Emerging Trends – Robotic Process Automation Technologies

In the past few decades, Business Process Transformation has been one of the strategic focus areas for most of the Business Houses, primarily to enhance their productivity & efficiency. This also helps them laying foundation of growth & new opportunities at the same time. After successfully leveraging strategies like outsourcing, low cost locations & Business process optimization, now the focus is on “Technology”.

Exponential growth in Technology advancement clubbed with focused approach from IT Industry, is resulting in suite of amazing solution patterns having capability to solve almost every other possible use case falling under Business Process Transformation. Industry has observed exponential growth and evolution of Robotic Process Automation (RPA) technologies in last 5 Years. The growth will continue at-least for next 5 Years with primary focus on innovation and stabilization. Currently, I see the following 11 emerging trends as RPA plus in this space,

  • Multiple templates handling Capability – Leveraging Cognitive technologies to read multiple templates without hardcoding.
  • Image Reading Capability – Leveraging Cognitive technologies to read Images beyond typed text.
  • Un-structured natural language text reading Capability – Making sense out of natural language in Industrialized manner.
  • Capability to integrate advanced technologies with legacy Applications– Leveraging RPA to implement advanced Technologies without interrupting legacy.
  • Virtual workforce as-a TRUE Service – Human workforce leveraging digital workforce as and when needed, with the right alignment of RPA Infrastructure and Product licensing strategy.
  • Intelligent RPA execution – Robots execute Business processes with little more intelligence beyond pre-defined business rules.
  • Evolution of true Digital Platform – Providing capability to seamlessly integrate multiple technologies on a common platform.
  • Extending RPA to other areas – Applying RPA beyond Business Process Automation.
  • Evolution of BOT Accelerators – “Expediting process automation journey”
  • Powering Analytics – “Building data for Analytics and also Enabling real-time Analytics”
  • Business domain specific Solutions – Moving away from one-size-fit-all Approach.

Business Process Transformation Framework

Robotic Process Automation

Optical Character Recognition

Business Process Management

Process Recorder / Analyzer

Digitization at source

Artificial Intelligence



Business Process Transformation Framework

Typically, Technology levers are utilized under the wrapper of Business Process Re-engineering with strong support from Business domain knowledge and Lean concepts. These levers when applied in conjunction to each other, creates unique solution patterns helping Businesses to meet their objectives in more advanced and efficient manner.

Key technology levers in the context of business process transformation can be defined as follows,

  • Robotic Process Automation (RPA) – IT layer which mimics the way human agent interacts with IT system(s) to execute any process, typically with the help of pre-defined business logic. This also serves as orchestration layer for most of the technologies to integrate on a common platform.
  • Optical Character Recognition (OCR) – Capability to recognize text from Images.
  • Artificial Intelligence (AI) – Capability to perform tasks normally require human Intelligence, such as visual perception, text / audio / video analysis, decision making, speech recognition, etc.
  • Process Recorder / Analyzer – Capability to record any existing Business Process and provide with detailed mapping of the same. The data can further be analysed to identify efficiency gaps within the process.
  • Analytics – Capability to provide insights into the operational efficiencies and help in decision making.
  • Reporting – Capability to provide integrated operational and strategic reports for efficient management of the complete system.
  • Business Process Management (BPM) – Single platform to manage and execute the complete business process with the help of work flow management, rules engine, business domain specific user interface, integration layer with legacy applications, analytics and Reporting engine.
  • IT Infrastructure – Capability to host various technology levers in an Integrated environment, primarily considering cost, security, scalability and maintainability.
  • Digitization at source – Bouquet of technologies like mobile applications, Internet of Things (IOT), Business specific platforms, etc. to digitize data at the source. Typically, this aims at providing intuitive user interface to the end-customer.

Over the past few decades, Digital Transformation has been a key strategic focus for most business entities, primarily aimed at improving their productivity and efficiency, and, more importantly, effectively managing the growth aspect of the business. After successfully implementing strategies such as outsourcing, leveraging low-cost locations, and optimizing business processes, the focus has now shifted to “profit maximization,” “customer satisfaction,” and having a direct impact on “business metrics.” With Intelligent Process Automation moving from a “concept” to a “reality,” it is now well-positioned to take center stage in any Digital Transformation Strategy. 

1. Virtual workforce as-a TRUE Service

“Human workforce leveraging digital workforce as and when needed, with the right alignment of RPA Infrastructure and Product licensing strategy…”

Screenshot 2023-04-18 173938In last couple of Years, RPA technology has evolved at a very fast pace and now reached the stage where it is ready to move from ‘On-premise’ to ‘Cloud’ Architecture. There are still few perceived challenges in terms of security and performance of BOTs on Cloud as compared to them on-premise Architecture. This perception would slowly change with evolution of security guidelines specific to RPA and new era of BOTs on Cloud will soon be the first choice of any Business.

RPA Products typically goes with annual licensing model. Few of them are also counting on perpetual licensing model. But, no one so-far has come up with ‘Pay-per-use’ model. This has got severe impact in terms of return on Investment for any such Implementation. Also, this constraint is adversely impacting one of the biggest benefits of RPA to deal with fluctuating demand for workforce based on dynamic and seasonal nature of today’s Business. Rarely, any organization has accomplished more than 70% BOT utilization. Most of them are in-fact below 50% utilization. This clearly indicates that we are not fully utilizing our investment.

Efficient Robot monitoring & control has now become one of the key focus areas for every RPA adopters, specifically to optimize Robot utilization and effectively managing the functional and technical exceptions. Products like Thoughtonomy are investing heavily here. Also, different RPA service providers are working towards building tool agnostic platforms to address various aspects of Robot Monitoring & control. Each and very process execution comes with its own operational constraints like SLAs, fixed duration, etc. and thus impacting the BOT utilization.

Looking at all these pointers, the alignment between Infrastructure and Product becomes important and leading the Industry towards the following trends,

  • RPA Product companies becoming more innovative when it comes to pricing model and shifting towards ‘pay-per-use’ model.
  • IT Service Providers carving out a new offering of RPA (Any Product) + Infrastructure (Server or Cloud) combination as-a-Service. Thoughtonomy has certainly emerged as pioneer in this area with their partnership with BluePrism. Industry is expecting many such start-ups and even large IT service providers to enter this space in near future. Innovative pricing will certainly be the key differentiator.
  • This service offering will further get differentiated based on added features like alert engine, dynamic load balancing, data insights through advanced Analytics, agility to scale up or down, etc.

2Intelligent RPA execution

Robots to execute Business processes with little more intelligence beyond pre-defined business rules…”

Screenshot 2023-04-18 170916

RPA Technology typically differentiates itself with other technologies like scripts, macros & screen scraping by providing whole lot of capabilities like over-all orchestration, e2e process mapping, surface integration, exception handling, etc. But the true power of term, “Robot” in RPA is yet to be realized by adding more intelligence towards execution.

After stabilizing core UI / Surface integration technology, Industry is now moving towards adding adjectives like “Intelligent”, “Smart”, etc. to the Automation world, specifically by adding cognitive layer to it. Automation execution is slowly becoming more predictable with in-built cognitive & sophisticated algorithms-based features. During process execution journey, Robot often executes unknown scenarios in terms of unknown pop-ups, data sets, and may be unexpected latency. Today, RPA products are equipped with many advanced features to identify such scenarios and mark them for manual handling. But the need is to not only identify but also to execute these scenarios with accuracy.

RPA technology has got another capability to auto-create scripts from process recording but requires a good amount of effort to make it production ready. This brings us to a new trend of building capability to auto-create intelligent RPA scripts with series of process recordings over time. Imagine a situation where we deploy a component on Agent’s machine and come after a month… We have our intelligent RPA scripts ready with capability to execute process with very low exceptions.

Process Analyzer with in-built Analytics engine typically takes continuous feed of data from process recorders and carves out the complete process map with almost all the possible exceptions, which then be used to measure and improve on the operational efficiencies. If RPA technology along with AI algorithms starts using this output of Process Analyzer, we are not far away to realize benefits from self-trained BOTs. Epiplex, WorkIQ from OpenConnect and WFI from Pega are few examples to understand more about Process recorders and Analyzers.

3. Image Reading Capability

“Leveraging AI to read Images beyond typed text…”

Optical character recognition has certainly emerged as a strong robust technology to read typed text in image format. But it is not yet industrialized to read hand-written text or maybe recognizing figures in the Images. Here, AI come to rescue can complementing OCR technology in many ways like,

  • Recognizing hand-written text
  • Filling up missing information based on natural language understanding.
  • Recognizing figures like logos, signatures, faces, etc and matching them with data repository.

Be it Research scholars or large IT service provider or start-ups or RPA Products… Everyone involved has taken this challenge as a priority and is working towards industrializing the solution. Here is our next trend, where all these technical components will soon be available on a common platform.

Intuitive UI solution (may be in-built within RPA product) to configure and leverage,

  • AI powered OCR engine to read typed or hand-written text along with figures.
  • Cognitive services falling under “vision” category.

4. Un-structured natural language text reading Capability

“Making sense out of natural language in Industrialized manner…”

For last couple of decades, understanding natural language has been a favourite topic of research in AI world, but only in last few years Industry has started witnessing increased usage of this component in solving real world problems. Still long way to go… This comes with few key challenges like highly skilled human resources, huge investment, long duration to reap benefits, etc.

These set of challenges are giving rise to our new trend of having easy-to-use platform with in-built Business domain specific libraries. Cognitive services from core AI hubs like Microsoft, IBM, Google and Amazon is a good start. Industry is now witnessing a trend for an intuitive platform based on this continuously evolving cognitive services with capabilities to solve commonly encountered Business problems of extracting data from document images like driving license, passport, KYC forms, legal contracts, etc.

5. Evolution of true Digital Platform

“Providing capability to seamlessly integrate multiple technologies on a common platform…”

In the recent past, Industry has observed many strategic alliances & partnerships to bring multiple technologies on a common platform and offer unique value proposition to the industry.

Business Process Management solutions can drastically be improved with RPA primarily considering its non-intrusive nature of integration with huge chunk of existing IT. Traditionally, RPA solutions were targeting business process automation with orchestration only to the extent of in-scope processes. There was a strong need to have e2e enterprise-wide BPM solution tightly coupled with RPA technology. And this need of the industry is bringing a change where we see many strategic alliances between BPM and RPA product companies.

In Apr 2016, Pega opened the field by acquiring OpenSpan, bringing RPA and BPM on the same platform. In Feb 2017, BluePrism joined the wagon by striking strategic alliance with Appian. In Jul 2017, Automation Anywhere joined hands with IBM and then in Oct 2017, UI Path with Oracle. Looking at the very nature of BPM and RPA technologies, it was obvious to build tight integration between the two to gain e2e perspective of business processes in true sense. Apart from the technical advantage, this also enabled both the partners to eye for larger pie in the market. While technically from RPA standpoint, it has got the capability to integrate with any BPM platform but, from business perspective it becomes much easier choice if RPA to be built on top of its existing platform.

After BPM, cloud services and Artificial Intelligence is the next target for RPA products. Recently, BluePrism partnered with Microsoft Azure to launch its Operating system for the Digital workforce. This will certainly enable BluePrism to extend its offerings to comprehensively cover the digital transformation area on Cloud powered by Azure Machine Learning and Microsoft AI. The trend is now set for the industry, and we will soon see more such collaborations in the Industry.

After BPM, is it ERP? With an objective to accomplish e2e Business process execution perspective, focus here is either on building enriched library of adaptors with Industry standard BPM platforms or building the platform itself on top of RPA Products.

6. Extending RPA to other areas

“Applying RPA beyond Business Process Automation…”

While we observe RPA getting applied to many fields in future, following few areas are clearly emerging as core RPA use-cases,

  • Test Automation – Considering User Interface integration as a common element between core RPA and test automation technology, the two Industries have a got a potential to converge at some point in time. Automation Anywhere by launching “TestingAnywhere MOBILE” has certainly set the precedence here. Industry is yet to observe a few leading RPA and test automation Products to enter in each other’s space. This trend will certainly have a huge positive impact on test automation Industry.
  • IT / Apps operations automation – After successfully targeting Business Process Operations Industry, now the focus is on IT Infrastructure and Application operations. Industry has already started utilizing the concept and reaping benefits. But the real industrialization of the same is on its way.
  • Data Migration or Master Data Management – One of the biggest challenges here is to build integration with legacy applications where most of the Business logic is written at the User Interface level. Any back-end integration in this scenario is quite effort and cost consuming. Thus, RPA being non-intrusive technology comes in handy. A few enterprises have already started exploring RPA for this purpose. The evolution of RPA technology into a core digital platform will certainly extend the possibility of utilizing it more extensively for this purpose.
  • Mobile apps – RPA for Mobile… Sounds like a remote use case. But, with the explosion of Mobile Applications and Personal BOTs, soon it will become a reality where there is a need for personal RPA BOTs in mobile. WhatsApp is one example where we don’t have APIs to interact with. And in this scenario, if we need to send personalized message to Individuals then the only option is manually typing the same. Fortunately, this platform is also available on web and thus desktop RPA is a possibility. But, many mobile applications do not even having web interface and thus providing an opportunity for RPA to explore.

7. Business domain specific Solutions

“Moving away from one-size-fit-all Approach…”

After building core capabilities like natural language processing, virtual assistance, UI / Surface integration, OCR, etc., the focus here is primarily to build Business domain specific solutions. Products like WorkFusion, Thougtonomy and RedWood are investing heavily in this space. More than the product owners, many IT / BPO service providers are investing in building Business domain specific solutions like Accounts Payable, legal contract remediation, etc. to run Automation as a service.

“Disruption” is the reality of today’s Business and is keeping them on their toes to continuously innovating the way they operate. Rapid evolution of Technology is adding catalyst to the “Disruption” factor. With an objective to bring best-of-the-world technology under single umbrella and to eye for a larger pie in the market, Multiple IT brands are joining hands by leveraging their proprietary technologies and expertise. In summary, Information Technology is currently riding on its next wave to not only support but to drive Business Process Transformation.

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