Great things have been predicted for the future of Robotic Process Automation, with experts claiming that such technology could have a significant influence on the economy. In a recent study conducted by renowned management consultancy McKinsey & Company, Robotic Process Automation (or RPA for short) was hailed as the next big thing, with predictions estimating that automation technologies including RPA could have a financial impact of around $6.7 trillion by 2025. It was also reported that companies which adopt this tech have the potential to see a return on investment between 30 and 200% in the first year alone.
Aside from the dry financial predictions, such technology also has the potential to revolutionise the way we work - particularly for professionals in areas such as payroll. There is much speculation about the future of RPA; however, in order to understand where the technology is today and (crucially) where it will go, it’s helpful to understand the developments which preceded it.
The history
RPA is made up of a number of technologies, brought together under one toolkit to be deployed as and when needed for different automation purposes.
One of the first steps towards the innovation which would eventually lead to the creation of RPA was Machine Learning (ML). It’s widely credited that the name was first coined in 1959 by Arthur Samuel, a pioneer in the field of artificial intelligence who at the time was working for infamous computer company, IBM. Machine learning started as a scientific endeavour aimed at creating artificial intelligence.
Explorations in Machine Learning allowed computers to do a lot of interesting and useful things; enabling programs to be created that conduct complex, language-based tasks such as translation and text summarization. However, there were, and still are, limits in how computers could process language. This naturally led to the development of Natural Language Processing (NLP). This subfield of science, which begun in the 1960s, combined artificial intelligence with the interactions between computers and human languages.
The main focus of NLP was to help computers understand and process human language more accurately. Computers do not have the same understanding of natural language that humans do - for instance, they can’t ‘read between the lines’ of what a person is saying and so, NLP is dedicated to improving this. Aspects of both Machine Learning and Natural Language Processing can be seen in the RPA of today, and as RPA grows it is likely to incorporate even more aspects of these two developments.
Fast forward to the 1990s and as technology progressed further towards the establishment of RPA, there were a few more key developments. Firstly, screen scraping software made big leaps towards the creation of RPA. The technology is used for extracting data from programs, websites and documents, which is something that RPA draws on heavily.
The 90s also saw the emergence of technology which most closely resembles RPA. It was in this decade that workflow automation tools were released and AI emerged in its infancy; all of which paved the way for Robotic Process Automation.
Thanks to these developments, by the early 2000s simple RPA was developed; however, it remained relatively unknown for some time - it wasn’t until 2015 when RPA began to enter the mainstream. The basic RPA versions released in the early noughties were useful for automating repetitive tasks, however it had its limits and so-called cognitive RPA was considered to be inevitable evolution of the tech.
Cognitive RPA allows for better optical character recognition (OCR), natural language processing (NLP) and machine learning to handle semi-structured and unstructured data, expanding the efficiencies of RPA to a wider range of enterprise activities. This is the RPA we know today.
What the experts predict for its future
Just a brief look at the evolution of RPA highlights the innovation of the wider industries from which is was born and it’s clear that this thirst for advancement will likely continue as the technology grows. As a result, experts have predicted a number of effects that this may have on the current technology and its uses.
- Wider adoption of RPA
More businesses are becoming aware of the benefits of RPA and implementing it in their businesses. In 2018, the impact of RPA already became significantly larger and started to move from being used in primarily multinational organisations with large budgets into the realm of national, mid-cap and smaller businesses. As this continues through 2019, the technology will be used by more and more companies to complete a wider range of processes.
- Expansion into more sectors
As RPA becomes more mainstream and more use cases are published, the use of RPA is set to expand into a wider variety of industries including ones which hold significant power including banking, financial services and insurance, manufacturing, retail, law, and Oil and Gas.
- Development in RPA’s external process capabilities
More organisations are continuing to try RPA and witness results from it. As a result, many are being encouraged to experiment with the software’s capabilities; this is making the sector primed for innovations and new applications will naturally soon emerge. As RPA is currently focused on business’ internal processes, it is thought that as innovation occurs, developments will likely happen in what RPA can do for external processes.
- Internal process capabilities will reign supreme
Despite this, RPA will always maintain its core focus on internal processes. Incoming email classification is one example of an area which is set to be massively improved with the help of RPA. In the near future, most computer-aided processes that are governed with a set of protocols will be managed with the help of RPA as well as analytics and data analysis.
- Integration with other tools
It will become increasingly common to see RPA used in conjunction with other workplace tools. As companies increase adoption of RPA into their processes it will become clear it works best when integrated with other tools that they use. This will result in RPA being used more in conjunction with other work management platforms.
- Greater AI capabilities
Artificial Intelligence and RPA are intrinsically linked through their shared history. So, it comes as little surprise that the next phase of RPA is expected to include greater incorporation with AI as RPA moves beyond simply rule-based technology.
- SPA will emerge
Smart Process Automation or SPA is hailed as the next incarnation of RPA. Whereas the RPA deployed in most organisations today struggles to automate data which is unstructured, SPA will combine machine learning, big data, AI and cloud technology to extract data from unstructured sources and process it contextually with a far more intelligent ruleset.
What this means for the world of payroll?
Due to the nature of RPA technology and its functions, it has a number of services which have the potential to greatly improve the payroll process. For example, data entry and data re-keying jobs can be entirely managed with RPA to free up time for payroll employees to complete more complex tasks. Particularly as RPA becomes more integrated with other tools used by companies, it is likely to lead to greater job flexibility and employee satisfaction.
The emergence of Smart Process Automation is also likely to have a big impact on the working lives of payroll staff. The introduction of AI into RPA will enable employees to become digitally empowered as they use this new technology to enhance their work - for instance RPA allows the integration of communication tools, meaning that communication barriers will be eradicated, productivity increased and payroll’s ‘customer experience’ improved.
Specifically, RPA and its various incarnations could drive a properly intelligent query management system for employees, or at a more basic level simplify the process of payroll authorisation - as an example, presenting authorisers with a month-on-month comparison of employee’s pay to help speed up the process.
The continued focus of RPA on internal processes will help to shape payroll workers into becoming the digital workforce of the future, and SPA will help payrollers to identify key insights which can be used to inform and improve internal processes as well as highlighting trend patterns or anomalies easier.
The future looks bright for the world of payroll with RPA on its side. Forrester estimate that the RPA market will reach $2.9 billion by 2021, however its potential goes far beyond the economy and, if integrated successfully, RPA could spark a wider cultural change in which payroll staff have increased flexibility, success and satisfaction.
About the Author
John Welsh, Director, Cleardata
John is a Director of Cleardata and leads their Robocloud division which offers RPA Services to businesses of any size throughout the UK. Robocloud uses cloud-based software robots to perform intelligent process automation for many manual business tasks. This can be used across all areas of businesses to increase productivity and reduce costs, for example Payroll Automation, Accounts Statement Reconciliation, Data Migration, and Automated Customer and Employee Onboarding. For more information visit the Robocloud site.
Great things have been predicted for the future of Robotic Process Automation, with experts claiming that such technology could have a significant influence on the economy. In a recent study conducted by renowned management consultancy McKinsey & Company, Robotic Process Automation (or RPA for short) was hailed as the next big thing, with predictions estimating that automation technologies including RPA could have a financial impact of around $6.7 trillion by 2025. It was also reported that companies which adopt this tech have the potential to see a return on investment between 30 and 200% in the first year alone.
Aside from the dry financial predictions, such technology also has the potential to revolutionise the way we work - particularly for professionals in areas such as payroll. There is much speculation about the future of RPA; however, in order to understand where the technology is today and (crucially) where it will go, it’s helpful to understand the developments which preceded it.
The history
RPA is made up of a number of technologies, brought together under one toolkit to be deployed as and when needed for different automation purposes.
One of the first steps towards the innovation which would eventually lead to the creation of RPA was Machine Learning (ML). It’s widely credited that the name was first coined in 1959 by Arthur Samuel, a pioneer in the field of artificial intelligence who at the time was working for infamous computer company, IBM. Machine learning started as a scientific endeavour aimed at creating artificial intelligence.
Explorations in Machine Learning allowed computers to do a lot of interesting and useful things; enabling programs to be created that conduct complex, language-based tasks such as translation and text summarization. However, there were, and still are, limits in how computers could process language. This naturally led to the development of Natural Language Processing (NLP). This subfield of science, which begun in the 1960s, combined artificial intelligence with the interactions between computers and human languages.
The main focus of NLP was to help computers understand and process human language more accurately. Computers do not have the same understanding of natural language that humans do - for instance, they can’t ‘read between the lines’ of what a person is saying and so, NLP is dedicated to improving this. Aspects of both Machine Learning and Natural Language Processing can be seen in the RPA of today, and as RPA grows it is likely to incorporate even more aspects of these two developments.
Fast forward to the 1990s and as technology progressed further towards the establishment of RPA, there were a few more key developments. Firstly, screen scraping software made big leaps towards the creation of RPA. The technology is used for extracting data from programs, websites and documents, which is something that RPA draws on heavily.
The 90s also saw the emergence of technology which most closely resembles RPA. It was in this decade that workflow automation tools were released and AI emerged in its infancy; all of which paved the way for Robotic Process Automation.
Thanks to these developments, by the early 2000s simple RPA was developed; however, it remained relatively unknown for some time - it wasn’t until 2015 when RPA began to enter the mainstream. The basic RPA versions released in the early noughties were useful for automating repetitive tasks, however it had its limits and so-called cognitive RPA was considered to be inevitable evolution of the tech.
Cognitive RPA allows for better optical character recognition (OCR), natural language processing (NLP) and machine learning to handle semi-structured and unstructured data, expanding the efficiencies of RPA to a wider range of enterprise activities. This is the RPA we know today.
What the experts predict for its future
Just a brief look at the evolution of RPA highlights the innovation of the wider industries from which is was born and it’s clear that this thirst for advancement will likely continue as the technology grows. As a result, experts have predicted a number of effects that this may have on the current technology and its uses.
- Wider adoption of RPA
More businesses are becoming aware of the benefits of RPA and implementing it in their businesses. In 2018, the impact of RPA already became significantly larger and started to move from being used in primarily multinational organisations with large budgets into the realm of national, mid-cap and smaller businesses. As this continues through 2019, the technology will be used by more and more companies to complete a wider range of processes.
- Expansion into more sectors
As RPA becomes more mainstream and more use cases are published, the use of RPA is set to expand into a wider variety of industries including ones which hold significant power including banking, financial services and insurance, manufacturing, retail, law, and Oil and Gas.
- Development in RPA’s external process capabilities
More organisations are continuing to try RPA and witness results from it. As a result, many are being encouraged to experiment with the software’s capabilities; this is making the sector primed for innovations and new applications will naturally soon emerge. As RPA is currently focused on business’ internal processes, it is thought that as innovation occurs, developments will likely happen in what RPA can do for external processes.
- Internal process capabilities will reign supreme
Despite this, RPA will always maintain its core focus on internal processes. Incoming email classification is one example of an area which is set to be massively improved with the help of RPA. In the near future, most computer-aided processes that are governed with a set of protocols will be managed with the help of RPA as well as analytics and data analysis.
- Integration with other tools
It will become increasingly common to see RPA used in conjunction with other workplace tools. As companies increase adoption of RPA into their processes it will become clear it works best when integrated with other tools that they use. This will result in RPA being used more in conjunction with other work management platforms.
- Greater AI capabilities
Artificial Intelligence and RPA are intrinsically linked through their shared history. So, it comes as little surprise that the next phase of RPA is expected to include greater incorporation with AI as RPA moves beyond simply rule-based technology.
- SPA will emerge
Smart Process Automation or SPA is hailed as the next incarnation of RPA. Whereas the RPA deployed in most organisations today struggles to automate data which is unstructured, SPA will combine machine learning, big data, AI and cloud technology to extract data from unstructured sources and process it contextually with a far more intelligent ruleset.
What this means for the world of payroll?
Due to the nature of RPA technology and its functions, it has a number of services which have the potential to greatly improve the payroll process. For example, data entry and data re-keying jobs can be entirely managed with RPA to free up time for payroll employees to complete more complex tasks. Particularly as RPA becomes more integrated with other tools used by companies, it is likely to lead to greater job flexibility and employee satisfaction.
The emergence of Smart Process Automation is also likely to have a big impact on the working lives of payroll staff. The introduction of AI into RPA will enable employees to become digitally empowered as they use this new technology to enhance their work - for instance RPA allows the integration of communication tools, meaning that communication barriers will be eradicated, productivity increased and payroll’s ‘customer experience’ improved.
Specifically, RPA and its various incarnations could drive a properly intelligent query management system for employees, or at a more basic level simplify the process of payroll authorisation - as an example, presenting authorisers with a month-on-month comparison of employee’s pay to help speed up the process.
The continued focus of RPA on internal processes will help to shape payroll workers into becoming the digital workforce of the future, and SPA will help payrollers to identify key insights which can be used to inform and improve internal processes as well as highlighting trend patterns or anomalies easier.
The future looks bright for the world of payroll with RPA on its side. Forrester estimate that the RPA market will reach $2.9 billion by 2021, however its potential goes far beyond the economy and, if integrated successfully, RPA could spark a wider cultural change in which payroll staff have increased flexibility, success and satisfaction.
About the Author
John Welsh, Director, Cleardata
John is a Director of Cleardata and leads their Robocloud division which offers RPA Services to businesses of any size throughout the UK. Robocloud uses cloud-based software robots to perform intelligent process automation for many manual business tasks. This can be used across all areas of businesses to increase productivity and reduce costs, for example Payroll Automation, Accounts Statement Reconciliation, Data Migration, and Automated Customer and Employee Onboarding. For more information visit the Robocloud site.
