Robotic Process Automation
Robotic Process Automation (RPA) is an emerging business process automation technology based on the concept of software robots or Artificial Intelligence (AI). Robotic process automation is a technology that allows anyone to configure computer software, or "robots," to simulate and integrate human interactions in digital systems to execute business processes. RPA bots utilize user interfaces like humans to capture data and operate applications. They interpret, trigger responses, and communicate with other systems to perform a wide variety of repetitive tasks. In essence: an RPA software bot that never sleeps, makes zero mistakes, and costs far less than an employee.
Source: wiki
Introduction
Robotic Process Automation (RPA) is an emerging business process automation technology based on the concept of software robots or Artificial Intelligence (AI).
Robotic process automation is a technology that allows anyone to configure computer software, or "robots," to simulate and integrate human interactions in digital systems to execute business processes. RPA bots utilize user interfaces like humans to capture data and operate applications. They interpret, trigger responses, and communicate with other systems to perform a wide variety of repetitive tasks. In essence: an RPA software bot that never sleeps, makes zero mistakes, and costs far less than an employee.
Consider the case of a company below:
- The business environment is constantly changing. Businesses need to continually evolve their product, sales, marketing and other processes to grow and stay relevant
- A typical business uses multiple disconnected IT systems to run its operations. As business processes change, these IT systems do not change frequently due to budget, time and implementation complexity issues. Therefore, business processes do not map technical processes that are mapped in IT systems.
- To overcome this technical and organizational debt, people are hired to fill the gaps between systems and processes. One company changed its sales process to require a 50% upfront payment to confirm pre-orders for its products. But this is not yet coded in the IT system. Humans have to manually check invoices and payment details, and only process sales orders if 50% is prepaid.
Through robotic automation, the company can deploy virtual workers that mimic humans. In the event of a process change, changing a few lines of software code is always faster and cheaper than retraining hundreds of employees.
Here are some reasons for the advantages of robotic process automation:
- A person can work an average of 8 hours a day, while a robot can work 24 hours a day without fatigue.
- The average productivity of humans is 60% with small errors, while the productivity of robots is 100% without any errors.
- Robots are good at multitasking compared to humans
Approaches to RPA Applications
Planning
At this stage, you need to identify the processes you want to automate. The checklist below will help you determine the correct process
- Are process manuals duplicated?
- Is the process based on rules?
- Is the input data in electronic format and readable?
- Can the current system be used as usual?
- Establish project team, determine implementation timeline and method.
- Agree on a solution design for executing the RPA process.
- Determine which logging mechanism should be implemented to find problems with running bots.
- A clear roadmap should be defined to scale the implementation of RPA
Develop
Test
Support and Maintenance
Applications of RPA
- Patient registration
- Billing
- New employee joining formalities
- Payroll process Payroll processing
- Hiring shortlisted candidates
- Claims Processing & Clearance
- Premium Information Premium Information
- Bills of Material
- Calculation of Sales
- Service Order Management Service Order Management
- Quality Reporting
- Ticket booking
- Passenger Details
- Accounting
- Cards activation
- Frauds claims
- Discovery
- Change of Address
- License Renewal License renewal
- Issues Processing
- Account setup and communication renewal address
In traditional workflow automation tools, software developers use internal application programming interfaces (APIs) or specialized scripting languages to generate a list of actions to automate tasks and interface with back-end systems. Instead, RPA systems develop action lists by watching users perform that task in the application's graphical user interface (GUI), and then perform automation by repeating those tasks directly in the GUI. This can lower the barriers to using automation in products that might not otherwise provide APIs for this purpose.
RPA tools share strong technical similarities with GUI testing tools. These tools can also automate interactions with the GUI, often by repeating a set of demonstration actions performed by the user. RPA tools differ from such systems by including functionality that allows data to be processed in and between multiple applications, for example, receiving emails containing invoices, extracting the data, and then entering it into a billing system.
Historical Evolution
Deploy
The hosting of RPA services also aligns with the software robot metaphor, with each robot instance having its own virtual workstation, much like a human worker. Robots use keyboard and mouse controls to take actions and perform automation. Typically, all of these actions take place in a virtual environment, not on a screen; the robot does not need a physical screen to operate, but instead interprets the screen display electronically. The scalability of modern solutions based on these architectures is largely due to the advent of virtualization technologies, without which the scalability of large deployments would be limited by the available capabilities and associated costs of managing physical hardware. Implementing RPA in commercial enterprises has shown significant cost savings compared to traditional non-RPA solutions.
However, RPA has several risks. Criticisms include stifling innovation and the risk of creating a more complex maintenance environment for existing software that now needs to think about how GUIs are used rather than how they were originally used.
[Source: https://en.wikipedia.org/wiki/Robotic_process_automation]
Case:
For now, Creators are only taking reservations for 30 minutes for Wednesday and Thursday lunchtime in July, and plan to do the same in August, during which they fix machine bugs and improve software and workflow.
Development History
Describe
In the 1990s, the concept of enterprise resource planning and shared services drove the emergence and development of centralized finance and accounting, human resources, procurement, and other business functions. The next wave of cost savings is gathering pace, focusing on replacing people with technology in delivering services.
In the 2000s, manual labor was added to perform activities between business systems. Although using software to automate work is not a new idea. In the 2010s, machine process automation gradually entered people's field of vision. This vocabulary, which has evolved due to business needs, does not have a long history in the field of research. Most of the related studies are from the 2010s, and it can be found that this proper noun is still a relatively new vocabulary. The more classic papers are "Robotic process automation at Telefonica O2." "The IT function and robotic process automation."
In 2015, Professor Leslie Willcocks published "The IT Function and Robotic Process Automation", which introduced the combination of IT industry and RPA in detail, and stated the various challenges and future development directions of their combination.
In 2016, Aleksandre Asatiani published "Turning robotic process automation into commercial success – Case OpusCapita" in JITTC to explain machine process automation with the case of OpusCapita. He stated that machine automation has huge market potential and is needed.
In 2017, Leslie Willcocks of The London School of Economics and Political Science published "Robotic process automation: strategic transformation lever for global business services?" based on xchanging to introduce the process of RPA to help readers understand.
In addition to these developments, RPA is also accompanied by some noise. Although it brings huge benefits to enterprises, it also threatens the employment of normal employees.
In 2015, Harvard Business Review reported that most operating groups that had adopted RPA had promised employees that automation would not lead to layoffs. Instead, workers were redeployed to more interesting jobs. An academic study highlights that knowledge workers do not feel threatened by automation: they embrace it and see robots as teammates. The same study, Robotic Process Automation at Xchanging, also highlights that the way to adopt automation technology is not to reduce "people", but to do more work and increase productivity with the same number of people.
Instead, some analysts have suggested that RPA poses a threat to the business process outsourcing (BPO) industry. The thesis behind the concept "Gartner Predicts 2014: Business and IT Services Are Facing the End of Outsourcing as We Know It," is that RPA will enable businesses to take advantage of this new technology to "repatriate" processes from offshore locations to on-premises data center. If true, the effect would be to create high-value jobs for skilled process designers at onshore locations (and within the supply chain of associated IT hardware, data center management, etc.), but reduce the available opportunities for low-skilled offshore workers. On the other hand, this discussion seems to be the basis for a healthy debate, as another academic study strives to disprove the so-called "myth" that the Rwandan Patriotic Army will bring back many jobs overseas.
The academic study "THE FUTURE OF EMPLOYMENT: HOW SUSCEPTIBLE ARE JOBS TO COMPUTERISATION?," "Nine likely scenarios arising from the growing use of software robots" predicts that, among other technology trends, the Regional Action Plan is expected to drive global labor markets A new round of productivity and efficiency gains. Oxford University speculates that up to 35% of jobs may have been automated by 2035, but it's not just RPA that is to blame.
In a TEDX talk hosted by UCL in London, entrepreneur David Moss explained that digital labor in the form of RPA has the potential to revolutionize the cost model of the service industry not only by driving down the price of products and services, but also to improve service levels and product quality, providing Personalization of services creates more opportunities.
Meanwhile, professor Willcocks, author of the London School of Economics paper, talks about the increased job satisfaction and intellectual stimulation, arguing that the technology could "liberate robots from humans", "Technology is not about to steal your job," . The idea is that robots will take over mundane and repetitive parts of people’s daily work, allowing them to be reassigned to more interpersonal roles or to focus on the remaining, more meaningful parts.
[Source: https://en.wikipedia.org/wiki/Robotic_process_automation ]
| Years | Event | Related papers/Reference |
| 2015 | Lacity, M. et al explain RPA in the context of Telefonica O2 | Lacity, M., Willcocks, L. P., & Craig, A. (2015). Robotic process automation at Telefonica O2. |
| 2015 | Leslie Willcocks detailed the combination of IT industry and RPA | Willcocks, L. P., Lacity, M., & Craig, A. (2015). The IT function and robotic process automation. |
| 2016 | Aleksandre Asatian explains machine process automation with the case of OpusCapita | Asatiani, A., & Penttinen, E. (2016). Turning robotic process automation into commercial success–Case OpusCapita. Journal of Information Technology Teaching Cases, 6(2), 67-74. |
| 2017 | Leslie Willcocks introduced the process of RPA based on xchanging to help readers understand. | Willcocks, L., Lacity, M., & Craig, A. (2017). Robotic process automation: strategic transformation lever for global business services?. Journal of Information Technology Teaching Cases, 7(1), 17-28. |
Development Analysis
Bottleneck
Challenge 1: Misleading RPA Glossary
The words "robot", "robot software", "developer", "designer" and "analyst" have different meanings to different people. The "robots" of RPA are not physical robots. The first point of departure is that the customer is not dealing with a physical robot. But it is a software robot, not ordinary software. "They call it a robot because it tries to have all the characteristics of a virtual human," said Jason Kingdon, chairman of Blue Prism. However, it is an infinitely scalable human that can be instructed very quickly to act as a machine speed to perform the operation.
Challenge 2: Better, Faster, Less
Today's IT functions are expected to form a square (or triangle) in resources, time and quality. Traditionally, these three project components have been viewed as tradeoffs. If you want to do it quickly, it will cost more and/or the quality will suffer. If you want to reduce cost and consumption of resources, the quality will drop and the time will increase. In today's enterprise, however, senior business executives expect IT to deliver faster, better quality, and at lower cost, while being judged primarily on business rather than IT metrics.
Challenge 3: Lightweight vs Heavyweight IT
Shadow IT is proliferating as mobile, cloud services, social media, endless new applications and more attract purchases and deployments outside of enterprise IT. Software as a Service (SaaS) is a good example. An initial cost-benefit analysis of SaaS may make shadow arrangements immediately attractive, but losing control over architecture, security, applications, and deployments can have far-reaching and disruptive consequences.
Challenge 4: Business and Operations and IT Projects
For the past 15 years, business executives and many CIOs have been reciting the mantra: "There are no more IT projects, only business projects supported by IT." Our own study of 26 cases of IT-supported innovation shows that more accurately In other words, they mean that most projects with business needs - and all IT-enabled business process innovations - need to be business/user-led, not IT-led.
【 http://eprints.lse.ac.uk/64519/1/OUWRPS_15_05_published.pdf】
Future Direction
At present, the identification of working conditions, operation control and decision-making in ERP and MES in the whole process of complex manufacturing still rely on knowledge workers. Knowledge workers rely on data, text, images and other information and experience for working condition identification, operation control and decision-making. However, big data-driven artificial intelligence technology has made revolutionary progress. Automation science and technology is essentially an artificial intelligence technology driven by mathematical models. The combination of big data-driven artificial intelligence technology and automation science and technology will inevitably produce artificial intelligence-driven automation. Big data, mobile internet, and cloud computing have opened up new avenues for AI-driven automation. AI-driven automation is bound to play a more important role in smart manufacturing.
Automation technology not only plays an irreplaceable role in the navigation, guidance and control of aviation, aerospace, rail transit, automobiles and marine vehicles, robot control and trajectory planning, but also begins to be used in transportation systems, energy systems, water Security monitoring and management of key infrastructure systems such as resource systems, biological systems, medical systems, and communication systems. Like enterprise management systems, the above systems are essentially information-physical systems involving human participation. To make these critical infrastructure systems operate in a safe, reliable, efficient and green way, it is necessary to carry out research on the theory and technology of modeling, simulation, prediction and control and optimization of such systems. This will certainly promote the development of automation science and technology.
The development of information technology has promoted the development of cyber-physical systems involving smart factories, smart grids, smart transportation, and smart cities, as well as quantum communication, micro-nano manufacturing, and biological systems. Achieving detection, control, management, and optimization decisions in the aforementioned emerging fields poses challenges to existing modeling, control, and optimization theories and techniques. Therefore, the future development of automation science and technology should be taken as the development direction, and the following research should be carried out:
- AI-driven automation;
- A new generation of networked and intelligent management and control systems;
- Automated science and technology in cyber-physical systems with human participation;
- Automation science and technology in emerging application fields (quantum communication, micro-nano manufacturing and biological systems).
In order to realize the vision function of the automation system required by the vehicle in the future, it is necessary to develop the vehicle automation system into three major systems:
- Intelligent autonomous control system;
- Multi-agent collaborative control system;
- Navigation and guidance integrated control system.