Welcoming digital workers: the CIO becomes the Chief of Staff

As IDC predicts the number of 'digital workers' entering the workforce will increase by 50 percent in the next year, we look at how to successfully onboard a digital workforce.

This is a contributed article by Neil Murphy, Global VP at ABBYY

With the speed of innovation ever increasing, businesses are trying to innovate along with it. This transformation in the workplace will result in an expansion of the responsibilities of those in charge, with the CIO at the centre of this change. As such, the CIO will have to adopt a new role as Digital Chief of Staff, alongside their tech-focused duties, to be largely responsible for the new kids in town: digital workers.

The number of digital workers entering the workforce will increase by 50 percent by 2021, according to new IDC research. With the explosion of the robotic process automation (RPA) market, there are now millions of digital workers employed at businesses around the world. So, it shouldn't be surprising that we will soon see organisations give at least one robot to every employee to augment their day-to-day activities.

But despite the promise that trillions of dollars are expected to be saved by deploying digital workers, most RPA projects fail to fully deliver on that promise. The root cause of many of these failures is that digital workers don't know how to handle unstructured content or undocumented processes - just like badly onboarded employees don't. In order to realise the return on investment in RPA and content intelligence, the CIO needs to ensure our robot colleagues are employed and onboarded appropriately.

The recruitment process

The first step for the new Digital Chief of Staff, our humble CIO, is figuring out if you really need to hire that digital worker. Given all the hype this may seem counter-intuitive, but not every process is qualified for RPA. Even worse, picking the wrong process will only lead to frustration as you try to make your digital worker perform a task it is technically unable to do.

Following rules-based decisions, rather than judgement-based, is the critical component to determining whether a process can benefit from digital workers. If your process is prone to human error and is repetitive - and especially if there is input data, and it is digitised through OCR and document capture - then the opportunity is ripe.

Further to this, it is important to avoid duplicate work and overlaps in the job function for your digital worker. Unlike humans, digital workers will tirelessly do what you ask of them, even when there are unintended results. Therefore, it is critical that digital workers' ‘managers' use process intelligence to ensure they are properly designed to avoid conflicts, and can deliver their benefits without the costly side effects of a poorly employed worker. What's more, the CIO playing a prominent role as responsible for these workers is crucial, so that existing employees know where to go to stop bad processes in their tracks.

It's also important that the process is fully documented for a digital worker, as this information is the basis of properly training the robot. Having this insight into processes means you can evaluate your current processes in their ‘baseline' state, so that process automation teams can clearly set ROI expectations, and ensure agile service delivery and that automation efforts do not produce any unintended consequences.

Getting the bots up to speed

As with our human workforce, if we want our digital workers to handle increasing complexity and process sophistication, they will need more training. However, there is no skills gap with digital workers. This training is realised through the addition of cognitive skills such as AI and machine learning-enabled content intelligence, to raise the digital IQ of digital workers.

Previously, first generation RPA bots focused on automating high-volume, relatively simple processes involving structured data with no human intervention. As enterprise demands have evolved and AI capabilities increased, digital workers are increasingly being used in processes with unstructured data, in more complex environments where humans are part of the process, and where some cognitive reasoning may be needed.

Alongside training comes evaluating performance. A common reason why RPA projects fail is because bots aren't monitored effectively and get stuck performing broken or poorly executed processes. Automating a bad process just makes bad things happen faster.

Using process intelligence to monitor digital workers ensures your automation investment is operating as expected post-deployment, especially in mixed mode scenarios where bots incorporate human assistance. Beyond digital worker monitoring, process intelligence can easily specify detailed scenarios or conditions that trigger real time alerts to the right people at the right time - to handle a bottleneck immediately or directly trigger a remediation task or process in another technology. While the employee is directly responsible for ensuring these processes go according to plan, it's the CIO who should hold ultimate responsibility over the whole workforce.

The future of work will be made up of a growing digital workforce that will take on more reasoning and decision-making, allowing them to go much further than simple automation. IDC estimates that today machines conduct 29 percent of evaluating information, reasoning and decision making, and that this will only increase from this point on.

Digital transformation has blurred the lines between organisational change and technological. To keep up, CIOs will need not only to lead digital transformation efforts both big and small, but to quickly learn the necessary HR skills to manage both humans and robots in the march of the digital workers.

Neil Murphy is the VP for Global Business Development for ABBYY. He is an internationally experienced strategic leader specialising in helping organisations transform their manually intensive business processes using the latest in innovation from Machine Learning, Intelligent OCR and Robotics Process Automation (RPA).