Caught in the loop...daily mobile

app usage.

How many times a day do you check the apps on your smartphone or tablet?  You may well be in an information feedback loop and not realise it.  I became very interested in information feedback loops, or to give the field its full scientific name - cybernetics, when in 2007, I was observing how people used Facebook.  I was lucky, in my youth I had attended a lecture given by one of the great original thinkers in the field of cybernetics.  His name was Dr Gordon Pask, I wasn’t alone in finding his lecture difficult to follow for he was a very intense man.  Many years later I found out from an obituary that many other people could only understand roughly ten percent of what he talked about.  Nevertheless Pask’s image and his lecture stuck in the back of my mind, and it suddenly dawned on me 40 years later, what I was seeing on Facebook was what Pask had talked about in that lecture all that time ago.  You can see a short exert from a similar lecture by clicking on this link.  What Pask demonstrated, with several child’s windmill sticks, was how blowing on one windmill stick caused the other windmills to turn, and their “feedback” affected the rate that the first windmill stick turned.   In control system theory terms Gordon Pask had created a series of simple feedback loops.  In case you are not familiar with what is meant by feedback loops, a simple example would be a temperature controller attached to a hot water radiator.  Depending on the temperature set on the controller a valve will regulate the flow of hot water.  Too cold, and the regulator lets some hot water into the radiator, too hot and the valve shuts off the hot water supply, thus maintaining a constant radiator temperature.  The radiator valve regulator repeats this process continually.  What Gordon Pask demonstrated was that in a complex chain of feedback loops, a small change can have a large effect. I was vividly reminded of Gordon Pask, when I viewed the data for this chart.  Several books have recently mentioned the idea that humans are becoming the servants of computers, although they supplied little data as proof.  But people are often mere adjuncts to machines as much of today’s office work consists of people creating, tending, gathering and manipulating data to be processed by computers.  This isn’t a new idea.  The man who coined the term cybernetics for describing information feedback loops, Norbert Weiner, was well aware of the subject.  In 1950, two years after publishing his book “Cybernetics,” he published another book called “The Human Use of Human Beings,” an examination of the potential for automation and the risks of dehumanisation by machines.  What would surprise Norbert Weiner were he alive today (he died in 1964), would be how readily people are, not only adapting, but are actively seeking out interaction in feedback loops with computers.  Using quantitative data that is exactly what this PowerPoint chart shows. Last month I wrote about how people using apps instead of a browser were fragmenting the Web.  I explained the reason behind this is that using the Web on a mobile device is a pain while apps, if they are well designed, are very much easier to use.  So how many times a day do you check the apps on your smartphone or tablet?  If the answer is around 10 times a day then your behaviour conforms to the global average.  This fact, as well as the data used in the PowerPoint chart above, comes from Flurry whose analytics software is used by over 500,000 apps running across nearly 1.4 billion devices.  I frequently tell people who analyse data that dealing with averages can often be very misleading and yet sometimes it can be very useful – insights are often revealed in the frequency of the distribution and not the mean or average.  Nevertheless the average across a data set can, in the appropriate situation, also help in understanding the data. By way of demonstration I will use the distribution as well as the mean average of the data in the chart to make my comments.  To analyse their data Furry decided to segment the individuals addicted to using their mobile devices by defining addiction as somebody who checks their apps at a level six times that of the average behaviour of 10 times a day.  Those really addicted, who check their apps 60 or more times throughout the day, consisted of 13% of the total people using mobile apps in this large global sample.  Regular users were defined as people checking their apps under 16 times a day.  They made-up 56% of the nearly 1.4 billion people Flurry tracks across the globe.  Super users were those in between, checking their apps 16 to 60 times per day, and they comprised 31% of the total.  Using Flurry’s statistics I could easily work out these percentage distribution figures.  What I find incredible is that the mobile addict category is growing at four times the rate of regular users and twice the rate of the super users.  Millions of people now spend their waking hours involved in information feedback loops with their mobile apps, and you can see from this data that their behaviour becomes increasingly addictive.  Put another way: on average, just over half of all the people using mobile devices that use Flurry analytics check their apps once an hour throughout a typical 16 hour waking day.  Just under a third of people will check their apps every 30 minutes, and nearly an eighth (the addicts) will check them every 20 minutes.  The Furry data also shows that those people who are most addicted to their mobile apps are more likely to be female, and less likely to be aged over 55 years.  The younger generations who have been brought up with mobile devices have a significantly higher propensity to mobile addiction.  What both Norbert Weiner and Gordon Pask would have found absolutely amazing is how easily and enthusiastically society seems to have accepted this increasing state of constant distraction, with the concomitant loss of concentration on any task in hand, in exchange for being “in the information loop.”   Just as surprising is the fact that this interfering phenomena seems to cut right across all the globe’s major cultures.  We now live in an environment of dangerous distraction, where very, very few individuals manage to be able to focus on what they are supposed to be doing for any length of time without having to check their mobile apps. The reason I use the word dangerous is that the evidence is now clear that the result of short, brief, or even tiny, interruptions, ends up producing negative results when tasks that require sequential steps are undertaken.  These are exactly the sort of tasks that one finds in critical processes in the workplace.  Any interruption caused by checking an app disrupts an individual’s ability to remember where they were in a particular sequence.  Having checked their apps people are highly likely to make the mistake of repeating the last step or, worse still, to completely overlook a step when they resume their task.  As Simon Pask realised over 40 years ago - a small feedback loop can have major repercussions on any complex system.  Mobile devices have significantly compounded the propensity for human error because for many people keeping in the loop is far more important to them than the task with which they are engaged.  In the face of this data analysis, my advice to all employers would be to focus on engaging the younger people who can still sustain concentration on a task, although using the evidence in this chart those people will be very few and far between. May 2014    
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Caught in the loop...

daily mobile app usage.

How many times a day do you check the apps on your smartphone or tablet?  You may well be in an information feedback loop and not realise it.  I became very interested in information feedback loops, or to give the field its full scientific name - cybernetics, when in 2007, I was observing how people used Facebook.  I was lucky, in my youth I had attended a lecture given by one of the great original thinkers in the field of cybernetics.  His name was Dr Gordon Pask, I wasn’t alone in finding his lecture difficult to follow for he was a very intense man.  Many years later I found out from an obituary that many other people could only understand roughly ten percent of what he talked about.  Nevertheless Pask’s image and his lecture stuck in the back of my mind, and it suddenly dawned on me 40 years later, what I was seeing on Facebook was what Pask had talked about in that lecture all that time ago.  You can see a short exert from a similar lecture by clicking on this link.  What Pask demonstrated, with several child’s windmill sticks, was how blowing on one windmill stick caused the other windmills to turn, and their “feedback” affected the rate that the first windmill stick turned.   In control system theory terms Gordon Pask had created a series of simple feedback loops.  In case you are not familiar with what is meant by feedback loops, a simple example would be a temperature controller attached to a hot water radiator.  Depending on the temperature set on the controller a valve will regulate the flow of hot water.  Too cold, and the regulator lets some hot water into the radiator, too hot and the valve shuts off the hot water supply, thus maintaining a constant radiator temperature.  The radiator valve regulator repeats this process continually.  What Gordon Pask demonstrated was that in a complex chain of feedback loops, a small change can have a large effect. I was vividly reminded of Gordon Pask, when I viewed the data for this chart.  Several books have recently mentioned the idea that humans are becoming the servants of computers, although they supplied little data as proof.  But people are often mere adjuncts to machines as much of today’s office work consists of people creating, tending, gathering and manipulating data to be processed by computers.  This isn’t a new idea.  The man who coined the term cybernetics for describing information feedback loops, Norbert Weiner, was well aware of the subject.  In 1950, two years after publishing his book “Cybernetics,” he published another book called The Human Use of Human Beings,” an examination of the potential for automation and the risks of dehumanisation by machines.  What would surprise Norbert Weiner were he alive today (he died in 1964), would be how readily people are, not only adapting, but are actively seeking out interaction in feedback loops with computers.  Using quantitative data that is exactly what this PowerPoint chart shows. Last month I wrote about how people using apps instead of a browser were fragmenting the Web.  I explained the reason behind this is that using the Web on a mobile device is a pain while apps, if they are well designed, are very much easier to use.  So how many times a day do you check the apps on your smartphone or tablet?  If the answer is around 10 times a day then your behaviour conforms to the global average.  This fact, as well as the data used in the PowerPoint chart above, comes from Flurry whose analytics software is used by over 500,000 apps running across nearly 1.4 billion devices.  I frequently tell people who analyse data that dealing with averages can often be very misleading and yet sometimes it can be very useful – insights are often revealed in the frequency of the distribution and not the mean or average.  Nevertheless the average across a data set can, in the appropriate situation, also help in understanding the data. By way of demonstration I will use the distribution as well as the mean average of the data in the chart to make my comments.  To analyse their data Furry decided to segment the individuals addicted to using their mobile devices by defining addiction as somebody who checks their apps at a level six times that of the average behaviour of 10 times a day.  Those really addicted, who check their apps 60 or more times throughout the day, consisted of 13% of the total people using mobile apps in this large global sample.  Regular users were defined as people checking their apps under 16 times a day.  They made-up 56% of the nearly 1.4 billion people Flurry tracks across the globe.  Super users were those in between, checking their apps 16 to 60 times per day, and they comprised 31% of the total.  Using Flurry’s statistics I could easily work out these percentage distribution figures.  What I find incredible is that the mobile addict category is growing at four times the rate of regular users and twice the rate of the super users.  Millions of people now spend their waking hours involved in information feedback loops with their mobile apps, and you can see from this data that their behaviour becomes increasingly addictive.  Put another way: on average, just over half of all the people using mobile devices that use Flurry analytics check their apps once an hour throughout a typical 16 hour waking day.  Just under a third of people will check their apps every 30 minutes, and nearly an eighth (the addicts) will check them every 20 minutes.  The Furry data also shows that those people who are most addicted to their mobile apps are more likely to be female, and less likely to be aged over 55 years.  The younger generations who have been brought up with mobile devices have a significantly higher propensity to mobile addiction.  What both Norbert Weiner and Gordon Pask would have found absolutely amazing is how easily and enthusiastically society seems to have accepted this increasing state of constant distraction, with the concomitant loss of concentration on any task in hand, in exchange for being “in the information loop.”   Just as surprising is the fact that this interfering phenomena seems to cut right across all the globe’s major cultures.  We now live in an environment of dangerous distraction, where very, very few individuals manage to be able to focus on what they are supposed to be doing for any length of time without having to check their mobile apps. The reason I use the word dangerous is that the evidence is now clear that the result of short, brief, or even tiny, interruptions, ends up producing negative results when tasks that require sequential steps are undertaken.  These are exactly the sort of tasks that one finds in critical processes in the workplace.  Any interruption caused by checking an app disrupts an individual’s ability to remember where they were in a particular sequence.  Having checked their apps people are highly likely to make the mistake of repeating the last step or, worse still, to completely overlook a step when they resume their task.  As Simon Pask realised over 40 years ago - a small feedback loop can have major repercussions on any complex system.  Mobile devices have significantly compounded the propensity for human error because for many people keeping in the loop is far more important to them than the task with which they are engaged.  In the face of this data analysis, my advice to all employers would be to focus on engaging the younger people who can still sustain concentration on a task, although using the evidence in this chart those people will be very few and far between. May 2014    
Click here to download the PowerPoint chart: Click here to download the PowerPoint chart: