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RPA’s Future is Now: Lessons in Gaining Greater Business Value with Automation

Regina Viadro

VP, Co-Head East Coast, Head of RPA Competency

A lot can change in just twelve months. A year ago, many businesses viewed their RPA journey and automation strategy with mild curiosity at best. Fast forward to today, and intrigue around the promise of a simplified future has grown significantly. Organizations across many industries are quickly learning that they need to identify innovative opportunities from new technology trends in order to yield greater operational efficiency and achieve greater customer satisfaction.

EPAM has jumped head first into this rapidly growing industry, with the ultimate promise of an idyllic world where a vast majority of routine tasks are executed by robots and more complex ones are performed by more advanced robots with cognitive and decision-making abilities. While there’s no shortage of attention on the subject of RPA and Intelligent Automation, the path to successful implementation can be a challenging one at the beginning. But with a clear understanding of how exactly this technology fits into your business, the results can be very rewarding.

The Evolution of RPA: What Have We Learned?

All businesses strive for efficiency and accuracy, and most focus on using technology to make it a reality. Creating a fool-proof strategy takes time and careful consideration as implementing even the most basic technical changes can have a huge impact on operations.

The Insurance, Healthcare and Financial Services industries, in particular, are well positioned to experience the benefits of applying RPA in data-rich processes. Additionally, ideal applications of RPA can be found in HR, Procurement, Finance, Supply Chain Management, Insurance Claims Processing and Customer Service areas of the business.

Two of the most important considerations when building a strategy within these industries include improving client experience and adhering to ever-changing regulatory requirements. Ultimately, these client-centric, information-heavy focuses often underscore the need for more resources, therefore opening a window of opportunity for automation.

Intelligent Investment: Know Where you Stand with RPA

Though a relatively low percentage of companies have already invested in RPA, many are taking steps toward assessing the value it could bring to their business. In fact, 34% of large enterprises plan to invest in Intelligent Automation within the next year.

When doing so, understanding the objectives of any automation initiative and the potential benefits becomes key:

  • Is the optimization driven by cost savings or improvement in accuracy of processing data?
  • If the speed of processing is improved, what are the clear benefits of this change?
  • Could a combination of some of the factors be driving the automation and will the optimization initiative be considered successful only when multiple goals are met?
  • Should machine learning be applied to enable decision-making done by robots or should it remain at a basic automation level?


Prioritizing Business Practices with a Proof of Concept

After setting objectives, the next vital step to an effective strategy is prioritizing business practices that are ready for automation, as well as defining success criteria for each candidate. Once those things are established, the focus shifts to identifying platforms that will help reach the goals.

Starting the journey with a Proof of Concept (POC) implementation has been a common practice, but now companies employ a string of parallel POCs ranging in complexity of use cases and sophistication of platform vendors. From here, expediency in experimentation becomes crucial, decision-making is shortened, stakeholders pay attention and success parameters are scrutinized.

The POC phase of automation exploration is just as much about testing organizational readiness for an automation program as it is about verifying software product capabilities. Too often, organizations become preoccupied with verifying product functionality and not giving enough thought to setting the stage for the right governance models, and conducting due diligence on software players and system integrators.

Some key recommendations for POC phase objectives include:

  • Settling on a few very specific use cases
  • Narrowing the list of software vendors and deciding on who is best positioned to cover the most objectives
  • Learning about the organizations behind the products
  • Assessing the availability of system integrators on the market, deciding on partnerships and evaluating their competency with chosen tools
  • Exploring governance models and determining the roles needed on the enterprise side to manage operations and communication with software vendors and implementation partners


What to Look for in a Service Provider

Over the past year alone, interest in RPA has evolved within large and small organizations from being tactical to strategic. When planning RPA programs, enterprises often consider moving ahead with multiple software platform players. Competition is fierce but distinctions between products are notable and a complementary RPA platform landscape can be achieved, especially for large organizations.

As enterprises continue to scale automation programs, the demand for specific, high-end technical talent will grow exponentially and applying expertise in core engineering, enterprise architecture, data science, machine learning and business consulting will be pivotal. Keeping up with the talent demand requires investment, experimentation, creative approaches and training program discipline. Scaling global and diverse automation teams can help make the promise of the RPA evolution real.

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