By Harel Tayeb, CEO of Kryon Systems.
It’s difficult to imagine a more tumultuous year than 2020. The pandemic crisis that wreaked havoc on global workflows and business continuity also served as a business automation accelerator. The events of this year illuminated critical challenges and made addressing them even more essential to survival moving forward, particularly in BFSI (banking, financial services and insurance). Post-Covid-19, organizations will need to move from a tactical focus—oriented toward weathering the storm—to a strategic one. Where do we go from here? What will it take to get there? The answers to these questions are inextricably linked to more efficient, profitable operations and to three fundamental RPA (robotic process automation) developments.
Automation and Process Discovery Robots Unite
At the outset of RPA adoption, the distinction between execution automation (“unattended” and “attended”) and process discovery automation (bots that work alongside humans to identify processes for automation) made sense. When RPA was still in its infancy, enterprises had no choice but to bring in human advisers to oversee the process discovery function. These experts spent many hours identifying the best processes for automation and mapping organizations toward digital transformation.
But today, the distinction between execution automation and process discovery is disappearing. We’re moving toward a reality where attended bots will not only run automation, but also identify and map processes within your organization. Several years from now, it will be difficult to imagine how we ever worked without our desktop personal assistant that monitors our activities, completes routine tasks, and enables us to offload processes from our day-to-day job to software bots behind the scenes.
In a parallel development, bots will increasingly handle more front-office processes. Consider a financial institution looking to provide customers with more value and a ubiquitous banking process like loan or mortgage adjustments. There is no reason for that process to take weeks with multiple people working several days to complete tasks, such as information and cost reference validation. It should take just minutes. This year has shown the need to make this type of automation a reality on a much larger scale, which leads to the next prediction. Companies, along with RPA providers, must address the challenge of scaling automation.
Solving the Scale Problem with the Citizen Developer
The problem of scale is not new, but solving it now is vital to widespread RPA adoption. If enterprises are going to make investments in RPA, then providers must make it easier for organizations to scale their automation efforts and realize greater ROI. It’s a failure of the entire industry that few companies, even large enterprises, have more than 50 bots in production. Even using 50 robots as a KPI is ridiculous. We should be measuring bot deployments by the thousands.
Part of the issue lies with misaligned expectations around citizen developer output and capabilities. Expecting an accomplished finance employee, for example, who has worked as an accountant for many years to focus most of his day on developing robots is arrogant and misunderstands the concept of the citizen developer. An accountant’s passion is numbers and that’s where he wants to spend most of his time. Our job as an RPA company is to provide easy-to-use solutions that will enable him to delegate the mundane, repetitive tasks he doesn’t enjoy to a bot.
The problem of scalability is also closely tied to process discovery. Identifying which processes are best for automation and calculating the value RPA will bring are the two biggest hurdles to widespread adoption and far-reaching benefits. It’s why automated process discovery encompasses identifying work processes, mapping the main path and variants of any given process, evaluating suitability for automation, and generating workflows instantly. It saves hundreds of hours and many thousands of dollars of consultants’ time manually observing, documenting, and advising, with imprecise outcomes.
But even more important, automated process discovery provides the baseline for automation available to any employee, uncovering 80% of the automation available and ready for execution. Citizen developers need to invest most of their time in their respective business areas. The automation will automate itself, requiring citizen developers to make only minor time investments in fine-tuning bots. This is where the real change in RPA scalability comes into play.
Along with automated and cost-effective process discovery, companies must address TCO (total cost of ownership) much more specifically. Analyzing investments and quantifying the ROI and potential upsides should be a fundamental business practice. Does a $10 million investment to get 100 bots into production that will execute 200 processes behind the scenes make sense? Is there a positive ROI potential? These kinds of insights must be measured before the market can scale dramatically and achieve the full range of RPA advantages.
Oversight and Orchestration
In 2021, companies will begin to understand that there are too many interfaces to get an accurate understanding of activity within the organization from three key perspectives: productivity, efficiency and impact. Organizations will need a person, product or company to take ownership of productivity, provide direction around the activities that should be monitored, and create the plan to scale up to bring more productivity and efficiency. Imposing strict percentage increase goals and clear metrics for quantifiable improvements will be an important breakthrough. This kind of monitoring will also provide critical operational insights. RPA providers will be able to help organizations better understand exactly how employee are executing tasks from home, whether they are spending their time on one, two, or five applications, and how workflow processes vary.
In comparison to many other technologies, RPA is still young, with a lot of room for growth. But it has also matured to a point where it’s ready to exert its true power. It’s incumbent upon RPA providers to help organizations with the issues that are compromising widespread adoption. Next year, we need to make RPA deployable in a way that realizes the full value it can bring. What lies ahead is exciting. We’re just scratching the surface of what’s possible. As an industry, we’re up to the challenge. Look for far greater value and easier, more scalable RPA deployment in 2021.