Four Skills Tomo
ow’s Innovation Workforce Will Need
Four Skills Tomo
ow’s
Innovation Workforce Will
Need
Tucker J. Marion, Sebastian K. Fixson, and Greg Brown
The young digerati will lead innovation, but they’ll need business
awareness, an entrepreneurial attitude, bottom-line focus, and ethical
intelligence.
Throughout history, new technologies have demanded step
shifts in the skills that companies need. Like the First
Industrial Revolution’s steam-powered factories, the Second
Industrial Revolution’s mass-production tools and
techniques, and the Third Industrial Revolution’s internet-
ased technologies, the Fourth Industrial Revolution —
cu
ently being driven by the convergence of new digital,
iological, and physical technologies — is changing the
nature of work as we know it. Now the challenge is to hire
and develop the next generation of workers who will use
artificial intelligence, robotics, quantum computing, genetic
engineering, 3D printing, virtual reality, and the like in thei
jobs.
The problem, strangely enough, appears to be two-sided.
People at all levels complain bitterly about being eithe
underqualified or overqualified for the jobs that companies
advertise. In addition, local and regional imbalances among
the kinds of people companies want and the skills available
in labor pools are resulting in unfilled vacancies, slowing
down the adoption of new technologies.
Before organizations can rethink how to design jobs,
organize work, and compete for talent in a digital age, they
must systematically identify the capabilities they need now,
and over the next decade, to innovate and survive. For more
than 10 years, we’ve been studying the impact of digital
design and product development tools on organizations,
their people, and their projects. 1 We’ve found that the
competencies companies need most are business-oriented
ather than technical. That’s true even for
ick-and-morta
companies that are trying to become more digital.
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And most companies are beginning to realize that they can’t
just hire all-new workforces; there aren’t enough qualified
ecruits, and the expense would be enormous. Instead, they
need to retrain and redeploy existing employees and othe
members of their communities, in addition to hiring and
contracting new ones to fill their needs. However, rapid
technological change has rendered skill cycles shorter than
ever; key competencies of even a decade ago are passé today,
and most of tomo
ow’s jobs remain unknown.
Waiting for the fog to clear isn’t an option. Companies must
identify and develop the core skills their employees will need
going forward. Our interviews, surveys, and case studies
have revealed that most companies focus on refining the
skills their people already possess, which doesn’t prepare
existing employees or new hires for the business challenges
they’ll face when using emerging technologies in their jobs.
We’ve also found that young digerati, many of whom come
into the workforce from na
ow academic streams, are
typically more captivated by digital technologies than they
are by business problems. And yet, given the sweeping
changes that the new technologies are likely to
ing about,
companies would do well to cultivate four
oad business-
oriented competencies in tomo
ow’s innovators.
1. Omniscience
To know it all may be a godlike, even insufferable, goal. But
tomo
ow’s talent must aspire to understand everything —
or at least much more than they cu
ently do — about thei
usinesses. Employees must grasp key connections: links
etween physical machines and digital systems, between
each step of the value chain, between the company’s cu
ent
and future business models. 2 And they must know thei
customers’ businesses — how and when their customers’
products and services are used, how their customers’
organizational processes work, and the related challenges
and opportunities. That’s the only way companies will be
able to evolve from selling products and services to
delivering outcomes — a process that will likely change the
very businesses they’re in.
For instance, a major medical device manufacturer we
studied has moved from developing R&D-driven solutions
to delivering patient outcomes, which has become possible
ecause of new technologies and big data. The company
needed to quickly employ more people with a systemic
understanding of everything it does, including patient care
and rehabilitation and treatment efficacy. To move the
needle on patient outcomes, it’s critical to understand all
those aspects of the system and the associated variables.
Thus, the business will demand that existing and new
employees have a
oader understanding about the
underlying science, the delivery technologies, and the
industry than almost all of them, other than top
management, cu
ently possess. Breadth of knowledge
cannot substitute for depth, either; employees must also be
able to make deep dives into the vertical aspects of the
usiness when necessary.
Let’s consider another example: The Canadian company
Dental Wings is using recent advancements in digital design,
digital imaging, and additive manufacturing, as well as a
collaboration platform, to rethink its dental implant
usiness. From the dentist’s initial assessment to patient
ecovery, the company has started adopting new
technologies to improve its processes and provide bette
care. For instance, all-new imaging capabilities provide more
accurate pictures of the dental site that can be used not only
to create digital models for implants, but also to develop
tools to help surgeons define the optimal surgical paths. That
educes exploration of the implant site, which helps reduce
ecovery time and lowers the risk of infection. To innovate at
each step, Dental Wings’ employees need to understand how
the new processes and systems connect and work together.
The need to know more holds true for people in every
function, but especially so in R&D and product design. In
the not-too-distant future, product designers who are
designing new earth-moving equipment will have to use AI
and internet of things (IoT) sensor data to model, analyze,
develop, and modify features in near real time. Once in
the field, each prototype and its digital twin will operate
simultaneously so that the designers will have access to data
24-7. They must be trained to use it to develop
improvements for the cu
ent model on the fly as well as to
etter design the next generation of equipment.
In almost every
ick-and-mortar company, dozens of
digital platforms will have to be coordinated, the data mined,
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and the insights used in a harmonized effort between the
human team and AI systems. Orchestrating all that data,
whether from design outcomes or field performance, will
equire people who understand the value of each data point
and how all the pieces fit together. It will also require
knowledge across myriad disciplines, such as mechanical
and electrical engineering, computer sciences, and product
development, because the variables in a complex system
interact in many ways. For instance, the location of a senso
on a suspension lever (a mechanical issue) will affect the
data that the sensor electrically measures, which will in turn
affect the mathematical algorithms that determine the lever’s
accuracy. Companies whose employees can manage and
navigate complex data-based systems will be best equipped
to improve the performance of their products, reduce
maintenance costs, and attract and retain customers.
A Perfect Storm of Megatrends
Businesses tend to overlook the fact that the Fourth Industrial Revolution is gaining ground just as two other major shifts
are exace
ating the skills shortage.
First, there’s a demographic shift. With the baby boomer generation retiring and the working-age population declining in
many countries, automation will likely replace many of the people who are leaving the workforce. Succeeding generations,
such as the millennials and the centennials, seem to have different career aspirations than previous generations, as several
surveys show. i Many would prefer to work for startups rather than incumbents. However, most large companies are old.
Just 26 of the Fortune 500 companies were created in this century — like the centennials, who will soon constitute half the
U.S. workforce. These young workers have high expectations of employers, making it tough for traditional corporations to
attract the young talent they need.
Second, as technologies change the way we work, they’re creating a dynamic that differs from that of previous industrial
evolutions. In the past, technology boosted the precision and productivity of workers with manual skills, enabling them to
do tasks previously performed only by highly skilled and well-compensated artisans and craftspeople. Artificial intelligence
and robots will have the opposite effect: They will increase highly skilled workers’ precision and productivity but end up
eplacing many low-skilled workers, such as those on assembly lines, service desks, or maintenance teams. Even though
some of those professions will survive, the necessary skills are changing fast: Miners will have to operate machines remotely,
truck drivers will have to monitor self-driving rigs, and so on. Workers at all levels must learn to collaborate and coexist with
learning machines.
2. Entrepreneurial Mindset
Although it may sound obvious, innovation teams will need
to become more enterprising to succeed. They must become
oundary pushers in terms of not just the products they
wish to develop, but also the processes they use. The two are
closely linked.
In large businesses, R&D and product development teams
are organized like most other functions. They must follow
the company’s guidelines about sourcing hardware,
materials, and technologies to do their work and can use
only IT-approved tools. R&D must adhere to time-tested
procedures and rules for sharing information about o
testing prototypes and product designs. And traditional
R&D teams usually work in a centralized way, relatively
insulated from the outside.
All that works well when business is as usual, but these
are extraordinary times. R&D is meant to push technical
oundaries, so R&D teams must learn to redraw
organizational boundaries to keep pace with technological
change. Essentially, they must become digital intrapreneurs,
using the latest tools or, if necessary, creating them. That
involves experimenting with new software and systems
outside those recommended by IT, and even
developing some solutions in-house.
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For incumbents, that can be a shock to the system — most
people are used to working on proprietary systems and tools,
getting things “right” before launch, and offering bette
products over time. Moving toward open systems, beta
versions, and constant iteration can feel like a clash of
civilizations in established companies, but they need to do so
to innovate for today, as well as tomo
ow. Collaboration is
central to this effort. One study of 152 managers found that
companies that used digital tools for collaboration improved
performance — as measured by the number of concepts
and prototypes developed — during the early stages of
innovation. And another study of 400 companies showed
that