Let’s talk about Robotic Process Automation (RPA).

There’s a lot of well-deserved hype about this new technology already, and as a business owner or tech enthusiast, it is a bit unfortunate, if you are not leveraging from it.

RPA is big and everyone believes so. Not surprisingly, the misconceptions about RPA are promptly being debunked and replaced with greater recognition and acceptance of the power of bots. For instance, a research by Forrester predicts RPA growth to expand to $2.9 billion by 2021. Deloitte believes that RPA will achieve ‘near universal adoption’ in the next 5 years.

But before we delve into more numbers that validate RPA as a tech that’s here to stay, let’s first understand the technology better by answering the common RPA questions for customers. 

What is RPA? 

First things first – let’s understand what is robotic process automation?

Robotic process automation or RPA is a technology that allows organizations to automate repetitive tasks. It makes use of bots that emulate human actions, to capture data and share/connect with other systems to perform specific rule-based tasks. For RPA to work, the bots can seamlessly be integrated with existing IT infrastructure for maximizing returns from business processes.

Robotic Process Automation (RPA) technology has witnessed rapid evolution in the last few years with organizations across industries considering it as a more cost-effective and efficient alternative. According to a report by Mckinsey & Co., RPA is expected to have an economic impact of nearly $6.7 trillion by 2025, making it the second most impactful tech (the first being mobile internet).

Is RPA the same as AI?

When initiating into the world of robotic process automation, it is common to ponder over what is the difference between AI and RPA. Some even question the superiority between the two technologies – that is, which technology is better, RPA or Artificial Intelligence? Or even, can RPA and AI work together?

This overlapping often leads to confusion and it is not unnatural. But the two techs – RPA and AI – are not essentially the same and understanding the differences will help businesses to decipher when to deploy which.

As stated previously, RPA uses robots to automate repetitive tasks that would otherwise have been done by humans. The bots need to be programmed and can execute the tasks seamlessly, round-the-clock, with negligible errors. It cannot however make cognitive decisions.

Artificial Intelligence on the other hand, simulates human behavior and decision making. AI systems as such are intelligent or smart machines that involves a combination of problem solving, learning, thinking, speech recognition etc. and delivers accordingly.

That being said, it is also true that in recent years, there’s been greater integration between AI and RPA. AI disciplines such as computer vision and NLP is reshaping human interactions, are getting paired with RPA, and the resulting possibilities are infinite.  Eg. AI powered chatbots, that can gather data, analyze them and provide recommendations based on the input received.

How much time does it take to implement RPA?

When considering going the RPA way, it is natural for businesses to consider the time that the entire RPA implementation process will take.

At an enterprise level, a pilot RPA implementation project can take as little as two-three months, with only a few bots implemented for certain business processes. At Day One, as your RPA technology partner, we recommend a pilot or phased implementation process. This will not only help organizations to keep a check on costs incurred, but will ensure that capabilities can be scaled on requirement. A phased RPA implementation strategy moreover will also allow the organization experience the challenges first hand, while being able to measure ROI from RPA implementation.

When looking at enterprise level adoption of RPA, in one case study by SSCON it was found that scalable was ‘unbeatable’ in that the bot-based workforce could be doubled almost instantly.

In general, most RPA vendors start by implementing ten to fifteen bots only, and then scale in a planned, structured manner.

How can RPA implementation benefit organizations?

The business benefits of implementing RPA in organizations are plenty. While the most immediate advantage of RPA adoption is the organization’s ability to invest the time and effort of human resources to more critical tasks that require human intelligence and decision making, there are several other ways product and services companies can leverage automaton.

• Cost-effectiveness: When it comes to saving on dollars, there’s a lot of sense in implementing RPA software into the organization. The cost to build bots and implement them into processes amounts to a fraction of what organizations spend on their human resources. Moreover, unlike human resources, bots can function round-the-clock, maintaining their performance/productivity at all times.

• Resource optimization: One of the primary reasons why businesses are going the RPA way is for optimizing resources. RPA tools can be integrated with existing IT systems to perform the repetitive tasks efficiently. This frees up actual man hours that can be invested in carrying out high-value tasks requiring the application of intelligence and/or decision making.

• Improved customer experience: RPA bots are like the company’s virtual workforce and play a critical role in improving the customer’s engagement/experience with the brand. By performing the routine, rule-based tasks, bots free time for their human counterparts to focus on the customer-front. Also, considering that using bots, error rates are reduced, processes are more streamlined, data is more secure, turnaround time is lessened, the benefits of robotic process automation adoption facilitates customer satisfaction at all stages.

• Improved business processes: Significant improvement in business metrics can be seen with the deployment of bots and adoption of RPA technology. As bots are able to do tasks faster and with minimal errors, more gets done in less time. This however means that internal and business strategies have to be modified. For instance, for the success of the RPA initiative, the first step is to identify if RPA is the right choice or if AI for digital transformation will be a more suitable alternative, or a combination of both? Similarly, before streamlining a business process, the process bottlenecks needs to be identified and evaluated for RPS suitability.

• Data and Analytics: Robots documenting all transaction details, less manual intervention, accuracy and precision in output, reduced variance in deliverables – all of these make RPA solutions optimal for data and analytics. Bots moreover integrate with legacy IT systems to extract historical data that in turn make analytics more concrete.

• Adherence to compliance: All tasks carried out using RPA bots are recorded, and can be used for future reference and audit if required. Moreover, with bots carrying out the repetitive tasks there are reduced scope of contamination of data, in turn lessening scope of fraud or misuse. While this is true of all industries and sectors, this is more true for the Financial sector that deals with real monetary transactions and interactions.

While there are several other top advantages of RPA for organizations to onboard it, these are the most cited reasons.

Examples of Applications of RPA

RPA bots are popularly being used in industries for diverse purposes. Some prominent examples of RPA implementation include:

• Human Resources: Payroll processing, Employee onboarding

• Retail/e-Commerce: Order management, product categorization

• Insurance sector: Product information, Application document validation, claims processing

• Banking: Appointment confirmation (client facing role), product recommendation, loan approval processes, account closures

• Travel and Tourism: Payments, passenger document validation, customer support

• Utilities: Accounts and billing, customer enquiry, inventory

• Healthcare: Patient data management, billing and payments, third party vendor management

How can success from RPA implementation be measured?

There are numerous RPA vendors and partners in the market offering reliable RPA solutions, and in order to get the most ROI out of your RPA implementation, it is key to partner with a vendor who will provide custom RPA software and/or solutions.

The ROI from robotic process automation deployment differs from organization to organization, based on the number and type of processes automated. Here are some key points to keep in mind when calculating RPA ROI for business:

• Cost of the RPA software: RPA solutions costs vary according to its scope and the vendor selected.  

• Cost of implementation: Developing a RPA software is only the first step, the real cost to the company comes with implementation – especially with reference to the additional infrastructural support required, training of resources, manpower planning etc. along with the ongoing cost of maintenance or the additional cost of scaling.

• Transition cost: Measuring ROI from robotic process automation adoption is not easy, especially when there are qualitative and quantitative parameters to consider.

• Timeline: The time required for every process, to adapt and adopt digital change, so as to derive the desired outcome.

• Qualitative parameters: Difficult to measure, but the RPA ROI estimate, should also account for the qualitative costs. For instance, boost in productivity, error reduction rate/percent, time taken to resolve an issue, etc. should be mapped and given a quantitative weightage for a better ROI calculation.

The days ahead: RPA and digital transformation

Automation has been trending since long as more and more businesses realize the benefit of bringing it into their organization. New tech like blockchain is impacting global industries, and it won’t be long when RPA adoption will become the norm of the day.

The future of RPA is likely to be inclusive of more deep tech especially artificial intelligence, and a systematic drift from merely rule-based processes. Smart Process Automation (SPA), involving machine learning, cloud, big data etc. is likely to be integrated into RPA processes to build more mature bots.

RPA in the future is full of possibilities. Digital Employees and Total Workforce, which will involve intelligent digitally powered employees capable of decision making, is something organizations should gradually be gearing up for.