Author: Dr. Bappaditya Mukhopadhyay, Professor, Great Lakes Institute of Management,
Gurgaon
As uncertainty
grips the post COVID19 phase, the definition of “new normal” keeps evolving,
one fact that strongly emerges out of the discussions and debate is that
neither the business models nor the work place dynamics will be the same as
before. The social distancing which almost all the nations, developed or
otherwise, has advocated so far, is going to be an essential part of the new
normal. “Work From Home” will be a part of an employer – employee contract.
This is amplified by the fact that a quick google search on “work for home jobs
in India”, returned 40,50,000 returns with 422 new postings regarding the same
in LinkedIn. So what will drive such change? What will be the skill
requirements in the new scenario?
grips the post COVID19 phase, the definition of “new normal” keeps evolving,
one fact that strongly emerges out of the discussions and debate is that
neither the business models nor the work place dynamics will be the same as
before. The social distancing which almost all the nations, developed or
otherwise, has advocated so far, is going to be an essential part of the new
normal. “Work From Home” will be a part of an employer – employee contract.
This is amplified by the fact that a quick google search on “work for home jobs
in India”, returned 40,50,000 returns with 422 new postings regarding the same
in LinkedIn. So what will drive such change? What will be the skill
requirements in the new scenario?
Business models
driven by Data Science has been growing steadily over the last few years. Post
COVID-19 era will only accelerate it further. While data driven decision making
and unstructured data was increasingly being used across all business
verticals, companies were reasonably behind the curve when it came to employing
them in the manufacturing process. We must race for a major disruption in the
manufacturing process owing to increased automation and using robotics. Scenes
from Sci-fi movies will become reality very soon where a handful of experts
will be running and developing complex computer simulations while the shop
floors will be ‘manned’ by robots. Decisions like these will not only be driven
by market efficiency, but also concerns about maintaining ‘social distancing’.
COVID-19 will eventually subside but the next one may not be too far way.
Businesses and Governments will endogenise such eventualities in their decision
making. This leads us to two important
questions-one, what are the new skill sets that are required and two, how does
one acquire them?
driven by Data Science has been growing steadily over the last few years. Post
COVID-19 era will only accelerate it further. While data driven decision making
and unstructured data was increasingly being used across all business
verticals, companies were reasonably behind the curve when it came to employing
them in the manufacturing process. We must race for a major disruption in the
manufacturing process owing to increased automation and using robotics. Scenes
from Sci-fi movies will become reality very soon where a handful of experts
will be running and developing complex computer simulations while the shop
floors will be ‘manned’ by robots. Decisions like these will not only be driven
by market efficiency, but also concerns about maintaining ‘social distancing’.
COVID-19 will eventually subside but the next one may not be too far way.
Businesses and Governments will endogenise such eventualities in their decision
making. This leads us to two important
questions-one, what are the new skill sets that are required and two, how does
one acquire them?
Integration of AI
ML knowledge with Business would require professionals who can blend domain
expertise with technical skills. The concept of manager will undergo change.
Our approach to adopting AI ML in workplace so far has been, a balance between
demand and supply lead. Organizations mostly applied available tools and
techniques in Data Science to solve problems and at times extracted or
generated newer data depending upon the business forecast. The future would
tilt more towards demand lead problems. For example, as a response to the
current uncertainty, more emphasis will be on immediate short run projections
and challenges. This would mean extremely precise predictions. Such predictive
modelling exercises will dominate business as well as policy making. Questions like, how do we plan against all
contingencies for each month will not be relegated as academic. To answer
these, professionals need to frame the right problem and adopt the right AI ML
tools.
ML knowledge with Business would require professionals who can blend domain
expertise with technical skills. The concept of manager will undergo change.
Our approach to adopting AI ML in workplace so far has been, a balance between
demand and supply lead. Organizations mostly applied available tools and
techniques in Data Science to solve problems and at times extracted or
generated newer data depending upon the business forecast. The future would
tilt more towards demand lead problems. For example, as a response to the
current uncertainty, more emphasis will be on immediate short run projections
and challenges. This would mean extremely precise predictions. Such predictive
modelling exercises will dominate business as well as policy making. Questions like, how do we plan against all
contingencies for each month will not be relegated as academic. To answer
these, professionals need to frame the right problem and adopt the right AI ML
tools.
The training
will undergo major transformation too. While the AI ML related training will
remain skill based, there will be now a lot of emphasis on problem structuring.
For example, one will have to integrate components of AI ML both within the
courses as well as in the program. The need will be to move away from defining
a customer in generic terms to a more nuanced definition of customers. The new
customer will be one who will now be assumed to be more digital savvy. This
would mean strategizing based on her digital footprint. The importance of
social media Analytics will occupy the centre stage. Curriculums that can
integrate traditional models with data and analysis that is in the domain of
social media will leap frog. Even the delivery of such curriculum will show a
significant shift towards online delivery. We are at an early stage, however,
innovative models to engage on line learning has already began. Perhaps this is
an area that will work in Indias’ favour too.
will undergo major transformation too. While the AI ML related training will
remain skill based, there will be now a lot of emphasis on problem structuring.
For example, one will have to integrate components of AI ML both within the
courses as well as in the program. The need will be to move away from defining
a customer in generic terms to a more nuanced definition of customers. The new
customer will be one who will now be assumed to be more digital savvy. This
would mean strategizing based on her digital footprint. The importance of
social media Analytics will occupy the centre stage. Curriculums that can
integrate traditional models with data and analysis that is in the domain of
social media will leap frog. Even the delivery of such curriculum will show a
significant shift towards online delivery. We are at an early stage, however,
innovative models to engage on line learning has already began. Perhaps this is
an area that will work in Indias’ favour too.
The success
stories in online education portal is usually measured in terms of program
completion rate. The Indian education system which crucially depends upon
“tutors” is handy as it allows constant engagement with the participants who
otherwise often struggle to complete online courses.
stories in online education portal is usually measured in terms of program
completion rate. The Indian education system which crucially depends upon
“tutors” is handy as it allows constant engagement with the participants who
otherwise often struggle to complete online courses.
Amidst all
these, there is an increasing concern that we will see more and more
individualistic approach. Social distancing would reduce the need for human to
human connect even further. While it may be too early to fathom what will be
its possible fall out, organizations will face even greater challenge to create
synergies. It is absolutely important that professionals now are both skilled
technically as well as embrace empathy. A new order awaits us.
these, there is an increasing concern that we will see more and more
individualistic approach. Social distancing would reduce the need for human to
human connect even further. While it may be too early to fathom what will be
its possible fall out, organizations will face even greater challenge to create
synergies. It is absolutely important that professionals now are both skilled
technically as well as embrace empathy. A new order awaits us.
 |
| Dr. Bappaditya Mukhopadhyay, Professor, Great Lakes Institute of Management, Gurgaon |
(Author Dr. Bappaditya Mukhopadhyay is Professor at Great Lakes Institute of Management, Gurgaon. Views expressed in the article are of the author.)
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