View source for Robotic Process Automation (RPA)

'''Robotic Process Automation (RPA)''' occurs when basic tasks are automated through software or hardware systems that function across a variety of applications, just as human workers do. The software or robot can be taught a workflow with multiple steps and applications, such as taking received forms, sending a receipt message, checking the form for completeness, filing the form in a folder, and updating a spreadsheet with the name of the form, the date filed, and so on. RPA software is designed to reduce the burden for employees of completing repetitive, simple tasks.<ref>[https://www.investopedia.com/terms/r/robotic-process-automation-rpa.asp What is Editing Robotic Process Automation (RPA)?]</ref>


[[File:Robotic Process Automation.png|400px|Robotic Process Automation]]<br />
source: Tibco


== Defining Robotic Process Automation<ref>[https://enterprisersproject.com/article/2019/5/rpa-robotic-process-automation-how-explain 5 ways to define RPA in plain English]</ref> ==
*“In layman’s terms, RPA is the process by which a software bot uses a combination of automation, computer vision, and machine learning to automate repetitive, high-volume tasks that are rule-based and trigger-driven.” –David Landreman,, CPO of Olive.
*“Robotic process automation is nothing but instructing a machine to execute mundane, repetitive manual tasks. If there is a logical step to performing a task, a bot will be able to replicate it.” –Vishnu KC, senior software analyst lead at ClaySys Technologies.
*“RPA is software that automates rules-based actions performed on a computer.” –Chris Huff, chief strategy officer at Kofax.
*“RPA is an advanced form of business process automation that is able to record tasks performed by a human on their computer, then perform those same tasks without human intervention. Essentially, it is a virtual robot copycat.” –Marcel Shaw, federal systems engineer at Ivanti.
*“Put simply, the role of RPA is to automate repetitive tasks that were previously handled by humans. The software is programmed to do repetitive tasks across applications and systems. The software is taught a workflow with multiple steps and applications.”–Antony Edwards, COO at Eggplant.


== Historic Evolution of RPA<ref>[https://en.wikipedia.org/wiki/Robotic_process_automation Historic Evolution of RPA]</ref> ==
The typical benefits of robotic automation include reduced cost; increased speed, accuracy, and consistency; improved quality and scalability of production. Automation can also provide extra security, especially for sensitive data and financial services.

As a form of automation, the concept has been around for a long time in the form of screen scraping, which can be traced back to early forms of malware. However, RPA is much more extensible, consisting of API integration into other enterprise applications, connectors into ITSM systems, terminal services and even some types of AI (e.g. Machine Learning) services such as image recognition. It is considered to be a significant technological evolution in the sense that new software platforms are emerging which are sufficiently mature, resilient, scalable and reliable to make this approach viable for use in large enterprises (who would otherwise be reluctant due to perceived risks to quality and reputation).

A principal barrier to the adoption of self-service is often technological: it may not always be feasible or economically viable to retro-fit new interfaces onto existing systems. Moreover, organizations may wish to layer a variable and configurable set of process rules on top of the system interfaces which may vary according to market offerings and the type of customer. This only adds to the cost and complexity of the technological implementation. Robotic automation software provides a pragmatic means of deploying new services in this situation, where the robots simply mimic the behavior of humans to perform the back end transcription or processing. The relative affordability of this approach arises from the fact that no IT new transformation or investment is required; instead the software robots simply leverage greater use out of existing IT assets.


== Effective Robotic Process Automation<ref>[https://www.cio.com/article/3236451/what-is-rpa-robotic-process-automation-explained.html 10 tips for effective robotic process automation]</ref> ==
*Set and manage expectations: Quick wins are possible with RPA, but propelling RPA to run at scale is a different animal. Dave Kuder, a principal with Deloitte Consulting LLP, says that many RPA hiccups stem from poor expectations management. Bold claims about RPA from vendors and implementation consultants haven't helped. That's why it's crucial for CIOs to go in with a cautiously optimistic mindset. "If you go in with open eyes you'll be a lot happier with the result," Kuder says.
*Consider business impact: RPA is often propped up as a mechanism to bolster return on investment or reduce costs. But Kris Fitzgerald, CTO of NTT Data Services, says more CIOs should use it to improve customer experience. For example, enterprises such as airlines employ thousands of customer service agents, yet customers are still waiting in the queue to have their call fielded. A chatbot, could help alleviate some of that wait. “You put that virtual agent in there and there is no downtime, no out sick and no bad attitude,” Fitzgerald says. “The client experience is the flag to hit.”
*Involve IT early and often: COOs initially bought RPA and hit a wall during implementation, prompting them to ask IT’s help (and forgiveness), Viadro says. Now "citizen developers" without technical expertise are using cloud software to implement RPA right in their business units, Kuder says. Often, the CIO tends to step in and block them. Kuder and Viadro say that business heads must involve IT from the outset to ensure they get the resources they require.
*Poor design, change management can wreak havoc: Many implementations fail because design and change are poorly managed, says Sanjay Srivastava, chief digital officer of Genpact. In the rush to get something deployed, some companies overlook communication exchanges, between the various bots, which can break a business process. "Before you implement, you must think about the operating model design," Srivastava says. "You need to map out how you expect the various bots to work together." Alternatively, some CIOs will neglect to negotiate the changes new operations will have on an organization's business processes. CIOs must plan for this well in advance to avoid business disruption.
* fall down the data rabbit hole: A bank deploying thousands of bots to automate manual data entry or to monitor software operations generates a ton of data. This can lure CIOs and their business peers into an unfortunate scenario where they are looking to leverage the data. Srivastava says it's not uncommon for companies to run ML on the data their bots generate, then throw a chatbot on the front to enable users to more easily query the data. Suddenly, the RPA project has become an ML project that hasn't been properly scoped as an ML project. "The puck keeps moving," and CIOs struggle to catch up to it, Srivastava says. He recommends CIOs consider RPA as a long-term arc, rather than as piecemeal projects that evolve into something unwieldy.
*Project governance is paramount: Another problem that pops up in RPA is the failure to plan for certain roadblocks, Srivastava says. An employee at a Genpact client changed the company’s password policy but no one programmed the bots to adjust, resulting in lost data. CIOs must constantly check for chokepoints where their RPA solution can bog down, or at least, install a monitoring and alert system to watch for hiccups impacting performance. "You can't just set them free and let them run around; you need command and control," Srivastava says.
*Control maintains compliance: There are lot of governance challenges related to instantiating a single bot in environment let alone thousands. One Deloitte client spent several meetings trying to determine whether their bot was male or female, a valid gender question but one that must take into account human resources, ethics and other areas of compliance for the business, Kuder says.
*Build an RPA center of excellence: The most successful RPA implementations include a center of excellence staffed by people who are responsible for making efficiency programs a success within the organization, Viadro says. Not every enterprise, however, has the budget for this. The RPA center of excellence develops business cases, calculating potential cost optimization and ROI, and measures progress against those goals. "That group is typically fairly small and nimble and it scales with the technology staff that are focused on the actual implementation of automation,” Viadro says. “I’d encourage all IT leaders across different industries to look for opportunities and understand whether [RPA] will be transformative for their businesses.”
*Don’t forget the impact on people: Wooed by shiny new solutions, some organizations are so focused on implementation that they neglect to loop in HR, which can create some nightmare scenarios for employees who find their daily processes and workflows disrupted. “We forget that it’s people first,” Fitzgerald says.
*Put RPA into your whole development lifecycle: CIOs must automate the entire development lifecycle or they may kill their bots during a big launch. “It sounds easy to remember but people don’t make it a part of their process.” Ultimately, there is no magic bullet for implementing RPA, but Srivastava says that it requires an intelligent automation ethos that must be part of the long-term journey for enterprises. "Automation needs to get to an answer — all of the ifs, thens and whats — to complete business processes faster, with better quality and at scale," Srivastava says.


== Benefits and Challenges of Robotic Process Automation<ref>[https://www.uipath.com/blog/the-benefits-and-challenges-of-rpa-implementation What are the Benefits and Challenges of Robotic Process Automation?]</ref> ==

''Benefits''<br />
*Increased compliance: RPA removes data gaps between disparate sources and logs all actions completed by the the software robots throughout automation. This allows employees to proactively recognize and manage any compliance issues and consistently run internal reviews. These features of RPA support companies across various industries, whether that be the insurance provider obligated to meet certain regulations, a healthcare company required to meet HIPAA privacy rules, or a financial service firm needing to be PCI compliant.
*Non-invasive nature and compatibility with existing systems: Because RPA mimics human actions, the technology interacts with data within the presentation layer of platforms and applications. This means RPA acts at the user interface just like a human would. As a result, this means companies do not need to make changes to existing legacy systems when implementing RPA. This is beneficial because it allows organizations to implement RPA in a non-interruptive way, which makes RPA unique among other types of automation. It also reduces the need for constant IT involvement and for employees to have coding abilities.
*Better management capabilities: A centralized management platform provides organizations with the ability to remotely model, monitor, control, schedule, and execute the deployment of RPA software robots. It also allows auditing and analytics to happen in the same place. Because certain requirements can be embedded in automation rules, RPA allows organizations to achieve enhanced governance in order to better manage business operations. In addition, high levels of security can be maintained through remote server control of the software robots.
*Improved customer experience: RPA is generally seen as a way for companies to alleviate employees from the burden of repetitive, high-volume tasks such as purchase order issuing and claims processing. Even though the automation of back office tasks seemingly does not have an impact on the front office, RPA can drive improvements for customers as well. Through its automation capabilities, RPA allows organizations to deliver higher quality services to their customers in a timely manner.

 

''Challenges
*Employee resistance and onboarding: Any changes that accompany implementation of a new technology can be stressful for employees as they might experience shifts in their responsibilities. Frequent communication from company leaders and executive sponsors to ensure employees are fully informed about what is expected of them throughout the implementation process is essential to successful adoption. Fostering a culture of innovation within the company will only further accelerate this adoption.  
*Choosing the right processes: The automation capabilities provided by RPA are ideal for tasks that are repetitive, rules-based, high volume, and do not require human judgement. This can include activities such as data migration and copy-paste tasks. RPA implementation is especially difficult though with business processes that are non-standardized and require frequent human intervention in order to execute. Typically, these more complex tasks include interacting with customers and developing human relationships. While it is an upfront time investment, it’s important for companies to determine which of their processes are suitable for RPA so that automation runs smoothly.
*Setting realistic expectations: This is arguably one of the biggest obstacles when it comes to implementing a new technology such as RPA. Instead of seeing RPA as the panacea for operational problems and broken processes, organizations need to recognize the limits of what RPA can and cannot do. Decisions regarding the technology need to be made on an individualized and company-specific basis, as RPA’s functionality, implementation timeline, and operational results will vary between different companies. Maintaining company-wide discussions about expected results will allow organizations to make the most of RPA and its benefits.


== See Also ==
[[Automation]]<br />
[[Artificial Intelligence (AI)]]<br />
[[Machine Learning]]<br />
[[Machine-to-Machine (M2M)]]<br />
[[Process]]<br />
[[Business Process]]<br />
[[Business Process Automation]]<br />
[[Business Process Improvement (BPI)]]<br />
[[Business Process Management (BPM)]]<br />
[[Cognitive Computing]]<br />


== References ==
<references/>
__NOTOC__