Robotic process automation or RPA has the power and capability to help organizations increase their output and accelerate their digital transformation agenda. The true benefit of RPA rests on the technology’s ability to increase efficiency while reducing costs. There is no surprise that RPA is gaining traction in the market by taking away repetitive manual tasks from the human workforce and freeing them to focus on more critical strategic functions.
6 steps to use RPA in an effective way
1. Identify the process
The first thing is to carry out a thorough assessment of all the operations, within and across various departments, so that you can determine which processes can prove to be good candidates for automation.
2. Manage expectations:
Implementation of RPA is all about managing the people and their expectations. Employees must be informed about the need for automation, its essentiality, and how it is likely to influence the return on investment (ROI). The most important areas in which you need to manage expectations are:
- Implementation time
- Implementation cost
- Cost savings
- Benefits of analytics
3. Choose the right tool
Another vital task is to have a crystal-clear set of objectives that your company aims towards. There you can follow two criteria. First, you can consider vendor-related criteria, such as their experience or their orientation to future-proof automation solutions.
Another way, you can try to match the RPA software features, like security and screen scraping capabilities, ease of implementation, the total cost of ownership, etc., to your company’s hierarchy of goals and needs.
4. Assessment of ROI
A fine-grained analysis is required for analysis of the feasibility required before successful RPA implementation. It is important for every organization to compare investment against return, and to decide based on this to what extent it is profitable to invest in RPA.
5. Involve your IT team
The members of your IT team can provide critical insight as you choose an RPA tool that meets your business objectives. Their expertise will also be valuable whenever unexpected issues or malfunctions occur. Training for other employees will be also easy with their support.
6. Measuring the performance
Finally, formulate key performance indicators (KPIs) based on which you can find out the success rate of your RPA implementation.
Inovar blends diligence with skill
Inovar delivers state-of-the-art smart solutions by blending diligence with skills. We adhere to the aforementioned steps and identify what processes/functions need to be automated.
Considering the massive importance and benefits of RPA solutions in reducing efforts, improving customer service, and increasing profits, proper implementation becomes pivotal to ensure that every step is duly scrutinized, vetted, and backed.
With every progressive step of technological advancements, the priorities of CIOs are also changing. Process transformation and automation have gained much of leaders’ attention in recent times. Automation, the use of machines to perform work, most commonly refers to using the use of computer technologies to perform the tasks humans would otherwise do as part of their jobs. The use of computer-based process automation is widespread, with organizations deploying a broad range of software automation tools to help them reach the automation goals they set as part of their larger digital transformation objectives.
According to the December 2020 Global Intelligent Automation (intelligence AI) Study from Deloitte, *73% of organizations worldwide use automation technologies. That’s a significant increase from the *58% of organizations using such technologies in 2019. Gartner reported that organizations’ interest in a process of transformation is accelerating, demand for robotic process automation (RPA) software witnessing the growth of **19.5% from 2020.
But, RPA is not the only process automation technology that companies are leveraging to drive goals, efficiency, and digital transformation. The diversified business sector embraces certain other automation options such as business process automation (BPA) and digital process automation (DPA). Each of the three technologies offers benefits, and each has distinctions that separate it from the others.
What is robotic process automation (RPA)?
RPA technology mimics the way humans interact with software via a UI to perform high-volume, repetitive tasks. The technology creates software programs, or bots, that can log in to applications, enter data, calculate, and complete tasks, and copy data between applications or workflows as required. But RPA doesn’t inherently have intelligence or decision-making capabilities. Hence, the work best suited to RPA is rules-based. These are discrete tasks done the same way over and over, with no deviations that require human decision-making. According to Gartner, RPA represents a major portion of the automation market. Experts believe that the primary benefits of RPA are increased efficiency, lower costs, and reduced errors. RPA bots can perform tasks faster and with consistent accuracy and reliability. They can work round-the-clock without taking breaks.
Another reason for RPA’s growing popularity in the enterprise is its relative ease of use. RPA works with an organization’s existing infrastructure and applications. Also, because many vendors offer low-code/no-code RPA platforms that require little to no programming experience, business users can harness RPA, creating their own bots with minimal help from their IT departments. As such, business users are driving much of the RPA adoption.
What is digital process automation (DPA)?
DPA is a software technology used to automate a process and optimize the workflow within an automated process. A big focus of DPA is to improve employee and customer experiences by taking friction out of the workflow. The software is used to create efficiencies and enhance UX experience in various areas of the enterprise, from IT service requests to onboarding new employees and client intake.
Organizations use DPA to automate a process from its beginning to its end. Typically, DPA is used for the longer and more complex processes than the tasks that can be effectively handled by RPA. These processes can contain multitudes of decisions that, if using RPA, would create bots that are too long and too difficult to maintain.
As per a ***Forrester schema, DPA is divided into two types: DPA-deep, and DPA-wide, which is closely related to RPA:
- DPA-deep is automation that transforms and improves a business process and, because of the complexity, requires skilled technologists to implement and focus on continuous
- business users and can be managed by the business and delivered using low-code platforms and Agile methods.
What is business process automation (BPA)?
BPA automates workflows within an organization; as one step in the business process is completed, the BPA software then automatically triggers the next step. BPA software is used to automate complex, multistep business processes that are usually unique to an organization and are part of the organization’s core business functions.
Size of the business process automation system (BPA) market worldwide from 2016 to 2021
BPA’s holistic approach stems from the technology’s capability to work across the multiple enterprise applications and systems required to complete a typical business process. Organizations often first analyze and improve a business process with a BPA approach before automating it, which is different from the mimic-as-is tactic typically used in RPA.
Reworked, optimized processes using BPA remove human hands from the workflow; with human workers no longer involved in the automated process, they’re not introducing individual workarounds or unauthorized changes to the workflow. Consequently, enterprises use BPA in their digital transformation efforts for the accuracy, efficiency, and reliability it brings to each automated process.
Experts Opinion on – RPA Vs BPA Vs DPA
Some experts use BPA as an umbrella term for a wide range of process automation technologies but there are varied opinions on that concern as well.
According to Gina Schaefer, intelligent automation lead at Deloitte Consulting LLP said- “DPA, BPA, and RPA — are practically interchangeable.”
She further added – “Digital, business process and robotic process automation are essentially the same. When applied appropriately, these refer to comprehensive end-to-end process automation. Specifically, these terms refer to the use of scripted automation software to mimic human actions in the execution of rules-based ‘swivel chair’ type tasks, typically where an individual accesses and processes data from multiple applications.”
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Business process automation now becomes the new norm at the workplace to cope with a fast-paced economy and growing challenges for modern business. While a few organizations may very well consider automating their IT tasks, RPA likewise means to help them rehashing the way they work together, uplifting their consumer loyalty and fortifying employee work values. The necessity of bringing automation has given a boost to Robotic Process Automation (RPA) solutions. But AI (Artificial Intelligence) comes into the center stage as entrepreneurs craving more assistance from robotic process automation. Near future, it would be hard to imagine the RPA solution without AI integration.
According to Forester’s 2019 predictions, the combination of RPA and AI is becoming the new strategic
investment in the corporate world. AI and RPA are emerging automation technologies with enormous potential. The combination helps businesses in achieving tremendous growth in such a competitive market.
You may curious why a business should combine these two technologies?
The reason is simple- RPA has no capability of cognitive awareness, and AI brings it in the customized solution. This combination of AI and RPA adds up to intelligent process automation (IPA). In interest to machine learning algorithms and RPA, IPA also incorporates process management software, natural language processing, creation, and cognitive agents, or “bots.” According to McKinsey, IPA can –
- Add up to20 to 30% improvement in proficiency,
- Reduce the processing time by 50 to 60 percent!
Make an improvement in ROI in triple-digit percentage. TMR (Transparency Market Research) has predicted RPA will be prevalent in the corporate world that its market to reach up to $16 billion by 2024. On the other hand, AI focused on imparting intelligence in the machines and connected devices through speech recognition, decision making, and predictive analysis.
As AI is gaining ground swiftly across the world, it can be integrated with other emerging technologies like IoT and Blockchain to realize the futuristic concepts of smart cities and secure transactions sequentially. McKinsey foresees AI to deliver around $3.5 to $5.8 trillion in value to the world per annum.
How AI enhances RPA services
AI and RPA combination enables modern enterprises to leverage the benefits of both these technologies in accomplishing incomparable tasks with higher efficiency. It is like something beyond the range of a customized RPA solution because it develops to perform the same and repetitive type of work.
At the point of a substantial change is anything but a reasonable alternative for companies, RPA can go about as a facilitator to enable organizations to grow and include value. It also permits them to appear with strategic frameworks around investment they’ve efficiently made into their custom frameworks. The assimilation into AI is the following stage of this granular, more responsive type of change, with more business exercises either completely or partially automated by progressively refined means. It is known as cognitive RPA or CRPA.
RPA alone imitates human action through different AI capabilities, machine vision, speech recognition, and pattern identification capacities and can deal with organized, semi-organized, and unstructured data. However, infused with machine learning gives robots a chance to figure out how to process and enhance tasks that ensure probabilistic conduct.
AI integrated Robotic Process Automation solutions bring the capability of gathering and sharing valuable information with different systems for better decisions. Customized RPA solution can utilize data fetched by AI and performs the complex task with ease. Adding up, AI, commonly with cognitive technologies and ML (Machine Learning), enables robotic process automation by preceding a human response in the workflow.
The humble bot
Organizations aren’t looking for just a bot. They have been looking for a platform with orchestration and integration where, they could readily adopt modern technologies and combine them with intelligence. Now, most organizations are strategizing to automate most of the steps of a business process and then applying a different level of intelligence. Hence, when picking vendors for their bots, the enterprises keep their eye towards that future.
Just like, Germany’s ZF Group, an automotive supplier has started applying intelligence to its business processes just over a year ago and created a bot to answer the most repetitive questions. According to the company’s IT manager around their corporate communication, they have a lot of repetitive work. Furthermore, they receive a lot of emails with repetitive questions coming into their inboxes. Automated integrations and orchestration were their first goal, and they also wanted a platform with built-in checks and balances. Finally, they choose a bot platform that offers a management, governance, and language support layer underneath the bots, called stateful network for AI process (SNAP), which will stop a bot if it demonstrates anomalous behavior.
Real-time Decision support system
Decision points are another way to add intelligent decision points into a traditionally automated business process. Nevertheless, cognitive technologies and machine learning direct out to be even more severe. In general, when AI technologies are integrated with RPA stages will automate the emotional and judgment-based process.
Just like American Fidelity Assurance, an insurance policy provider turned to UiPath, an enterprise RPA vendor, and AI platform Data Robot, to add intelligence to its processes. A system that can manage and execute real-time decisions through AI is the best option for automating complex decision processes. Applying high-level analytics and machine learning those systems to become intelligent and continually adjust and discover from new, contextual data. They set up a real-time decision-making system in form of RPA that helps to transfer highly complex problems in real-time applying AI-based analytical decision-making.
For investment firms, real-time decision-making can analyze thousands of business inputs, constraints, and options and arbitrate between multiple internal targets and trading decisions. It can apply an analytical constraint-based optimization approach to models across thousands of possible actions – whether it be specific content, an offer, a price, a sort order, or a recommendation – and determine the best outcomes for the organization. sometimes it qualifies those choices upon certain criteria from profitability, risk, or revenue perspective.
Sometimes, the traditional approaches to RPA may hit a decision point that is too complex for simple automation. Considering the facts, organizations are also looking at using AI for process mining to automate process discovery rather than have business analysts figure out what happens in the company.
RPA-Robotic Process Automation is transforming the system many organizations function. Process Mining enables companies to holistically experience their methods and recognize process advancement possibilities to boost efficiency and overcome costs. Its 360° view of processes enables hyper-automation—standardizing and accelerating enterprise automation using technologies, such as machine learning (ML) and artificial intelligence (AI).
The conventional way to business process management involves business analysts talking to managers and employees, carrying audits, then creating charts that illustrate the organization’s various business processes.
Sumeet Vij, director of the strategic innovation group at Booz Allen Hamilton, has mentioned how clients are presenting process workflow automation and how things happen, bottlenecks are different. When it comes to process mining, machine learning helps people experience a picture of how things are actually happening. New tools will update the processes and spot anomalous behavior in real-time with the evolvement of business.
Sometimes, a business process may be viewed as charts, such as Visio diagrams, and managers can drill down into the process, down to the level of individual transactions.
Business process analytics
Some organizations have sufficient business process data that they can instantly view the overall picture of what’s happening and make analyses and forecasts. Organizations are taking the exhaust from the RPA process and trying to capture that, learn from it, and make those processes smarter.
Seann Gardiner, senior VP of business development at Data-Robot (an AI platform provider), mentions if a company has a strong focus on process-level automation and can manage that data, then it might be ready. But strong leadership is also mandatory to make the process successful. Business leaders who believe in automation and an AI-first mentality can make the organizational changes needed.
The use-cases of intelligent automation will likewise keep developing as new AI procedures and solutions enter the marketplace, drastically changing the future working environment. It can perform even complex and unique business actions like humans as an advanced solution. However, there is no point in believing that this combination will replace humans as they remain the controller of the RPA +AI combination by building the rules and manage the operation. The combination of RPA and AI had aimed to bring a digital transformation in the companies and adding more value over the period.
For organizations to use this innovation completely, they initially need to see how these solutions can change their procedures and apply strict governance to settle on beyond any doubt their decision-making is paramount. If organizations attempt to actualize these connected yet granular solutions over their companies, it will enable them to drive a double speed change and pursue new heights in Business and IT maturity level.