can be critical for businesses that sell it. This is my main interest for this post especially around how people visualise time.
The theory of time management generally advocates that if we can manage our time better, we will be able to do more of the right things, be more relaxed and have more spare time to pursue other things, although there some challenges to this point of view.
Blind obedience to anything is never good.
I am involved in a project which will automatically record time spent on tasks. In the chaotic world of consultancy where people charge for their time they frequently don’t know where time went or how they spent it. They are so busy doing the work and managing the flow of information that billing can become guesswork. In the US alone it is estimated the $7.4 billion is lost per day due to poor time recording.
People tackle this problem is a variety of ways from writing down the hours, using spread sheets or inputting into specialists software but the same problem persists on remembers what you did and the onerous task of inputting it.
This an area ripe for automation and machine learning. Your phone and computer combined with a raft of applications pretty much knows what you did. We leave digital foot prints everywhere we go and with every key stroke. These devices can see who you were on the phone with, what documents you edited, what emails you sent, what websites you visited, where you physically were, what was on your screen in addition to among many other variables. Combine this with names, time spent etc and you have a granular picture of what you did, after which you apply your own intuition on how much to officially record. This has big implications for billing, future job estimation but with predictive analytics and machine learning it can greatly enhance productivity by telling you what you should be doing and plotting your week ahead.
Imagine a system that visually maps out exactly how you spent your day, compares against previous performance and starts to learn from previous activity so it can predict what the weeks and days ahead could look like.
For all this there are engineering solutions (that remove the low value grunt work) but the key is trust and more importantly usability and an understanding of how we visualise time.
First Trust. One of the biggest barriers will not be technological but human. In order for such as system to be truly effective there needs to be a high degree or trust - from trust between employer and employee, consultancy and client and trust of the platforms.
Bizarrely we already grant this level of trust to many social media sites – telling them where we are and what we are doing and even more detailed information through health trackers.
If businesses moved to a point where there was a high degree of trust new forms of contract could be developed that allow for automatically billing and full visibility of what is done on their behalf. Similarly, if managers trusted their staff more and constructed work days better with employees they could see big jumps in productivity.
Friction emergences when staff feel paranoid of big brother and companies feel they are not getting value from contactors/suppliers/consultancies.
This all involved a certain amount of change management but with pressures on talent acquisition and retention, millennials moving up through the workforce and developments in technology we will see these changes happening.
How we Visualise Time.
Developments in social media and website site/service design have irreversibly increased our expectations in how intuitive software should be and also given us another perspective in how we organise our thoughts around a timeline.
Andy Cotgreave in a post after the Tableau Conference 2016 talks about time going up and down and from left to right but he brings us right back to 1493 to look at early chronological charts up to the present.
In another Huffington Post article he show how we can cheat Benjamin Franklin quote from 1758 about “Lost time is never found again” by changing chart types.
Most of us are familiar with the regular range of chart types (courtesy of productivity apps) but the options now available are far greater.
Ref: http://www.datavizcatalogue.com/search/time.html
Visualisation (in any shape or form) is not easy and involves a number of steps ranging from emotions to association and digs deep into the human psyche.
We also have to be cognisant of other prejudices people have. Some think in terms of block calendars, some think daily going from top to bottom on a time continuum while academia time tables go left to right while the world of fitness applications think circularly, following a clock. The length of time under question can also strongly affect how we see it as John Conway points out.
ICASTIC in a fascinating video asked people to draw how they see the passage of time and what emerges is a varied and view on something people rarely question.
The more we tap into the immense amount of big data the more we can drown in it. The first wave of data scientist perfected the extraction of the data, the next wave started organising and building tools to interpret/harness it and now in a marriage of psychology and technology we see the emergence of accessible ways to gain understanding from dense information without the need for complex understanding of tables.
Take this study from A Day in the Life of Americans.
Think of all the rich data flowing underneat to give an engaging, funny and interesting visualisations of the data. This is key - it should almost be gamified with the raw data available for manipulation but largely hidden.
The global media industry with a strong lead by the Guardian has harnessed this approach in report for sometime with a focus on Data Journalism.
With these developments new disciplines have emerged with User Experience Design (UX) and User Interface Design (UI) working closely with the evolving Data Artist community. We see good/bad UX/UI in most things online but the journey that a data artist takes is equally fascinating.
Take data artist Doug McCune's approach as he looks at time and how we layer data on to. He looks at time as 12 hr, 24 hr or continuous circles and plots lines, coloured Arcs/Wedges to overlaid circles.
One of the more interesting approaches he takes called Infinity Hour Chart starts with the representation of time using the age old hour glass. From simple sketches to he uses this basic shape to first layer on hours and then shows how he can add complex data with intuitive models.
My current favourite sees time as spirals, mirroring how we learn to read a clock and one favoured by the health industry.
Which will win out who knows but this is an area that will only be cracked by digging deep into our psyche (in an area we rarely question), making simple models for manipulation and discovering new ways of extracting/monitoring what we do outside of the current automation approach.
Charts will be augmented with heat maps against activities while the new brave world of Augmented Reality is sure to push the boundaries futher as we not only visualise time but experience it in a more wholeistic manner.
What is clear is that as we layer more data onto time we need to carefully think about how we do it so that it actually helps people rather than add another level of data overload.
Future
Outside of how we see and visually interpret it, one of the big question that this, and other developments, brings up is what work will we be doing and how will this be managed.
As machines gobble up the low value tasks and data is collated and mined for useful insights what can humans do that adds value. If we reach full productivity (something not necessarily accepted as good) does it mean we actually get more free time.
Early versions of this future predicted humans having large amount of free time and courses in the 70’s educated us on how to keep gainly occupied but this has largely not materialised.
One doomsday vision of the future projects us as eventual slaves to machines but this generally ignores the human traits that are largely underutilised.
The human brain is continually evolving and as technology improves, vast parts of the population merely moves to more useful deployment of their skills.
People will clearly need to upskill but the future lies in harnessing the vast unused human potential.
