Automation is not new. Automation is a technology that dates back for decades as it has evolved over many years. For example, the term "robot" was first used by a Czech writer named Karel Kapek in 1921. Since then, there have been many instances where new and innovative solutions were introduced to ease tasks performed by humans — technologies such as autonomous vehicles, AI systems, chatbots, drones, and many more.

This evolution took place mainly around physical robots. However, technologies such as artificial intelligence (AI), machine learning (ML), and Natural Language Processing (NLP) have led the way to software robots that reduce the manual, time-consuming, and repetitive actions performed on digital platforms. The concept of automating tasks on digital platforms is called robotic process automation (RPA). RPA is a software robot that interacts with computer-centric processes and aims to introduce a digital workforce that performs repetitive tasks previously completed by humans.

Software solutions are designed to ease the many tasks that we do. But software solutions still evolve around human input all the time. Have we ever thought about introducing a digital assistant to interact with the same application we created without human involvement? A digital assistant who works in our own computer, working in the background to perform the same tasks we do? We can easily build digital assistants who perform our daily actions — without the need for highly technical knowledge. Not only for enterprises, but we can also use the same technology in our personal life too.

Today, RPA is gaining more and more attention as it revolutionizes the way we work. Many organizations are investing in automating high-volume, repetitive, mundane activities to save many human hours for more value-added activities.

What Makes RPA so Powerful

RPA is not just one technology. RPA robots can use AI, ML, computer vision, NLP, data analytics, and deep learning to expand their capabilities beyond the stretch of our imagination. The combined force offers many benefits for organizations, such as:

• Working 24/7 with high accuracy rates
• Ability to scale and implement quickly using existing infrastructure
• Ability to mimic human actions on any digital platform without any change to existing applications
• Rapid Return on Investment (ROI)
• Improved service delivery and customer satisfaction
• Improved process efficiency
• Better tracking on the performance of the robots through quick and easy dashboards

Current Trends in RPA

These proven results and use cases attract many organizations to start their RPA journey. According to Gartner, the global RPA software revenue is projected to reach $1.89 billion in 2021, increasing 19.5% compared to 2020.

Despite the economic pressures from Covid-19, investments in RPA have picked up quite rapidly. Today, many critical business processes in domains such as finance, healthcare, supply chain, and manufacturing are carried out by virtual workforces to support the current pandemic situation. The following figure is a part of a survey conducted by UiPath to understand the current state of the RPA developer. According to the survey, it is visible that industries such as finance, technology, and insurance are leading the way in adopting RPA into their ecosystem.

Universities worldwide have already started teaching RPA to their students to prepare the next generation. According to the State of the RPA Developer Report 2021 by UiPath, students are already seeking opportunities in RPA after graduation, with 82% of respondents considering a job in RPA after they graduate; 3 in 5 respondents consider RPA more diverse than other software development fields; and 100% of respondents believe RPA has high potential for growth over the next 5 years. As there is a massive demand for resources and opportunities, let's now look at how to come up with the right automation solution to solve your business requirements.

Every RPA project is required to go through a set of stages during its journey. These stages are often called the lifecycle of an RPA project. Each step handles different aspects of the automation solution — discovery, build, manage, run, engage, and measure. Let’s look at each stage to better understand the activities performed and what technologies help to best complete the designated tasks.

Discovery

Identifying the best processes to automate, optimize and standardize processes, and capture detailed requirements usually consumes a lot of resources and time. However, the power of science and AI introduced by many discovery tools make discovery processes more efficient. The knowledge and experience of the employees combined with AI enables the organization to come up with a holistic 360-degree view of all the processes.

There are many tools that users can use to record the process steps and analyze the recorded information to generate insights. Especially, the results generated by such process and task mining tools can be easily transformed into decisions to prioritize and identify the automation potential of the current processes. Further, the insights provided to the RPA Center of Excellence (CoE) team can solve process inefficiencies by introducing the right kind of standardization where necessary.

Build

The world of RPA today is moving towards the concept of having a robot for each individual. Hence, irrespective of an individual's background, they should be able to build and manage their robots. Today, there are low-code platforms for people with different levels of coding skills. Such development tools allow users to build scalable, adjustable, and intelligent automation solutions using a simple drag-and-drop canvas and dashboards.

With the introduction of RPA, every technology company found ways to build components that allow easy interaction with its platforms. Apart from the tools, there are many readily available components, code snippets, and code templates available online for users to download and use free of charge. Users can easily use such components by plugging them into their solution to interact with multiple software applications effectively.

Artificial intelligence is also a topic that we cannot exclude when building automation solutions. Integrating AI, ML, and other NLP capabilities with RPA workflows are now just a couple clicks away. RPA platforms come with built-in AI capabilities, which we can easily configure and train to use in our automation workflows to perform any complex activity. This approach has allowed business users to easily combine their workflows with AI to perform more complicated actions, while technical users can use the same or build their own.

Manage

As we manage our team, managing the virtual workforce is an essential aspect of the journey. Managing the virtual workforce usually includes centralized deployments, processes scheduling, automation workflows, monitoring for errors and inefficiencies, and scalability. Orchestration also enables global information management such as credentials, globally used configuration values, etc. for better tracking and management. Such features provide a single centralized interface to apply changes to all automation solutions with just a click.

Run

Virtual assistants execute your processes in any way you like — attended, unattended, or in a hybrid model. The flexibility offered by RPA technologies enables the virtual workforce to take up multiple background processes while executing foreground processes (which interact with UI elements). The attended robots work in the same machine as the user, helping their daily activities by conducting repetitive work simultaneously without interruptions. The unattended robots primarily work on backend processes that do not require any human involvement.

Engage

Automation is not just about automating repetitive activities. Robots today are also capable of interacting with people as chatbots to understand the user requirements and act accordingly. The power of AI and NLP enables robots to perform human-like conversations with users and collaborate to optimize the entire process from start to finish.

Today, automation platforms are configurable to monitor and communicate with web or mobile applications where robots can bring in exceptions and approvals to an employee to keep meaningful work flowing. This concept enables users to work on value-added activities while the robots work behind the scenes to bring required data to the screen as soon as the user needs it. An excellent example of the use of such apps is in a call center environment. Whenever a user receives a call, the robot captures the customer information either by listening and understanding the language or by automating specific inputs that bring in the required data to the app screen. This reduces the time involved for the operator to search and extract the required information from different applications.

Measure

Embedded analytical capabilities of RPA platforms enable users to define KPI's and track the ROI of the automation program through different reporting platforms. The performance dashboards built on data generated by the robots allow process owners, CoE leads, and management to monitor the performance of their digital workforce.

Govern

Governance usually wraps around all stages described above to better control the quality of the automation solution. Quality control mechanisms may vary from organization to organization as they have their own best practices and standards, depending on the requirements. However, it is vital to have a governance model around all stages to ensure consistency across the organization. Though every automation solution has a lifecycle, it does not ensure that we always build the most efficient solution for the process. Identifying the best procedure to automate requires a good level of research and understanding of the goal and process. Let’s have a look at some important considerations when deciding on automation.

Business processes may not be in perfect shape all the time. The processes that we see in organizations were created many years back, and those processes cannot be changed easily. However, these processes may have many manual and redundant steps that can be removed and optimized. The most crucial point to consider is that RPA is not a nail that we can use to fix a broken process that humans perform manually. Every RPA project should focus on some level of process standardization before any automation efforts. Characteristics of a non-standardized process include:

• Increased error rate
• Decreased quality of routine tasks
• Inefficient tasks
• Excess repetitive tasks
• Reduced functionality
• High maintenance costs
• Less reliable end results
• High variability in output
• No clearly defined inputs and outputs

Automation of such processes will not gain the required outcome for the organization without the proper application of process standardization. Hence, it is necessary to go through standardization and technical feasibility frameworks to understand the automation potential and standardization needs. The following diagram illustrates a basic framework:

The figure shows that any process with repetitive manual activities, rule-based decisions, electronic input, and high exception rates are not good candidates for automation. Such processes should undergo process improvements before applying automation. Further, we also need to consider any changes in the process and applications involved. Any expected changes require evaluation and reassessment before considering automation. However, any process that passes through all the criteria mentioned above is a good fit for automation.

As we now have an idea of what to consider before automation, let's look at what RPA can automate. RPA is a tool that mimics human interactions with digital platforms. However, with the help of different technologies, RPA can do even better.

In general, an RPA robot can easily automate any of the following:

• Automating reading and/or sending emails and attachments
• Logging into different web or enterprise applications
• Organizing files and folders according to business requirements by moving, copying, and creating files and folders
• Automatically filling in forms in web or desktop applications to submit data
• Reading and writing to any database
• Analyzing data available in different platforms
• Reporting across different systems
• Scraping data from web applications
• Collecting and analyzing IoT data
• Performing simple and complex calculations
• Extracting data from structured, semi-structured, and unstructured documents using templates, regex, and artificial intelligence
• Collecting social media statistics
• Automating customer service in call centers, bank counters, etc.
• Automating standard letter writing

Today, most small, medium, and large companies are adopting automation. Sometimes, introducing automation is not straightforward because of the state of the processes, as we discussed above. However, we should develop standards, practices, and approaches to identify suitable processes to automate based on the framework provided.

Pick a Few Tools to Start With

There are many RPA tools available in the market. After thinking about the critical points and the capabilities required, narrow your search for the perfect platform. Find the platform based on the capabilities, budget, and how you plan to scale.

Setting Up Your Environment

While we would like to cover every single approach in great detail, there’s only so much space in one Refcard. Hence, this section will focus on setting up an example RPA tool so that you can begin your RPA journey.

Registering for a Community Version

UiPath offers a free-of-charge community license that anyone can use for learning and building small automation solutions. Navigate to UiPath Cloud Platform, create your free account, and sign in to perform the following steps. Once you sign in, your screen should look similar to the following screenshot:

Installing UiPath Development Environment

On the Cloud platform, the right-hand side panel provides the option to download and install the development tool named UiPath Studio.

Configuring Licenses for Your Orchestrator

Navigate to the Admin page in the Cloud Platform and locate the Tenants Page. The Tenants page shows all the available Orchestrator tenants. Click on the “Edit License Allocation” option in the Tenant and assign all available licenses to the Tenant.

The number of licenses available to you may depend on the version. For example, the community version will have fewer licenses whereas trial and enterprise versions will have a higher number of licenses.

Configuring Orchestrator User

Click on the “Orchestrator” on the Tenants page or the home page to navigate to the Orchestrator. Follow the steps below to set up your environment:

1. Navigate to Tenant and click on “Manage Access”
2. Find your user, and click on the “Edit” option
3. On the “General details” screen, provide the user roles, including username, first and last name, email address, etc.
4. We would love to show how to enable both attended and unattended robots. However, for the scope of this Refcard, let’s only enable the attended robot for now. Click on the “Robot setup” option, enable “Attended Robot,” and finally, click on the “Update” button.

Now you have completed the user configuration. Next, let’s assign the user to a folder and complete the Orchestrator configuration.

Connecting UiPath Studio With Orchestrator

Open the UiPath Assistant from the Windows Start menu. Once the application is loaded, you will get an option to sign in. Sign in with the same account in which you created your Orchestrator instance. Now open the UiPath Studio, and you will have all the access needed to start building your first automation solution.

Creating the First Automation Project

There are many templates that you can select to start development. However, to keep it simple, create a blank process with any given name. Once you are in the created solution, you will have several panels available to interact.

The Solution panel contains all the files and folders in the solution. The Activities panel is where we mostly interact to drag and drop the required activities to build the automation workflow. Let’s do a simple Excel automation as our first project.

1. Create an Excel file as shown below:

Now, let’s try to find the total number of sales worth more than $2,500 and save them in a different sheet within the same Excel file.

2. Open the Main.xaml file from the Project panel

3. Search for “Excel Application Scope” and drag and drop the scope into the middle of the Design canvas

4. Configure the activity to point to the Excel file created

5. Place a “Read Range” activity (from Excel activities) within the Excel Application Scope

6. Create a new variable of type “DataTable” in the Variables panel

7. Configure the “Read Range Output” property in the Properties panel by providing the data table variable

8. Drag and drop a “Filter DataTable” activity

9. Click on the “Configure” button

10. In the “Filter Wizard” screen, provide the Input DataTable and the Output DataTable with the data table that we created

11. Configure the filter options as shown below:

12. Place a “Write Range” (via Excel activities) below the “Filter” activity

13. Configure the sheet name as “Sheet2”

14. Configure “Input DataTable” with the variable we used for the output of the “Filter DataTable” activity

15. Enable “Add Headers” from the Properties panel

Congratulations! Your completed workflow should look similar to the following:

16. Click on “Run project” from the Top Ribbon to execute the flow. Once complete, open the Excel file and check your output.

RPA technology has evolved from simple application-specific automation scripts to using multiple state-of-the-art technologies. RPA today has plenty of potential in shifting the way businesses operate. As the world navigates through the Covid-19 pandemic, we have seen more and more companies getting on board with RPA to automate manual tasks. As the demand grows for RPA, universities worldwide are preparing the next generation of the workforce with RPA knowledge and skills. As RPA revolutionizes the way we work, we also need to identify the right candidate processes with higher automation potential.