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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