Learning is the new working
Honored to be included in a research paper written by Ruggero Cesaria, Head of Learning, at Fiat Chrysler Automobiles, EMEA Region who resides in Turin, Piedmont, Italy, and with whom I corresponded during the toughest months of the Pandemic in his home country as he helped restart his industry in a thoughtful and safe way. Here’s my contribution and I’ve included Ruggero’s conclusions at the end of this post.
The point of view of Chris Pirie, former Chief Learning Officer at
Microsoft, Chief Executive Officer and founder of The Learning Futures
“For me, the phrase «learning is the new working» is a useful frame for
thinking about how we approach supporting learning in the workplace. On
one hand it reflects the fact that the increasing prevalence of technology
and the increasingly rapid pace of technological change, impacting most
of the work that people do today, creates an advantage for individuals who
have a learning mindset, and makes it necessary to approach work with
curiosity and an openness to continuous learning.
The phrase also acknowledges that learning itself is hard work. It takes
energy, focus and motivation in proportion to the unfamiliarity and
complexity of the task, concept, or behavior that needs to be learned. When
we are honest about what it takes to learn and grow, we can better create
the space and conditions for working people to be effective learners. This
is our work, I believe.
It’s also clear that to work is also to learn. Expertise is the result of
both a learning mindset and a sustained period of practice and
performance which creates a sustained feedback loop that leads to better
judgement and performance over time.
The phrase «learning in the flow of work» popularized by Josh Bersin
I think is related to this last point and reflects the fact that we now have
work and productivity technology that many people use in the workplace,
that can assist in the learning process in real time as we do our work. An
example might be as simple as auto- suggested responses in email software
that prompt you to attach the file that you mentioned in your text, or an
automated proactive suggestion of the best next steps to take for
salespersons who has slow or stuck deals in his/her Customer Relationship
Management records. These suggestions might be generated by
algorithms that track and pattern match the activities of thousands of
sellers on the same system and can recognize the most effective a sequence
of steps to successfully close a deal. This approach is powerful, because
we know that teaching works best at the point and moment of need.
If learning is necessary to create sustained value and manage
increasing complexity, and we acknowledge it is hard, then it’s logical that
we experiment with ways to accelerate and improve the learning process.
Over the last 10 years, I believe the major innovation in this space has
been the MOOC and Productivity platforms that have wired together 100’s
of millions of learners and workers who we can now “watch”, interact,
study, and learn. I believe this will generate incredible insights into
learning and collaborating.
Over the next ten years, we have an urgent task to upskill millions of displaced workers and put them to work on the digital transformation of our planet. This too I believe is our work,
perhaps our most important work.”
Digitization is leading to the incorporation of learning into work (and vice versa).
This phenomenon has four important consequences:
- learning will become more and more intrinsic to the activity carried out and
will affect the whole man-machine system. In other words, both will learn in
interaction, adding mutual value. We have synthesized this implication with the
concept of “human-machine learning”;
11 Sources: World Bank; The WorldFact, CIA; Nigerian Communication
Commission, 2019; English Proficiency Index (EF-EPI), 2019.
- “lifelong learning”, understood as the alternation, of place and time, between
study and work will be replaced by “ubiquity” and “permeation” which will
increasingly unite work and learning;
- the quali-quantitative needs of roles and skills will increasingly emerge
“bottom-up”, thanks to the automatic capture of the behavior of people and
companies. As digitization progresses, data-driven workforce planning will
compete with centralized role and competency mapping systems at national
(o*Net, Rome, Excelsior), industry sector or individual company level;
- education, learning and development will provide a new playing field and a
new competitive front for public and private oligopolists. Together with health
and green economy, they will contribute to new and different economic and
social balances at a global level.