Robotic Process Automation (RPA) technology is fast emerging as one of the biggest disruptive forces to drive benefits across multiple dimensions—cost savings, efficiency, accuracy, scalability, and compliance—by automating key aspects of highly skilled knowledge work. Cognitive technologies that learn, recognize, and process languages, designs, and imagines like a human are poised to transform businesses globally. The implications of such capabilities are expected to drive revolutionary transformations in every industry, particularly IT and BPO. Considering these opportunities, the global RPA industry is expected to reach a market potential of $5 billion by 2020, growing at a CAGR of 60.5 percent.
In the last decade, ERP and shared services concepts fueled the emergence and growth of IT services as a key enabler for driving cost savings and improving service efficiency. IT services industry has long been looking at the next level of radical ideas that will bring quantum savings and service improvements. Broadly, these initiatives have been plugged under the non-linear umbrella. The evolving capabilities of robotic process automation (RPA), cognitive technology fueled by big data, analytics, cloud, AI, and machine learning, holds the promise of transforming business services and creating a new category of digital labor. In fact, while the transformational powers of robotics and cognitive automation are only in their infancy stage, the work of more than 100 million knowledge workers across the globe may be impacted by automation over the next 10 years. Cognitive-powered RPA will help purge and automate the tedious and routine aspects of jobs and allow workers to concentrate on bigger tasks at hand and make good decisions and innovate. Instead of tying up talent with monotonous tasks, businesses can automate more activities and access the most appropriate and expensive skills and talent to provide input and handle exceptions on demand.
40 percent savings
An excellent example would be how we used our end-to end automation solution for a large apparel company. After deployment, the manual process, which took close to 5.6 hours, was reduced to two minutes, resulting in savings of 30 FTE (full time equivalents) of effort. As clients globally tighten their budgets and reallocate a much higher proportion from “run” to “change,” such RPA-driven solutions will need to be universally adapted.
The impact of RPA is likely to be higher in back-office processing and routine IT operations, primarily due to the predictive nature of repetitive tasks performed by the human workforce. According to HfS Research, 54 percent of its respondents believe implementing RPA could realize up to 40 percent cost savings, although the primary driver for RPA is still predictability and enhancing quality of services.
Automation in the back office
Business processes that are repetitive, structured, and rule-based in HR, F&A, logistics, procurement, and supply chain, among others, are ideal for moving into automated processes. We are already witnessing automation in financial institutions, utilities, healthcare, and telecom companies. The early adopters and significant benefits are there not just for these institutions but also for customer-facing industries such as banking. As examples, a global bank automated its processes and reduced its bad debt provision by over GBP £175 million annually and an insurance company is processing 3,000 claims a day with just 30 percent of the workforce, thanks to automation.
Automation of IT operations
There is a tremendous scope for automation even in IT operations and specifically in the areas of application maintenance and support as well as infrastructure management. With widespread adoption of digitization and cloud computing, automated infrastructure management has become a critical need for enterprises and CIOs are prioritizing it. Automation can dramatically reduce the need to manually perform high-volume IT support, workflow management, and routine infrastructure maintenance.
Implementing RPA strategy
The RPA implementation journey can broadly be defined in four phases.
The first phase is assessing RPA for fit and opportunity. This phase creates an organizational understanding of RPA and where it can be utilized and will help evaluate product vendors to determine which one(s) can best meet requirements and which integration partners are right for implementation. In this phase, it also helps to conduct proof of concepts to see it in action and increase internal support.
The second-phase focus should be to create a CoE for RPA. One way of implementing a CoE is to start at a LOB/division level, where the CoE would provide consulting services to help the LOB/division understand RPA and its benefits and would also help launch initial projects.
In the third phase, after several initial deployments in the build phase, the CoE can be scaled to the organization level from the LOB/division level. This would involve the creation of a core set of support services such as project fitment, training, and consulting. Also, the CoE should look at how deployments can be accelerated by standardizing infrastructure, creating integration frameworks, and supporting common management dashboards.
The fourth stage is where RPA becomes embedded into your normal day-to-day operations. No longer an afterthought, digital labor becomes part of organizational planning and is thought of for any new product development or project requirement.
While the primary objective of automation is to eliminate routine tasks and improve employee productivity, enterprises will also continue to leverage automation technologies to improve corporate financial performance, accelerating business growth. As digitization and automation become the norm, there will be a significant need for a new breed of workforce – the “digital labor” – that combines automation knowhow with business domain. As enterprises define, hire, train, and depute this new breed of digital labor, care must be taken to ensure that enterprise-wide adoption of automation doesn’t disrupt business continuity by properly planning and executing the necessary organization-wide changes.
Additionally, as automation becomes widely adopted inside an enterprise, there will be an increased need for crisis management skills. With increasing expectations for business performance driven by automation, tolerance for failures will be virtually non-existent.
Lastly, enterprise security considerations will become increasingly critical as automation takes center stage. As automation could be vulnerable to cyberthreats and attacks, it is imperative to build parallel capabilities to provide threat protection.
I believe that cognitive-powered RPA technology is emerging as the biggest disruptive force to drive benefits across multiple dimensions in businesses across the globe. Organizational change management will be another key consideration for large-scale deployment of automation capabilities.