Robotic Process Automation - Key Strategies and Emerging Trends

By Nishant Goel, Vice President – Automation & AI Head, Mphasis

Looking at cost pressure, dynamic business requirements and huge IT legacy, “Automation” is slowly emerging as one of the key levers to expedite Business transformation journey for many organizations.

Robotic Process Automation (RPA) can be defined as on IT layer which mimics the way human agent interacts with the system to execute any process. The complete Automation spectrum swings between two extremes – from rule based Automation to human intelligence based Automation, supported by robust Business process management and Analytics platform. Rule based Automation is primarily targeted towards processes which are driven through defined business rules. Structured text data processing through technologies like macros, user interface or surface integration, optical character recognition, etc. falls under these left side of the spectrum. Human intelligence based Automation is targeted towards knowledge centric processes where the rules are a little fuzzy in nature and can’t be precisely defined. The process typically requires human brain to take decisions. Unstructured text data processing using sophisticated algorithms like neural network supported by core business domain knowledge repository falls under these right side of the spectrum.

It is now a proven fact that RPA has got a potential to extract 20 to 80 percent productivity improvement in any process. But the trick lies in defining the right strategy and roadmap to implement the same. Typically RPA Initiatives are driven by the Business side of the Organization with very late involvement of IT Organization. The fear of losing RPA early benefits in the over-all long term IT transformation strategy compels Business leaders to hide their initiatives. Often, this results in a huge mushroom farm of Robots, managed manually through localized teams. This poses multiple hindrances to the pace of long term IT strategy Implementation and finally slows it down considerably. This is a time to change the mindset for CIO organization and start evaluating RPA as a catalyst to their strategies. Yes, THIS IS POSSIBLE. Let’s take an example,

Considering enormous customer base, difference in their preferences of interaction style and the very nature of business itself, “Digitization at source” might be a 3-5 years long term strategy but still, RPA can effectively be designed with right hooks to the source data and implemented in 3-4 months. Good portion of benefits will then be realized much earlier than that of the previous approach and further benefits will be realized along the journey of digitization. In my view, focus towards API based echo system is the key to strike the most optimal balance between speed to drive the productivity benefits and the changes to support the dynamic nature of
the Business.

Market has observed exponential growth and evolution of RPA technologies in the last 2-3 Years. Therefore, it becomes important to have a careful selection of Products. Apart from company’s performance, credentials and their Product commercials, the other important consideration revolves around its current abilities and future roadmap. Product’s flexibility to integrate with different technologies and support enterprise level centralized Architecture to promote the virtual workforce concept in true sense, is the most important criteria to evaluate the current abilities. Alignment of Product’s roadmap with emerging trends like Artificial intelligence, business domain specific solutions and e2e Business Process management workbench, is another aspect to consider.

RPA is always implemented as a combination of virtual and manual workforce. However, split is highly skewed towards virtual workforce. RPA is designed and capable to provide 100 percent accuracy for the processed transactions but throughput varies from process to process. Typically 10-20 percent effort is kept aside for the manual workforce to handle functional and technical unknown exceptions. Return on Investment is the most important aspect to be considered while designing the Robot. Many a times, the rule of 80-20 is applied to accomplish the maximum benefits. Low volume exceptions are typically kept out of scope for the Robots.

Effective change management is the key to success of any RPA implementation. This is also one of the major reasons for most of the failures in this space. There are primarily three sets of possible changes – Process, IT infrastructure and Applications. This needs to be thought through along with the respective organizations, first to align with their roadmaps and secondly to carve out the right process for change management.

If we look at the emerging trends in this space, most of the Products are working towards increasing their breadth in the Spectrum and thus focusing on building capabilities like intelligent automation, Optical character recognition, natural language processing, virtual assistance, image and video analyzers, etc. Another group of Products are primarily focusing towards Business domain specific solutions and provide RPA as a Service offering.

RPA indeed has emerged as one of the strong levers to transform both Business & Knowledge process Organizations, if implemented in planned and structured manner.

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