Digital CapGemini: Capping IT Off

The Digitisation Affect and the Future of Work


Sam Hunt

July 13, 2016

Over the last month two close friends of mine have left their corporate careers to follow other, less traditional opportunities. One has joined a start-up on the other side of the globe. The other has chosen to work as a location independent freelancer, in order to focus her energies on a social cause close to her heart. These are two examples within a much broader trend that is being referred to as the future of work.

There are a number of definitions floating around for the future of work. My favourite is “a blend of technology and social drivers are creating the conditions for a radical rethink of what it means to work.” I believe this impacts on all aspects of work from the purpose and outcomes of work, the sorts of work we do, the way we organise it, the tools we use and the locations we choose to work within.

Over the course of this short series of blogs, we will look at:

  • The digitalisation effect & the evolving jobs market,
  • Organisational structure & operating models,
  • Talent & leadership, and
  • Location & environment.

Across all of these, we will ask the questions what is changing and what does this mean for large organisations of today.

The Digitalisation Effect & the Evolving Jobs Market

In a book called The New Division of Labour, Levy and Murnane mapped a set of information processing tasks along a spectrum from simple arithmetic on one end, followed by more complicated algorithms such as predicting mortgage payback. At the other end of the spectrum were activities such as pattern recognition, communicating with natural language and detecting sarcasm. Traditionally computers have only been strong in the first couple of activities, leaving the other end of the spectrum as the domain for humans.

Driven by the continued progress of Moore’s Law, we are seeing a shift in the activities that computers can be expected to deliver. Progress in fields such as Machine Learning and Robotics are making it possible for computers to start tackling the more complex information processing tasks. For example, we are already seeing:

  • Self-driving cars completing complicated information processing to be able to navigate through busy junctions. With Just Eat, the food delivery service, announcing the use of autonomous delivery vehicles in London this summer, the impact of this technology is getting clearer and clearer.
  • Machine Learning techniques are being applied to the white collar knowledge work world of medical diagnostics and legal case identification.
  • Cheap robotics are making humanoid robots an attractive proposition to augment staff in physical environments such as bank branches and airports
  • Robotics are even getting into the most humane of fields, caring for our own. Paro the robo seal is currently being tried in care homes to alleviate loneliness and depression in residents.

As these trends continue they will have a profound impact on the workforce. This simple graphic from Frey & Osbourne’s The Future of Employment neatly shows how digital technologies are entering traditionally human areas of work.

This is not a new phenomenon. Many times before we have seen new technologies disrupt the workplace. Schumpeter, the 20th century economist, coined the phrase Creative Disruption recognising the disruptive force of new technologies along with a complimentary creative force. For example, in the early 20th century America had a large number of people employed in the piano making industry. The piano was the living room entertainment item of choice for the new American middle classes. However, as the popularity of the television grew, the number of people involved in making pianos reduced significantly to be replaced by people manufacturing the televisions and in the newly created broadcasting industry.

The digitisation effect is creating a new wave of Schumpeter Creative Disruption that will cause a further evolution in the jobs market. It will be interesting to see the new roles that emerge from the creative force.

At an individual level I believe it is important to understand the potential impact of these technologies and their role within the workplace. For large organisations, now is the time to start trialling these technologies to understand if they have a role within your enterprise. But what does this mean for jobs in future? The answer is that there are two diverging clear possible paths to be identified that are: 1) elimination of current jobs or 2) specialisation of current jobs.

Elimination of current jobs

There are trends that suggest that in the future, algorithms could substitute approximately 140 million full-time knowledge workers worldwide4. Take retail and sales occupations as an example. These jobs are likely to become susceptible to computerisation in future. The systems adopted by Netflix and Amazon to identify users’ preferences and patterns and make recommendations may, in many cases, be more accurate than those of a human salesperson1. Similarly, in the manufacturing industry some manual activities such as assembling a car on a line might be replaced by machines as they are more efficient than humans and less susceptible to error.

Specialisation of current jobs

In contrast then we have jobs requiring an up-skill of resources or that are evolving as new professions as a result of technological advancements.  An example of this is the cognitive systems engineer in the manufacturing industries. This individual is responsible for optimising the interaction between the driver and the electronic systems on an assembly line. This type of job previously did not exist. It now is in growing demand and needs to be filled with an up-skilled or a new resource. Of course, specialisation of jobs will mainly be applicable to jobs requiring perception and manipulation, creative and social intelligence. Negotiating agreements, resolving problems and co-ordinating activities are tasks that require a great deal of social intelligence and thus are further examples of where specialisation is more likely than elimination.

It will remain interesting which of the above two trends will become the more dominant one. Irrespective, it cannot be questioned that across the economy as a whole we are entering a new era of human-artificial intelligence partnership. The challenge now will not be learning how to optimise the human-artificial interaction but how to best facilitate for human beings to adapt to the new technological requirement. Let’s see who will become the master of this challenge first.


This article was written by Sam Hunt from CapGemini: Capping IT Off and was legally licensed through the NewsCred publisher network.

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