TECHNOLOGY AT WORK

February 2015
Citi GPS: Global Perspectives & Solutions
31
The Services industry will need to adapt
from a full-time equivalent-based industry to
an outcome-based one
A sensor is a device that detects events or
changes in quantities and provides a
corresponding output, generally as an
electrical or optical signal
problematic for the people currently doing these jobs. However, from a societal
standpoint, we note the issue is that the “knowledge” workers that lose jobs are
typically above-average wage earners, which can obviously have negative
derivative consequences. According to work done by Carl Benedikt Frey and
Michael Osborne, 58% of Office & Administrative Support occupations are at risk of
automation.
Although these numbers sound dire, we note that certain “human” attributes are
unlikely to be replicated in the near term. Humans can be empathetic; humans
exhibit judgment; strategy and management are in the realm of humans. Asking the
right question is easier for humans. Certainly the early implementations of “robotic
process automation” systems immediately removed all exceptions processing to a
human counterpart. Of course, humans have to design the software as well. But we
do sound a note of caution here as well as the fact that the concept of judgment is
an interesting one. AI-based self-learning systems can draw conclusions based on
data and they can improve over time as more data is presented to them. So, as
“data expertise” grows, does the importance of process and domain expertise
diminish?
We believe there is still a role for Services professionals in many situations, even if
this is a different role from the present time. For Services vendors, the choice is
simple – “If you can’t beat them, join them”. There are already examples of
companies such as Accenture, Cognizant, EXL Service, Infosys, WNS and
Genpact, who have been investing in the development of end-to-end platformbased
systems that derive from their knowledge of the underlying process and
(sometimes) technology. We believe this is crucial for the future as the Services
industry changes towards an outcome based model.
The Internet of Things and Advanced Sensors
Driving the rise of big data is the increasing instrumentation of our physical
environment. Take the ‘Internet of things’ (IoT), the label given to the connection of
embedded computing devices to the Internet. Smart sensors might be installed
around a building in order to give detailed and timely readings of air temperature
and quality, or attached to goods in a warehouse to enable automated inventory
control. The rise of the IoT, and the increasing sophistication of associated sensors,
has made such sensor data one of the most prominent sources of big data. 55
Gartner highlights IoT as the most hyped technology of 2014 56 and predicts that 26
billion IoT units will have been installed by 2020. 57 Further, the 2014 EMC Digital
Universe study 58 estimates that the IoT generated 2% of the digital universe
available in 2014, while forecasting that that figure will increase to 10% by 2020.
Sensor data is often coupled with new machine learning fault- and anomalydetection
algorithms to render many tasks computerisable. A broad class of
examples can be found in condition monitoring, asset management and novelty
detection, with technology substituting for closed-circuit TV (CCTV) operators,
workers examining equipment defects and those responsible for plant control or
factory monitoring. GE announced that its IoT software business, which uses
sensors to monitor locomotives, wind turbines, gas turbines and oil and gas
equipment, will be worth $1.1 billion in 2014. 59 With the IoT allowing for the remote
55 Ackerman and Guizzo (2011).
56 Gartner (2014a)
57 Gartner (2014b)
58 IDC (2014).
59 Hardy (2014).
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