Future Trends in Robotic Process Automation
Enterprises have been undergoing a digital transformation for several years, but the pandemic has expedited their efforts significantly. Organizations globally are seeing more digital transformation in the past months than in the preceding five years. According to a recent Gartner report, global robotic process automation software revenue is projected to reach nearly $2 Billion in 2021. The RPA market is still expected to grow at double-digit rates through 2024, despite the economic pressures caused by the COVID-19 pandemic. The heavy investment towards robotic process automation indicates that digital strategy is now more important than ever before to most enterprises.
Robotic process automation typically uses a combination of user interface interactions and APIs to integrate and perform data transcription work between different enterprise and productivity applications. RPA automates repetitive human tasks by emulating the same human transaction steps, mainly via orchestrated UI interactions. Enterprises realize that RPA when applied correctly, can facilitate not just automation of “swivel-chair” processes, but could perform several other automation including triggering responses, inter-application messaging, integration between legacy applications, exception identification/handling or delivering reports. This, in turn, could support enterprises to leverage their investments in legacy applications while delivering agile processes.
Let us, deep dive, into the top future robotic process automation trends:
- Higher Focus on Safety
- RPA Cloud Deployment
- Paperwork Elimination
As organizations progress in their journey of identifying an increasing number of RPA use cases, security will definitely be a high priority. Organizations will be analyzing robust data sets to arrive at actionable insights which means the data would have to be protected. Whether it’s to ensure confidentiality in industries like healthcare or to protect customer data from hackers and identity thieves, the security framework around your processes must meet the highest industry standards. Enterprises using RPA will have greater responsibility to address the threat and mitigate the risks that come with the technology adoption.
The complexity of RPA workloads will increase as a result of RPA scaling and its use expanding to more cloud-based applications. As a result, it would not be peculiar to see bot workload sharing across platforms and multi-RPA vendor orchestration. RPA ROI will continue to increase as more enterprises increase RPA usage to get the most value from their bots. Enhanced use of RPA will help organizations yield benefits in a shorter span of time.
Enterprises are increasingly using RPA bots for extracting, filing, and processing data online. The virtual workforce of bots might be on its way to eliminate paper invoices, client forms, and everything that could be lost in the office. The bots can eliminate paperwork and ensure higher productivity for routine and mundane paperwork-related activities.
Complementary Technologies
As per Gartner’s latest report, by 2022, 80% of RPA-centric automation implementations will derive their value from complementary technologies. These complementary technologies include process mining, intelligent document processing (OCR, Computer Vision), Machine Learning & User experience.
- Workflow
- Content Ingestion
- Process Mining
- Machine Learning
- Chatbots
- Service Providers
Workflow solutions include generic process automation technologies like iBPMS and iPaaS, as well as process-specific technologies that automate industry or functional processes like strategy execution, revenue cycle management or healthcare document workflow.
Content ingestion includes technologies for intelligent document processing (IDP) that can be used to extract information from unstructured documents like invoices, images or video and convert the information into structured data for RPA manipulation.
Process mining is designed to discover, monitor and improve real processes (i.e., not assumed processes) by extracting knowledge from event logs readily available in today’s information systems. Process mining includes automated process discovery (i.e., extracting process models from an event log).
In the context of RPA, ML is used to enhance the capabilities of an RPA script beyond basic “if-then” statements, enabling greater intelligence and learning within the execution of the script. ML has enabled breakthroughs in several related “add-on” areas that are complementary to the core of RPA. RPA vendors have begun to apply ML to complementary process automation tools, such as iBPMS, process mining and content ingestion, to provide a framework to apply ML algorithms to business process problems.
A chatbot is a software component or service that allows users to apply natural language conversation to retrieve information, submit a request or complete a transaction. Users interact with business systems in the same conversational manner as they would with another person.
For many RPA buyers, professional services are needed to implement or scale RPA solutions. Three key areas emerge as areas for service providers to successfully differentiate their RPA services. First, service providers must build proprietary capabilities that enhance the performance of standard RPA solutions.
For example, many service providers compete using prebuilt RPA workflows that accelerate delivery times, accelerators to integrate custom solutions, and bundled artificial intelligence (AI) solutions that enhance basic RPA workflows. Second, service providers increasingly focus on vertical industry, domain-specific or geographic specialization. Third, growing interest in RPA managed services and a lack of RPA vendor-agnostic solutions have forced many leaders to build proprietary RPA operational platforms that enhance the overall value proposition of managed service delivery.
- Employee Experience will Become Significant
- RPA in ERP
We are all familiar with the focus on user experience over the past decade. In the recent past, companies are gradually shifting focus to a similar concept of employee experience. Considering the makeshift changes the COVID-19 pandemic made to how companies operate, there was a considerable focus to improve and enhance employee wellbeing and experience, to enhance productivity and engagement.
RPA can restructure existing working models to enhance human interactions between employees and conduct more strategic tasks meaningfully. However, on the contrary, poorly managed RPA efforts can trigger the feeling of discontentment among employees. Companies will start to focus on employee satisfaction as ardently as customer satisfaction.
Integration of ERP and RPA would lead to enhanced customer experiences. Through a centralized source of data, companies can deploy continuous triggers for one task to another. The entire process will be seamless and streamlining automation activities would become easier. On top of that, the employees would have access to the processed data without the hassle of searching in different systems.
The latest RPA trends do not stop at these above-mentioned trends. With innovation and changing requirements, RPA is moving from being an option to a necessity for being sustainable. The benefits of RPA have become extensive for all organizations and in the post-COVID era, the adoption is expected to be even more rampant. Organizations should adapt to the situation that emerges in these pandemic and post-pandemic times. RPA can open new skylines for every business and carry new potential to your organization to offer a superior and customized client experience.