Robotics
Quotient (RQ)
What It Is &
How It Shows if You’re
Ready to Implement RPA
The Robotics
Quotient (RQ)
is a quantitative method meant
to provide a fine-grained
analysis of how competent your
business will be at implementing
AI and automation technologies.
The RQ
is a helpful measure to evaluate
your company’s readiness for
RPA, telling you which areas (e.g.
technology, processes, skills,
finance) you should improve in
order to make the most out of
digital transformation.
The RQ score
depends on 39 parameters
grouped under four categories:
people, leadership, organizational
structure and trust (the PLOT
Framework), which are assumed
to underpin best AI practices.
PLOT framework
People, leadership, and
organizational structure are all
contrasted with the category
trust - the key dimension to
assess the likelihood that RPA
implementation is profitable for
your business.
People's assessment is based on
emotional intelligence key
elements such as:
self-awareness, self-regulation,
motivation, empathy and social
skills.
Other features that are considered
when measuring people are digital
literacy, openness to lifelong
learning, and ambition to stay up
to date with technological
developments.
People
The better able
are human
employees to
understand, adapt
to and
collaborate with
non-human
coworkers by
exchanging data
and insights with
them, the higher
the company’s RQ
score.
For a company to be ready to
implement RPA, it is highly
important that the leader’s traits
are attuned to the digital era.
Leaders’ adaptability, progressive
dynamism and their capacity to
contribute to building employees’
trust in automation, would raise
the RQ score and speak in favour
of the company’s readiness to
implement RPA.
Leadership
Leaders of
organizations are
the ones who are
called to
harmonize the
digitisation
perspective with
the organization’s
adaptive potential
and with people’s
confidence that
the effort invested
in these changes
is worth it.
Digitisation requires an
organizational infrastructure that
allows performance of superior
processes, devising new roles and
titles for the employees’(e.g., bot
manager), and including these
roles in the organizational chart.
The provision of training and
mentoring opportunities is a
precondition for extending the
chart with new positions.
Organizational
structure
RQ scores
showing that a
company is
prepared to go
digital depend on
the establishment
of new structures
and processes,
well suited with an
automated
workflow.
People’s baseline level of trust
varies proportionally with specific
traits of the robotic systems, such
as transparency or determinism.
The more transparent and
deterministic a system, the easier
it is for people to understand its
whys and wherefores and to
anticipate its behaviour, hence the
more they tend to have
confidence in it.
Trust
Employees’ trust in
the effectiveness
of their
interactions with
automated
devices must be
built by proper
education.
Conclusion
The robotics quotient provides objective answers to
questions about the ability of your organisation to handle
the challenges of automation and AI, and about your
employees’ readiness to learn, adapt and work alongside
digital entities.
It is a measure that helps you decide whether non-human
coworkers can be fruitfully co-opted into attaining your
financial and managerial objectives. It also shows what you
should be doing in order to maximise the likelihood of
people and robots successfully working together.
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