Digital workers need training and onboarding – just like their human colleagues – in order to realize their potential and maximize the return of an RPA investment.
There are currently millions of digital workers employed at businesses worldwide. In fact, new research from IDC estimates that the number of digital workers – including Robotic Process Automation (RPA) platforms – will increase by 50 percent by 2021. The future of work will be comprised of robots collaborating alongside their human colleagues in a manner that complements and enhances their work and achieves greater business results.
Currently, many RPA projects fail to fully deliver their potential, despite the trillions of dollars that are expected to be saved by deploying digital workers. The root cause is often that machines don’t know how to process unstructured content. In order to realize the greatest ROI with RPA, we need to ensure our robot colleagues are trained and onboarded properly and equipped with the necessary cognitive skills to perform their jobs most effectively.
When you started a new role at your company, you probably had someone explain the company’s processes and go into detail about your responsibilities. This onboarding process was crucial to your success in your role. However, this same roadmap isn’t always being applied to the new digital workforce. The steps below serve as a guide to hiring, training and integrating a digital worker into your organization:
Step 1: The Hiring Process
The first step is determining if you really should hire that digital worker. RPA offers many benefits including streamlining processes, automating repetitive and time-consuming tasks, and increasing operational efficiencies. However, it’s important to understand that not every process is qualified for RPA. Even worse, picking the wrong process can lead to unintended consequences if digital workers perform tasks they are not “qualified” for or do not have the technical skills to implement.
To determine whether your process needs digital workers, you must ensure it follows rules-based decisions rather than judgement-based. It is a robot, after all. If your process is repetitive and especially if it is digitized through optical character recognition (OCR) and document capture, then the opportunity is ripe.
Step 2: The Job Offer
Congratulations on your new employee! But don’t get too excited. Before they settle in you’ve got a few housekeeping tasks. Ensure you avoid duplicate work and overlaps in the job function of your digital worker. To accomplish this, process intelligence technologies can be deployed to analyze processes and identify the ones that are the best fit for automation. Having this insight into processes means you can evaluate your current processes in their ‘base line’ state, so that process automation teams can clearly set ROI expectations and that automation efforts do not produce any unintended consequences.
Step 3: The Training Process
As with a human workforce, if we want our digital workforce to handle increasing complex tasks, they will need thorough training. Fortunately, there is no skills gap with digital workers, so with the right training, digital workers can hit the ground running and deliver value right away.
The most effective training for digital workers involves content intelligence technologies such as natural language processing (NLP), OCR and other technologies that equip the digital workforce with cognitive skills. As enterprise demands have evolved and AI capabilities expanded, digital workers are increasingly being used in processes with unstructured data and where some cognitive reasoning may be needed.
A prime example is in the automation of invoices. Digital workers are trained on a company’s ERP system and a handful of invoices. Over time, their Content IQ continuously increases by monitoring and learning from variations in invoice forms, data and how exceptions are handled. Equipping digital workers with content intelligence technologies enables them to automate more complex processes involving unstructured content and data.
Step 4: The Performance Evaluation
Just as human workers regularly receive performance evaluations, it’s also important for digital workers’ performance to be evaluated and improved. It’s one of the primary reasons why RPA projects fail – because robots aren’t always monitored effectively and get stuck performing poorly executed processes. Automating a bad process just makes bad things happen faster.
Using process intelligence to monitor automated workflows ensures your RPA investment is operating as expected post-deployment. Additionally, process analytics helps to ensure that the promise of economic gains are realized by calculating clear, quantifiable post-implementation cost impact. This provides data-backed justification for future automation initiatives.
Step 5: Promoting Robots
By having proof of digital workers’ performance and cost impact, you’ll be able to give bots a “promotion” and grow them at enterprise scale. However, scaling from tens to hundreds, or even hundreds to thousands, of bots requires significant command and control to ensure automation remains synchronized across every process and business system it touches. Process intelligence provides a central viewpoint to monitor all bots and the contributory role they play in the business across every operation.
The future of work will be made up of a growing digital workforce that will be able to handle more reasoning and decision-making responsibilities, allowing them to go much further than simple automation. IDC estimates that today robots oversee about 29% of reasoning and decision-making functions within an organization – and that this percentage will only continue to increase. It’s important that we are prepared for this new class of workers. Being able to manage both humans and robots is the next big skills challenge – and now is the time to learn.
An earlier version of this article appeared in Computer Business Review by Neil Murphy, VP of Global Business Development at ABBYY: A Dummies’ Guide to Digital Workers and Hiring a Robotic Assistant
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