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robotics quotient

Contributor(s): Corinne Bernstein Gelb

Robotics quotient (RQ) is a way of scoring a company or individual's ability to work effectively with robots, just as intelligence quotient (IQ) tests provide a score that helps gauge human cognitive abilities. According to Forrester Research, the organization that created the RQ, it measures how well organizations learn from, adapt to, collaborate with, trust and generate business results from automated entities, including software like robotic process automation (RPA), AI (artificial intelligence), physical robotics and related systems.

RQ is aimed at helping technology leaders determine where resources need to be prioritized or improved before a company makes a major investment in the robotics realm. As a means to quantify readiness, the higher the RQ score, the more prepared a company is to handle challenges that automation and AI technologies bring. 

The RQ is comprised of 39 criteria that support AI best practices. Based upon the major players that take place in automation deployment, these characteristics focus on people, leadership, organizational structure and trust (also known as the PLOT framework). Trust is a variant that spans across the other three categories and varies depending on the type of technology. The Forrester model provides a numeric value for how deterministic (A always leads to B), probabilistic (A could lead to B as well as C or D) or transparent the technology is and how much change the technology could have on the workplace. Automation’s role in the workforce is often a sensitive issue for leaders, so a comprehensive idea of potential effects is a beneficial asset.

This was last updated in September 2018

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