Robotic Process Automation (RPA) is a bit like a macro in Excel. It mimics the activity of human beings in carrying out a task within a process and can-do repetitive stuff more quickly, accurately, and tirelessly than humans, freeing them for more value-added tasks involving emotional intelligence, reasoning and judgment. It is entirely software based (so don’t expect physical robots roaming around in your office) which can be deployed on workstations or the Cloud and performs tasks on a computer like a human does for example, launching applications, reading articles on the web, copy&pasting information, filling in forms with the added flexibility of working on 24/7/365 basis. For large back offices with data-entry or other repetitive, low judgment, high-error-prone, or compliance-needy tasks, this seems like a panacea. And the benefits go beyond cost reduction and include decreased cycle times, improved throughput, flexibility &scalability, and improved accuracy.

Various global think tanks estimate that 30-40% tasks in majority of occupations can be automated which could lead to up to USD 2 trillion savings in global workforce costs and RPA can help capture this value. Add in artificial intelligence or machine learning and you could actually get bots to do even more complex tasks, like responding to a customer email inquiry by retrieving some basic data, for example. Many companies, therefore, have rushed to install bot armies, approving pilots to configure all sorts of processes and projecting large financial outcomes to create a “zeroFTE” back office. As a result, the global RPA market grew by 63% last year and is expected to reach USD 1.3 billion this year. Telecom and IT sector being the biggest adopter, followed by the banking, financial services and insurance industries, and retail and consumer goods.

However, as companies try to scalebeyond the proof of concept the momentum starts decreasing. Installing hundreds of bots takes a lot longer and is more complex than the initial pilot. It introduces an additional architecture layer into the system, requiring more governance, security and oversight by the IT organization, already burdened with maintaining legacy systems. The economic outcomes often aren’t as rosy as originally projected. While it may be possible to automate 30 percent of tasks for the majority of occupations, that doesn’t neatly translate into a 30 percent cost reduction. People do many different things, and bots may only address some of them. Unless the process and the organization are also aligned true efficiencies don’t kick in. Also, asking operators to program bots that could take their jobs can understandably create high resistance at the front line. As a result, several programs get put on hold beyond the pilot stage. So, what is the recipe for a successful rollout and implementation?

Companies need to move beyond adopting a piece meal approach and address holistically five elements to truly achieve transformation at scale:

Awareness – Is there a common understanding of ‘RPA’ technology within the organization and is driven from the top?

Engagement – Do the frontline employees understand ‘what’s in it for me’ and are actively contributing in generating uses cases for its adoption and rollout?

Focus – Is there a clear articulation why and how does the company intends to create value from various automation initiatives?

Commitment – Are the required resources, governance mechanisms, vendors and IT infrastructure in place to scale up beyond the initial pilots?

Renewal – Are the automation initiatives periodically reviewed based on the learnings from the pilots and latest technological developments?

While the elements are quite intuitive in nature, the most common pitfall is that companies tend to concentrate only on 1-2 elements. Not only is it critical to address all five elements, but also in the right order for maximizing impact. For example, unless there is awareness at the frontline around the need for automation and how will it benefit the individual employees, there is very limited engagement on contributing to ideas/use cases. Likewise, if there is lack of focus on how the organization intends to generate value out of the automation program the initiatives don’t get the top management commitment and required resources for scale-up as the funds dry out.

Ultimately, RPA is a tool in a toolkit, just like workflow tools, lean-process maps, or six-sigma methodologies. Automation decisions must always be made with end users in mind. Companies needs to prioritise processes for automation with realisable business value and not just “good to automate” and start defining KPIs for measuring “robot” performance and realised value. If incorporating automation into a process is unnecessarily disruptive to the operator’s experience—if it involves too many new steps or requires accessing additional systems or files or unnecessary wait time—it will trigger significant resistance.

Any newly designed process should take advantage of familiar ways of working as much as possible and will only work if it has acceptance from the frontline and not perceived as a threat. Employees need to understand that RPA means they will have more interesting work in the long term. They will be relieved from repetitive and dull tasks, get more free time and can be equipped with higher-valued skills which also contributes in increasing their overall job satisfaction and promotes a culture of ‘lifelong learning’.