What's your robotic quotient?
Connecting state and local government leaders
Agencies looking to make the most of automation can use the robotic quotient framework to gauge their likelihood of success.
Even as automation, artificial intelligence and machine learning become more widely adopted, success with such tools may be elusive. To help organizations determine their likelihood of realizing value from these innovative tools, a Forrester analyst has developed the robotic quotient (RQ), a step-by-step way to gauge effectiveness.
J.P. Gownder, vice president and principal analyst, developed the model to help private- and public-sector users get past the excitement of emerging technologies so they could implement them thoughtfully and drive value.
“One thing that we recognized over the last few years … is that there was a load of hype and that organizations felt obligated to buy into the world of AI and automation,” Gownder said. “To deflate that hype, we wanted to understand what are some of the determinants of success once you’ve invested in these technologies.”
RQ is a self-assessment that uses the people, leadership, organization and trust (PLOT) framework to measure how individuals and organizations will learn from, adapt to, collaborate with and generate business results from automated entities such as robotic process automation, AI and cognitive and physical robotics, according to a June 2018 report by Gownder.
RQ compares an agency’s current state with its desired one, accounting for past experiences with automation and the perspectives of its technology, operations, business and human resources leaders. On average, the assessment will take six to 12 months, according to the report.
“It’s a method for prioritizing, so you can score yourself against where you are today, where you’d plausibly like to be tomorrow after a period of investment and then you can see where the gaps are,” Gownder said. “Where am I scoring really low? Where are the things that are inhibiting us from success?”
Within each part of PLOT, the tool considers several categories such as how employees can work alongside intelligent machines, leaders’ long-term automation strategy and the roles and skills required in this new environment. Four roles emerge as particularly necessary: analysts, automation managers, process specialists and technology experts such as developers.
The last ingredient is trust. “The specific automation technology you seek to deploy will have inherent characteristics that influence human trust,” according to the report. Those include governance and auditability, the level of determinism and its correlation with higher trust and human effects such as layoffs.
Trust acts as a technology challenge multiplier, the report says. “Adding people, leadership, and organization together and then multiplying them by the technology challenge multiplier gives you a better sense of what improvements you need to make to succeed with your automation technology plans.”
Government agencies best suited for applying RQ are those with high public engagement, Gownder said. For example, deploying a chatbot is all well and good, but employees from the call center and IT and marketing departments must be part of the discussion to understand what the chatbot does, what its limits are and what organizational structure surrounds it.
“Chatbots have a high failure rate because people are using natural language,” Gownder said. “You have to have, let’s say, data scientists on the other end to take in the data that could actually be used to make the chatbot better.”
Gownder acknowledged that the RQ model has some shortcomings. For one, it takes a long time to complete. Additionally, it has almost 40 best practices, and no organization can go after all of them at once, he said. But the takeaway is that agencies must invest in the fundamentals -- their workforce, leadership strategies and organizational support structures -- to make the most of automation.
“A lot of the success factors sit outside of the actual technology itself,” he said. “You could choose the right technology, you could implement it effectively in an error-free way, but if you don’t have the business processes and the fundamentals in place to actually make it work, you’re not going to drive the value.”