By William J. Rothwell (HOF 2023)
When organizations expand globally, leaders often assume
that technology transfer is mostly about systems, machines, and processes. But
one of the most difficult forms of technology transfer is not technical at all.
It is human.
A case study from China involving Motorola University and
workforce learning initiatives dating back to the early part of this century illustrates
a challenge that remains highly relevant today: organizations often
underestimate the importance of transferring “soft skills technology” alongside
technical expertise. The lessons from that effort have important implications
not only for multinational corporations but also for organizations implementing
artificial intelligence and other transformative technologies. In the case, an
American professor—William Rothwell—wrote 10 graduate courses on Talent
Development and delivered them by himself at Beijing University and Nankai
University over an 18-month period in 1999 and 2000. The project costs were
underwritten by 32 multinational companies, with Motorola leading the group. As
part of the project, 4 Chinese professors (2 from each university) were given
free seats to attend the event so they could learn how to teach the courses.
All course materials prepared by Professor Rothwell were provided to the professors for
use in teaching the 10 graduate courses at their universities going forward. It
was essentially an effort to launch a state-of-the-art Talent Development
Master’s degree program at 2 Chinese universities. Sixty-nine students
participated from the 2 universities. Most were full-time students in MBA
programs, but a few were selected high-potential staff from Motorola and other
multinational companies.
The Real
Challenge Was Never Just Technology
In the 1990s, multinational corporations operating in
China faced a significant problem. They could find engineers and technical
specialists, but they struggled to find professionals trained in workplace
learning and performance (WLP), instructional design, training, and human
resource development.
At the time, China had limited university infrastructure
dedicated to these fields. As a result, companies had only a few options:
- Recruit
talent away from competitors
- Train
staff internally from scratch
- Hire
Chinese nationals educated abroad
- Help
build a local educational infrastructure
The fourth option was the most sustainable, but also the
most difficult. It required patience, collaboration, and long-term thinking. In
many ways, it challenged the short-term business mentality that dominates many
organizations.
This issue is remarkably similar to what organizations
face today with artificial intelligence (AI). Companies frequently invest
heavily in AI systems while neglecting the human systems needed to support
them. The result is predictable: impressive technology with disappointing
organizational outcomes.
Why Soft
Skills Matter More Than Ever
The China initiative recognized an important truth:
technical systems succeed only when human systems evolve alongside them.
Motorola University and 31 other multinational companies
working in China approached the problem strategically. They worked with Chinese
universities, multinational training networks, and corporate leaders to develop
awareness of the emerging field of workplace learning and performance. The
effort was not merely educational; it was cultural.
The initiative followed six major steps:
- Building
awareness
- Meeting
immediate workforce needs
- Delivering
advanced certificates
- Offering
university-based certificate programs
- Creating
internships
- Assessing
long-term results
Motorola worked with Penn State University, Beijing
University, and Nankai University to implement this change effort. This gradual
approach acknowledged that workforce transformation cannot occur overnight.
Sustainable change requires capability building at multiple levels
simultaneously.
That lesson is particularly important now. Organizations
implementing AI often focus almost entirely on the technology itself. They
purchase software, automate workflows, and redesign systems. But they fail to
consider how the introduction of new technology will change how people work
together to achieve results, resulting in the well-known “the productivity
paradox.”
Technology changes processes. But people determine
whether those processes improve performance. Failing to consider the human side
of the enterprise almost always leads to a failed change effort.
The
Productivity Paradox Reappears
Economists and management scholars have long discussed
the “productivity paradox,” the phenomenon in which organizations invest
heavily in new technologies without achieving proportional gains in
productivity.
One reason is simple: organizations frequently fail to
redesign work around the technology.
The case of China demonstrates the opposite approach.
Instead of merely importing training concepts, the project invested in local
capability, cultural adaptation, and institutional development. It recognized
that successful transfer requires more than technical replication. It requires
integration into the social and organizational fabric of the workforce.
Today, many AI implementations repeat the same mistakes
organizations made during earlier waves of technological change. Leaders assume
that software adoption automatically creates value. Value emerges only when
technology, leadership, structure, culture, and workforce capability align.
Without that alignment, organizations experience
confusion rather than transformation. The result is often disappointed management
expectations.
Building
Capacity Instead of Dependency
One insightful aspect of the China initiative was its
emphasis on localization.
Rather than depending indefinitely on expatriates or
imported expertise, the strategy focused on developing local professionals who
could sustain and expand the capability over time. This created long-term
organizational resilience.
That principle matters enormously today.
Organizations should avoid creating permanent dependency
on outside AI consultants or technology vendors. Instead, they should focus on
developing internal capability:
- Managers
who understand how AI changes workflows
- Employees
who can work effectively alongside intelligent systems
- HR
professionals who can redesign jobs and competencies
- Learning
leaders who can support continuous adaptation
In other words, organizations must build learning
ecosystems, not merely deploy tools. In the China case, the multinationals set
out to work with Penn State to encourage local universities to establish and
launch a new graduate program in Talent Development—sometimes called Training
and Development.
Cultural
Translation Is Essential
Another key insight from the China experience was the
importance of cultural translation.
Technology transfer is never purely technical because all
workplaces operate within cultural systems. Practices that work in one national
or organizational culture may fail in another unless adapted thoughtfully.
The project recognized the importance of local
facilitators, local partnerships, and sensitivity to Chinese educational and
organizational traditions. That helped create trust and credibility.
Modern AI initiatives require similar sensitivity.
Departments within the same organization may have different norms, fears,
communication styles, and attitudes toward automation. Leaders who ignore these
cultural realities often encounter resistance, disengagement, or passive
noncompliance.
Successful transformation requires dialogue,
participation, and trust-building.
Leadership
Must Think Long-Term
Perhaps the most important lesson from the case is that
transformational talent development requires long-term leadership commitment.
Short-term thinking often undermines strategic capability
building. Executives may prioritize quarterly metrics over investments whose
benefits emerge gradually. But sustainable organizational capability rarely
develops quickly.
The China initiative invested in partnerships, education,
and infrastructure because leaders understood that workforce capability is a
strategic asset.
The same is true for AI transformation today.
Organizations that focus only on rapid automation may
achieve temporary efficiencies while damaging long-term adaptability. By
contrast, organizations that invest in workforce development, learning systems,
and organizational alignment are more likely to achieve enduring success.
Final Thoughts
The Chinese workforce case is not simply a historical
story about multinational business expansion. It is a reminder that
organizational transformation is fundamentally human.
Technology alone does not create a competitive advantage.
Human capability, organizational learning, and cultural adaptation determine
whether technology produces meaningful results.
As organizations race to implement AI and other advanced
technologies, leaders would do well to remember the lesson demonstrated decades
ago in China: the most important technology transfer may be the transfer of
knowledge, relationships, learning systems, and leadership practices that help
people succeed together.
Organizations that integrate the human and technical sides
will be the ones most likely to thrive in the future.
This blog post is a condensed and adapted version of a
longer, full-length case study. Thoughts from other Hall of Fame members will
be appreciated as the Hall celebrates its 30th anniversary and looks forward to
how our field continues to adapt to AI and other changes in our professional
environment.
References
Reference
Yan, X., & Rothwell,
W. (2006). Motorola University: Transferring skills through strategic alliance.
In Harkins, P., Giber, D., Sobol, M., Tarquinio, M., & Carter, L. (Eds), Leading
the global workforce: Best practices from Linkage, Inc. (pp.
171-182). Jossey-Bass.
IACEHOF 30th Anniversary Celebration
The Hall of Fame is more than a recognition—it is a living
record of the people and ideas that have shaped adult and continuing education
globally
About the
Author
William J. Rothwell (HOF 2023) is
Distinguished Professor Emeritus and Academy Professor at Penn State
University, University Park. He is an author and an internationally recognized
expert in workforce development, leadership, human resource development, and
organizational change. He has written and edited numerous books on talent
management, succession planning, leadership development, and workplace learning.
His work has influenced organizations and educational institutions worldwide
through research, consulting, and executive education initiatives. He can be
reached by email at wjr9@psu.edu or by phone at 814-441-4087.