Getting started with robotic process automation
Imagine having an unlimited pool of office workers that you can train to do any task, across any function at your firm; that would be a valuable way to improve your productivity.
Now envision that your resource pool is not human but software, delivered from the cloud to anywhere in the world, 24 hours, 7 days a week, without needing to take a break and never making a mistake.
“It’s a very futuristic image, but thanks to robotic process automation (RPA) and other artificial intelligence (AI) technologies there’s nothing visionary about it,” said Terry Walby, Chief Executive of London-based Thoughtonomy.
Thoughtonomy has created a Virtual Workforce platform that addresses the ‘productivity of office-based workers’ not by replacing employees with virtual ones, but by ‘automating work’ and weeding out inefficiencies in day-to-day workflow processes.
Productivity in the UK has dramatically stalled since the financial crisis, growing at a mere average of 0.2 percent since. And working long hours is standard in many countries, including the US. Improving productivity in the workforce is an ongoing global challenge.
“Often businesses are hampered by the applications they use, they don’t seamlessly integrate, so employees become ‘process glue’ between various systems,” said Walby, “How many people in an office simply move information from one system to another? Those are repetitive processes created by systems that don’t talk to each other.”
To solve the problem employers could change their systems, but doing this is complex and time-consuming, Walby explained. The alternative is to automate the repetitive tasks.
For example, once Thoughtonomy’s Virtual Workforce platform is installed, employees teach it to complete certain tasks, such as onboarding a new customer to the system.
The platform then might do this simple task 100 times a day, each time creating data that it uses to self-improve. When it gets stuck it asks for help. For example, if it doesn’t understand a postcode format, it will ask a person, and then it will learn from what the person does.
The platform can also be taught to monitor one system and when an address changes within it, automatically update the information in other linked systems.
To do this, the platform combines three main technologies – the cloud, RPA/software robotics, and AI (machine learning, natural language generation) – to build a proprietary platform.
But it’s not important for employers or employees to understand the technology behind the system.
“Don’t think about the technology but the solution. If you can deliver the solution with AI, great, but it’s not important to necessarily know something uses AI or NLP but just that it works,” explained Walby.
The company wants to ‘democratise AI’, in other words, put the technology and the intricate but often confusing processes behind it, in the hands of businesses in an easy and accessible way.
It sounds relatively easy, but for the platform to produce a return on investment, does it matter what size the company is?
“If you are running an offshore service provider with thousands of workers in a processing center, then clearly you can see the benefits of increased efficiencies. However, we have built it to be non-function or task-specific, so it can do anything across different departments making it cost effective for mid-size companies,” explained Walby.
It’s important for companies to avoid being afraid of deploying technology in order to improve their processes or feel that it is too difficult to adopt, regardless of their size.
Technology can be powerful, but it can also be difficult to adopt when there are many solutions in the market, it’s sometimes hard to choose. To get the most value, start on the journey and scale up when ready, that can be done with a fairly limited investment and no risk because you are not changing any systems; it’s frictionless.