Robotic Process Automation
Robotic Process Automation
What is robotic process automation?
Robotic process automation (RPA), also known as software robotics, uses automation technologies to mimic back-office tasks of human workers, such as extracting data, filling in forms, moving files, et cetera. It combines APIs and user interface (UI) interactions to integrate and perform repetitive tasks between enterprise and productivity applications. By deploying scripts which emulate human processes, RPA tools complete autonomous execution of various activities and transactions across unrelated software systems.
This form of automation uses rule-based software to perform business process activities at a high-volume, freeing up human resources to prioritize more complex tasks. RPA enables CIOs and other decision makers to accelerate their digital transformation efforts and generate a higher return on investment (ROI) from their employee, allowing its digital workforce via RPA to shoulder more tedious and time-consuming tasks.
However, prior to adopting RPA technologies, organizations should evaluate their readiness to adopt by examining their data management processes and data architecture. RPA is dependent on high-quality data and strong data governance to be successful, and if the right guardrails (e.g. center of excellence, governance boards, documented guidelines) are not in place, it will not be able to meet the expectations of the business.
RPA and intelligent automation
In order for RPA tools in the marketplace to remain competitive, they will need to move beyond task automation and expand their offerings to include intelligent automation (IA). This type of automation expands on RPA functionality by incorporating sub-disciplines of artificial intelligence, like machine learning, natural language processing, and computer vision.
Intelligent process automation demands more than the simple rule-based systems of RPA. You can think of RPA as “doing” tasks, while AI and ML encompass more of the “thinking” and "learning," respectively. It trains algorithms using data so that the software can perform tasks in a quicker, more efficient way. As artificial intelligence becomes more commonplace within RPA tools, it will become increasingly difficult to differentiate between these two categories.
RPA and artificial intelligence
Robotic process automation is often mistaken for artificial intelligence (AI), but the two are distinctly different. AI combines cognitive automation, machine learning (ML), natural language processing (NLP), reasoning, hypothesis generation and analysis.
The critical difference is that RPA is process-driven, whereas AI is data-driven. RPA bots can only follow the processes defined by an end user, while AI bots use machine learning to recognize patterns in data, in particular unstructured data, and learn over time. Put differently, AI is intended to simulate human intelligence, while RPA is solely for replicating human-directed tasks. While the use of artificial intelligence and RPA tools minimize the need for human intervention, the way in which they automate processes is different.
That said, RPA and AI also complement each other well. AI can help RPA automate tasks more fully and handle more complex use cases. RPA also enables AI insights to be actioned on more quickly instead of waiting on manual implementations.
RPA and hyperautomation
Hyperautomation is the concept of automating everything in an organization that can be automated. Organizations that adopt hyperautomation aim to streamline processes, and they leverage technologies such, as artificial intelligence (AI) and robotic process automation (RPA), to operate certain workflows without human intervention.
How does RPA work?
According to Forrester, RPA software tools must include the following core capabilities:
- Low-code capabilities to build automation scripts
- Integration with enterprise applications
- Orchestration and administration including configuration, monitoring and security
Automation technology, like RPA, can also access information through legacy systems, integrating well with other applications through front-end integrations. This allows the automation platform to behave similarly to a human worker, performing routine tasks, such as logging in and copying and pasting from one system to another. While back-end connections to databases and enterprise web services also assist in automation, RPA’s real value is in its quick and simple front-end integrations.
The benefits of RPA
There are multiple benefits of RPA, including:
- Less coding: RPA does not necessarily require a developer to configure; drag-and-drop features in user interfaces make it easier to onboard non-technical staff.
- Rapid cost savings: Since RPA reduces the workload of teams, staff can be reallocated towards other priority work that does require human input, leading to increases in productivity and ROI.
- Higher customer satisfaction: Since bots and chatbots can work around the clock, they can reduce wait times for customers, leading to higher rates of customer satisfaction.
- Improved employee morale: By lifting repetitive, high-volume workload off your team, RPA allows people to focus on more thoughtful and strategic decision-making. This shift in work has a positive effect on employee happiness.
- Better accuracy and compliance: Since you can program RPA robots to follow specific workflows and rules, you can reduce human error, particularly around work which requires accuracy and compliance, like regulatory standards. RPA can also provide an audit trail, making it easy to monitor progress and resolve issues more quickly.
- Existing systems remain in place: Robotic process automation software does not cause any disruption to underlying systems because bots work on the presentation layer of existing applications. So, you can implement bots in situations where you don’t have an application programming interface (API) or the resources to develop deep integrations.
To learn more about what’s required of business users to set up RPA tools, read on in our blog here.
Challenges of RPA
While RPA software can help an enterprise grow, there are some obstacles, such as organizational culture, technical issues and scaling.
While RPA will reduce the need for certain job roles, it will also drive growth in new roles to tackle more complex tasks, enabling employees to focus on higher-level strategy and creative problem-solving. Organizations will need to promote a culture of learning and innovation as responsibilities within job roles shift. The adaptability of a workforce will be important for successful outcomes in automation and digital transformation projects. By educating your staff and investing in training programs, you can prepare teams for ongoing shifts in priorities.
Difficulty in scaling
While RPA can perform multiple simultaneous operations, it can prove difficult to scale in an enterprise due to regulatory updates or internal changes. According to a Forrester report, 52% of customers claim they struggle with scaling their RPA program. A company must have 100 or more active working robots to qualify as an advanced program, but few RPA initiatives progress beyond the first 10 bots.
RPA use cases
There are several industries that leverage RPA technology to streamline their business operations. RPA implementations can be found across the following industries:
Banking and financial services: In the Forrester report “The RPA Services Market Will Grow To Reach USD 12 Billion By 2023,” 36% of all use cases were in the finance and accounting space. More than one in three bots today are in the financial industry, which is of little surprise given banking's early adoption of automation. Today, many major banks use RPA automation solutions to automate tasks, such as customer research, account opening, inquiry processing, and anti-money laundering. A bank deploys thousands of bots to automate manual high-volume data entry. These processes entail a plethora of tedious, rule-based tasks that automation streamlines.
Supply chain: RPA has also been impactful within supply chain operations. By integrating information across shippers and operation managers, companies can better communicate to their customers when unscheduled events occur, like delivery changes or delays. By communicating ahead of time, businesses can improve overall customer satisfaction. Delve deeper into our Inter Aduaneira case study, where they used RPA to improve their response times by 80%.
Telecom: Telecom is another one of the industries using the most RPA as it experiences massive growth driven by the Internet of Things, 5G, and edge computing. As demand soars, RPA can help a telecom company streamline its apps and infrastructure and help them share data. Combined with AI processing, RPA can analyze network usage data to keep the user experience consistent and collect compliance data to keep up with regulatory Federal Communications Commission (FCC) mandates. RPA can also help providers automate customer recordkeeping, improve customer experiences, keep services affordable and uninterrupted, and monetize new 5G services.
Insurance: The insurance industry is full of repetitive processes well-suited for automation. For example, you can apply RPA to claims processing operations, regulatory compliance, and policy management. RPA can help generate faster quotes and policy documents at the “quote and bind” stage and the underwriting process. It can help standardize midterm adjustments by bringing data into a single source of truth and processing policy changes quicker. Agents work more efficiently with RPA tools, meaning the volume and length of customer calls are reduced, and customers are more satisfied. It also means being able to streamline renewal tasks, such as pricing and policy documentation, freeing employees to spend more time on customer retention.
Retail: The rise of e-commerce has made RPA an integral component of the modern retail industry by automating tasks that impact both customers and employees, such as collecting employee information for onboarding, scheduling, and payroll. RPA helps with managing inventory, warehouse and order management, supply chain operations, fraud detection, customer feedback processing, and returns processing. It can aggregate information from cash register reports. Retailers use RPA to automate pricing, analyze factors that impact sales such as geographic location, cultural and age preferences, aggregate information from registers, and send automated messages to suppliers and customers. Automating repetitive tasks not only improves customer support and the customer experience, but also frees employees to focus on more value-added and impactful actions.
Healthcare: Accuracy and compliance are paramount in the healthcare industry. Some of the world's largest hospitals use robotic process automation software to optimize information management, prescription management, insurance claim processing, and payment cycles, among other processes. Throughout the healthcare industry, RPA addresses process challenges such as billing and compliance, electronic health records, clinical documentation, patient scheduling, and more, helping organizations become more efficient and effective and improving the employee and customer experience.
Robotic Process Automation and IBM
Automating processes is just one important step forward as the need for automation widens across business and IT operations. A move toward greater automation should start with small, measurably successful projects, which you can then scale and optimize for other processes and in other parts of your organization.
Working with IBM, you’ll have access to AI-powered automation capabilities, including prebuilt workflows, to help accelerate innovation by making every process more intelligent.
Take the next step:
- Start your automation journey with IBM® Robotic Process Automation. It’s an AI-driven RPA solution that helps you automate more business and IT processes at scale with the ease and speed of traditional RPA.
- Watch this product overview demo (04:03) to see how you can use IBM Robotic Process Automation to build an unattended bot to handle common use cases, such as updating customer information.
- Try IBM Robotic Process Automation for no cost for 30 days to learn how to build and run software bots or virtual agents to automate processes.
- IBM Robotic Process Automation can also come integrated with automation capabilities such as content, capture, workflow and decisions as part of IBM Cloud Pak for Business Automation, a flexible set of integrated software that helps you design, build and run intelligent automation services and applications on any cloud, using low-code tools at scale.
- Read Robotic Process Automation: A "no-hype" buyer's guide to learn what RPA is, its pros and cons, and how to get started.
- Explore the six reasons to try a robotic process automation tool.
- Read about the five “must-have’s” for automation success (link resides outside IBM) in this HFS Research report.
Get started with an IBM Cloud account today.