UNIT-2

AUTOMATION PROCESS ACTIVITES

Process automation overview
What’s keeping today’s business leaders up at night? For one thing, it’s the fact that competition is
fiercer than ever. Another worry is the lightning speed at which customer and market demands are
shifting and evolving. To compete and thrive, businesses need to seize upon every possible edge to
not only become more competitive and profitable, but to increase their resilience and agility. That's
where process automation comes in.
Increasingly, businesses are turning to process automation as a powerful tool in their fight to drive
their competitiveness and profitability. In fact, according to a recent Gartner survey of global
industry leaders, 80% of respondents cited automation as one of their core business priorities and
tactics for success.
Process automation definition
Process automation is defined as the use of software and technologies to automate business
processes and functions in order to accomplish defined organisational goals, such as producing a
product, hiring and onboarding an employee, or providing customer service.

Process Automation is a simpler, faster way to enhance business efficiency and agility. In this
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Business process automation (BPA) and digital transformation
Business Process Automation was initially a single aspect of the greater overarching area
of business process management (BPM). BPA was focused on improving back-end productivity by
taking over time-consuming and repetitive tasks. Today, however, BPA is no longer simply a
component of BPM, it has become the driving force behind it and a central cornerstone of
any digital transformation journey. Digital transformation – powered by technologies such
as AI and machine learning – means that the scope and scalability of modern business process
automation is almost boundless. Modern BPA solutions can now be integrated into both back-end
and front-end applications, streamlining processes from supply chains to HR, finance, customer
service, and beyond. The stages of business process automation
Business process automation examples
Ad-hoc or one-time activities or tasks are not the ideal candidates for process automation. This
technology is more suitable for repetitive tasks with formalised steps, sequences, and rules.
Automation ensures the business process is done right every time – involving the right people, in
the right order, considering the right information, and within a specified timeframe. A planned and
modelled business process is the first step to improving efficiency by reducing redundant tasks and
activities. While process automation priorities will vary from business to business, below are some
areas that often benefit from process automation.
 Recruitment. Process automation tools can help streamline various recruitment activities
including the ability to upload résumés and references quickly and efficiently, and to rapidly
process assessments, rejections, or follow-ups so you can find and scoop up the best talent.
 Employee onboarding and training. From records processing to compliance and training,
process automation can help simplify recruitment and onboarding tasks. This leads to
quicker development of an engaged and productive employee.
 Payment and payroll processes. The past few years have seen a big rise in the number of
gig workers and remote employees working in multiple regions. Automated processes can
help businesses streamline both regular payroll activities, as well as payment of contractors
and external vendors.
 Workforce scheduling. It is a struggle to manage employee scheduling – especially across
multiple locations and departments. The ability to sync time off requests and business trips
across departments means that absences get covered, and HR and payroll teams can better
automate admin tasks.
 Simpler and more consistent invoicing. While invoice generation should ideally be the
remit of accounting departments, this is not always the case. Automated invoicing processes
can help to alleviate errors, accounting mix-ups, and even legal risk.
 Customer experience. In a competitive climate, it’s easier than ever for your customers to
bounce away if they experience hassles and delays. Process automation helps to create a
more personalised customer experience and move customers quickly and accurately through
process flows.
 Compliance and regulatory tasks. It is essential that a variety of business processes adhere
to compliance and regulatory requirements. Process automation solutions log files and leave
a visible data trail, making it easier to monitor and review these activities in real time. For
example, before maintenance crews are given access to power plant workings, managers can
confirm that all potentially dangerous systems have successfully completed and logged the
necessary shut-down safety protocols.
Core business process automation technologies
Robotic process automation and workflow automation solutions are at the centre of any digital
automation transformation.
Robotic process automation (RPA)
RPA doesn’t refer to physical robots like you might see on an assembly line. Rather, RPA tools and
bots are integrated into business systems for the purpose of automating and simplifying various
tasks and interactions. RPA is a primary component of BPA. It describes software and bots that are
programmed to emulate and copy human actions to complete repetitive business tasks. RPA
software robots can navigate systems, read and enter data, and perform a wide range of rule-based
tasks.
Workflow automation
Workflow automation is often used interchangeably with RPA but that is not accurate. Workflow
automation can be defined as making the flow of tasks, documents, and information across work-
related activities perform independently in accordance with defined business rules and refers to
specific tasks within an entire workflow.
Benefits of business process automation
The biggest drivers for process automation have to do with the obvious benefits that come from
increased speed and efficiency, and greater opportunity for agility and innovation. Those benefits
include:
 More agile and resilient business structures overall
 More efficient operations including faster cycle times and first-time-right rates
 Improved compliance through more visible data trails and monitoring
 Reduced burden of slow, manual processes, creating greater freedom to innovate and grow
 Real-time collaboration across an organisation, building teamwork, and employee
success/satisfaction
 Improved customer service quality and response times

Achieving end-to-end process automation is an essential pillar in any successful digital

transformation journey. McKinsey recently conducted a survey of industry leaders who had
successfully met their business process automation goals. They found that in basically every case,
those successes had three strategic components in common:
1. Automation must be adopted as a strategic priority across the entire organisation, not just
tackled in silos as a way to address a few isolated processes
2. Process automation should centre on making the technology work for people, not the other
way around
3. The market is particularly unpredictable at the moment so a focus on scalability is essential
to sustained process automation success .
 UNIT-3
APP INTEGRATION RECORDING AND SCRAPING
Data scraping is a powerful tool in robotic process automation (RPA) that enables businesses to
access, organize, and process data quickly and efficiently. Data scraping as a component of RPA
facilitates the expedient collection of data for several purposes across all industries and with endless
possibilities. By automating the tedious and time consuming tasks of manually gathering,
organizing, and analyzing large amounts of data, businesses can save time, resources, and money
when processing typical business operations. Here are some ways in which automated data scraping
is utilized:
 Collect timely market data for companies that analyze consumer trends to develop different
strategies.
 Extract product details for competitor analysis or to transfer and utilize the information in
another application.
 Collect real-time financial data on stock prices, market indexes, and market projections to
make informed investment decisions.
 Gather essential information from reliable sources such as business listing directories,
search engines, and social media to facilitate lead generation and refine digital marketing
efforts.
 Provide price monitoring and comparisons in the travel and tourism and e-commerce
sectors, allowing these types of organizations to stay competitive.
Why Automation Matters: Key Benefits of Data Scraping in RPA
Boosting Data Accuracy with Automation
One of the most significant benefits of using data scraping for RPA projects is improved accuracy.
By using automated web scraping tools, businesses can ensure the accuracy of the collected data by
eliminating manual processes, which are typically more prone to errors and inconsistencies.
Additionally, automated web scrapers can identify any changes to source material that would
otherwise be missed when collecting data manually. This ensures that all relevant information is
collected accurately each time a scrape is performed.
Accelerating Data Collection Speed
Another advantage of data scraping in RPA is increased speed. Automated web scrapers are much
faster than manual methods since they do not require labor-intensive tasks such as typing or
copying into a spreadsheet. Instead, these tools use advanced algorithms to parse websites for
exactly what is needed in seconds instead of minutes or hours, greatly reducing the time needed to
complete tasks associated with large datasets.

Scalable Solutions for Growing Data Needs

Data scraping also provides scalability - a key factor in any successful RPA project. These tools can
easily scale up or down depending on the size and complexity of the dataset without needing
extensive human intervention or expensive hardware upgrades. This allows businesses to quickly
adjust their workflows as their needs change over time without worrying about high costs or long
implementation times associated with other solutions.
Cutting Costs with Cost-Effective Automation
Finally, data scraping offers cost savings compared to manual processes and other solutions, such as
API-based alternatives, which often require costly licenses or subscription fees. Since automated
web scrapers are an all-in-one solution that requires no additional software setup or coding
knowledge, businesses can reduce their expenses significantly when using these tools for their RPA
initiatives instead of traditional methods like copy-pasting from websites or setting up costly API
connections manually.
Core Components of Data Scraping Technology in RPA
At its core, data scraping technology consists of two main components: web crawlers and parsers.
Web crawlers are programs that systematically scan websites and catalog the information found
within them into a database or directly into an application. Parsers then take the raw data gathered
by web crawlers and interpret it to extract only the relevant information for further analysis or
processing. To achieve this goal, parsers use techniques such as pattern matching, regular
expressions, and natural language processing (NLP).
In addition to web crawlers and parsers, automated web scrapers rely on algorithms designed to
identify changes in source material. By using these algorithms, businesses can ensure that any
updates made to their chosen websites or other online sources are detected in real-time, so they
always have access to the most up-to-date data available. Additionally, automated web scrapers
often employ machine learning models, which allow them to “learn” how to better recognize
patterns over time, resulting in increasingly accurate results with each scrape.
Types of Data Scraping Tools for RPA Projects
Data scraping is a powerful tool and has become an integral part of robotic process automation
(RPA) systems. Different data scraping tools can help businesses extract data from web pages,
databases, documents, and other data sources. Each type of data scraping tool has advantages and
disadvantages depending on the task. Here are some of the most common types:
HTML Parsers
HTML parsers are designed to extract specific elements from HTML files or web pages. These
tools are well-suited for parsing information from websites with uniform structures.
API-Based Scrapers
API-based scrapers use application programming interfaces to access data stored in remote
databases or web services. These data scrapers can scrape various sources, including social media
websites, e-commerce stores, and government organizations. The main advantage is that these
scrapers often come with built-in support for authentication protocols making it easy to access
protected resources securely.
Web Scraping Libraries
Web scraping libraries are software packages specifically designed for managing large amounts of
data extraction tasks from multiple sources quickly and easily. These libraries typically include
tools for dealing with proxies, IP rotation, errors and cookies, and HTTP requests/responses
manipulation, making them the ideal choice for developers looking to automate complex tasks
within their RPA systems involving large amounts of data extraction jobs from different sources
simultaneously.
PDF & Document Parsers
PDF & document parsers allow businesses to extract text or images from PDFs and other
documents without manual intervention. These parsers use OCR technology (Optical Character
Recognition) to accurately capture text present in images and non-structured PDFs by transforming
it into a machine-readable format. The data is extracted and saved to jpg, jpeg, pdf, png, bmp, or
other files that can be easily accessed and edited by the user.
Database Extractors
Database extractors allow businesses to automatically extract structured data from various
databases, including SQL Server databases, Oracle databases, MySQL databases, and others where
the data can be queried using advanced filters and sorting options before being exported into
machine-readable formats such as CSV files for further processing within their RPA systems.
Future of Data Scraping in RPA and Business Efficiency
Data scraping is an indispensable tool for streamlining mundane processes through RPA systems
while ensuring accuracy and staying compliant with applicable regulations. It is important to
choose wisely when selecting a tool best suited for your purposes. No matter what type of
automated web scraping solution your business needs – there will likely be a customized solution
based on your requirements. Companies looking to incorporate this technology into their operations
should partner with a skilled and experienced software developer to engineer the best solution.
Structured data is a specific kind of information that is highly organized and is presented in a
predictable pattern. For example, all Google search results have the same structure: a link at the top,
a string of the URL and a description of the web page. This structure enables Studio to easily
extract the information, as it always knows where to find it.
The scraping wizard can be opened from the Design tab, by clicking the Data Scraping button.

The main steps of the data scraping wizard are:

1. Select the first and last fields in the web page, document or application that you want to
extract data from, so that Studio can deduce the pattern of the information.
 UNIT-4
EXCEPTION HANDLING AND CODE MANAGEMENT
Robotic Process Automation (RPA) has emerged as a transformative technology in recent years,
revolutionizing how businesses automate routine, rule-based tasks. RPA bots execute these tasks
quickly and precisely, reducing human errors and operational costs.
However, to achieve the full potential of RPA, it is essential to understand and implement robust
exception-handling mechanisms. In this comprehensive guide, we’ll delve into the world of
exception handling in RPA, exploring its importance, common challenges, and best practices.
The Significance of Exception Handling in RPA
Exception handling is the process of managing unexpected events or errors that may occur during
the execution of an RPA bot. System changes, data inconsistencies, networking issues, or other
unforeseen circumstances could cause these events. Exception handling is crucial for the following
reasons:
1. Error Recovery
In a dynamic business environment, systems and processes change frequently. Exception handling
allows RPA bots to adapt to these changes by gracefully recovering from errors and continuing their
tasks. This ensures uninterrupted automation and minimizes manual intervention.
2. Data Integrity
Data accuracy is permanent in RPA, as bots often manipulate sensitive information. Exception
handling safeguards data integrity by addressing errors or inconsistencies in real time, preventing
costly mistakes.
3. Scalability
To scale RPA implementations effectively, handling must be well-defined. It helps bots handle a
wide range of scenarios, making it easier to deploy them across various processes and systems.
4. Compliance
In regulated industries, compliance with rules and standards is critical. Exception handling ensures
that RPA processes adhere to compliance requirements by dealing with exceptions in a compliant
manner and generating audit trails.
5. Cost Reduction
Robust exception handling minimizes the need for human intervention, reducing operational costs.
It allows RPA bots to resolve common issues autonomously, enhancing efficiency and cost-
effectiveness.
Common Challenges in Exception Handling
Exception handling in RPA comes with its fair share of challenges. Identifying and addressing these
challenges is essential to create effective exception management strategies.
Some common hurdles include:
1. Lack of Standardization
Inconsistent error messages and codes across applications and systems can make identifying and
handling exceptions difficult for RPA bots. Standardization is essential to streamline the exception-
handling process.
2. Complex Workflows
Complex business processes often involve multiple systems and interactions. Exception handling in
such scenarios can be challenging due to the sheer number of potential error sources and outcomes.
3. Real-time Monitoring
Monitoring RPA processes in real-time to detect exceptions can be resource-intensive. Ensuring that
the right people are alerted when exceptions occur is a crucial aspect of exception handling.
4. Inadequate Logging
Comprehensive logging is essential for debugging and auditing. Many RPA implementations lack
sufficient logging, making diagnosing and resolving exceptions difficult.
5. Scalability Issues
Scaling RPA implementations while maintaining effective exception handling can be challenging.
As the number of bots and processes increases, so does the complexity of exception management.
Best Practices for Exception Handling in RPA
To overcome the challenges of exception handling in RPA, consider the following best practices:
1. Error Code Standardization
Standardize error codes and messages across different systems and applications to make
recognizing and categorizing exceptions more accessible for RPA bots. This practice simplifies
error handling and reduces the development time for new bots.
2. Thorough Error Analysis
Before implementing an RPA bot, thoroughly analyze the processes to identify potential exceptions.
Understanding the types of errors that occur helps in designing compelling exception-handling
logic.
3. Scalable Exception Libraries
Develop a library of reusable exception-handling components to share across different RPA
processes. These components should be scalable and adaptable to various use cases.
4. Real-time Monitoring and Alerting
Implement real-time monitoring solutions to detect exceptions as they occur. These solutions should
be capable of sending alerts to the appropriate personnel for immediate action.
5. Centralized Logging
Establish a centralized logging system that records all bot activities, including exceptions. This log
should be easily accessible for auditing, debugging, and performance analysis.
6. Exception Resolution Workflows
Create well-defined workflows for resolving exceptions. Ensure that human intervention is required
only for exceptional cases, while common issues are determined automatically by the RPA bot.
7. Regular Maintenance
Keep exception handling logic up to date. Periodically review and update exception handling.
Workflows to account for changes in processes, systems, or regulations.

Exception Handling in Action: Use Cases

Exception handling is not a theoretical concept. It is a practical necessity in the world of RPA. Let’s
explore a few real-world use cases to understand how it works.
Use Case 1: Invoice Processing
Consider an RPA in Accounts Payable Automation responsible for processing invoices from
various suppliers. Exception handling becomes critical when an invoice arrives in a format the bot
is not programmed to handle. The bot can identify this exception, notify the relevant team, and
create a record for manual intervention.
Use Case 2: Customer Onboarding
In the banking sector, RPA is often used to automate customer onboarding processes. Exception
handling comes into play when the bot encounters discrepancies in customer data or
documentation. It can either flag these exceptions for a human agent to review or attempt to resolve
them based on predefined rules.
Use Case 3: Inventory Management
In a retail environment, RPA bots manage inventory and restock products. Exception handling is
vital when the bot encounters unexpected shortages, damaged products, or discrepancies between
the physical list and digital records. The bot can generate alerts, update inventory records, and
trigger purchase orders to address these exceptions.
Use Case 4: Healthcare Claims Processing
In healthcare, RPA is employed for claims processing. Exception handling is crucial when a claim
submission contains errors, missing information, or discrepancies. The RPA bot can categorize
these exceptions and follow predefined workflows to resolve them, ensuring that valid claims are
processed efficiently.
Exception handling is a fundamental aspect of successful RPA implementation. It ensures that
RPA bots can adapt to changing environments, maintain data integrity, and operate at scale.
By following best practices, organizations can enhance their exception-handling capabilities,
ultimately reaping the benefits of efficient, cost-effective, and error-free automation. As the RPA
landscape evolves, a proactive approach to exception handling will be essential for staying
competitive in today’s digital business world.
 UNIT-5
DEPLOYMENT AND MAINTANANCE
Robotic Process Automation (RPA), deployment involves deploying the developed and tested bots
into a production environment, while maintenance ensures the bots continue to function optimally,
adapt to changes, and resolve any issues. Effective deployment and maintenance are crucial for
achieving the full potential of RPA by ensuring that bots operate efficiently and reliably in a
dynamic business environment.
Deployment:
 Production Environment:
After development and testing, the RPA bot is deployed to the production environment where it will
be used by users.
 Hypercare:
A period of close monitoring and support, often referred to as hypercare, is typically provided after
deployment to address any unforeseen issues.
 Deployment Models:
Organizations can choose different deployment models like on-premises, cloud-based, or hybrid,
each with its own advantages and considerations.
 Success Factors:
Successful deployment requires a well-defined RPA strategy, a dedicated team, and a clear
understanding of the processes to be automated.
Maintenance:
 Ongoing Support:
Maintenance encompasses activities like monitoring bot performance, updating bots,
troubleshooting issues, and providing support to users.
 Adaptation to Changes:
RPA bots must be able to adapt to changes in business processes, systems, and applications.
  Error Handling:
Effective maintenance includes strategies for handling errors and ensuring that bots can recover
from failures.
 Continuous Improvement:
Maintenance provides an opportunity to continuously improve bot performance and efficiency
based on user feedback and performance data.
 Benefits:
Proper maintenance ensures the longevity and reliability of RPA bots, contributing to business
continuity and process optimization.

Key Considerations:
 Security:
Security is a major concern when deploying bots on production systems, as they can interact with
sensitive data and systems.
 Scalability:
RPA deployments should be scalable to accommodate future growth and changing business needs.
 Training:
End-users should be trained on how to use RPA bots and what to do if issues arise.
 Documentation:
Thorough documentation is essential for managing RPA deployments, troubleshooting issues, and
training users.
By carefully considering these factors and implementing effective deployment and maintenance
strategies, organizations can maximize the benefits of RPA and achieve their automation goals.

Hybrid Deployment
A hybrid deployment is an approach whereby organizations deploy RPA software both on-premises
and on the cloud. Under this deployment model, the organization can leverage the benefits of both
on-premises and cloud-based deployment models. The benefits of hybrid deployment include
providing the benefits of both on-premises and cloud-based deployment models, allowing
organizations to maintain full control over their data and processes, and offering flexibility and
scalability to accommodate changing business needs. However, hybrid deployment requires a
higher upfront investment compared to cloud-based deployment and has complexity in managing
both on-premises and cloud-based RPA software.
Choosing the right RPA deployment model depends on several factors, such as the organization’s
size, industry, and IT infrastructure. These factors include security and compliance requirements,
scalability and flexibility, and upfront investment. On-premises deployment provides complete
control over data and processes, making it suitable for organizations with strict security and
compliance requirements. Cloud-based deployment offers flexibility and scalability, making it
suitable for organizations with changing business needs. Cloud-based deployment has a lower
upfront investment compared to on-premises deployment, making it suitable for small and medium-
sized businesses.
Selecting and prioritizing processes
Not every process is suitable for automation. In this phase, you’ll prioritize processes based on
complexity, volume, frequency and strategic importance. It’s usually wise to start with automating
high-volume, rule-based tasks like moving files from multiple systems or data entry.
Designing and developing
This stage can encompass a lot of steps, including finding your RPA software, process mapping, bot
design, scripting and system integrations.
Testing
Before deploying RPA into production, you’ll want to thoroughly test your bots or “digital workers”
to ensure they meet your business requirements. This phase involves a range of testing activities.
Deploying
With your RPA solutions tested and approved, they move into the production environment. Here’s
where you look at training your people and monitoring the automation’s performance.
Continuous improvement
Ongoing monitoring and maintenance are key to driving a reliable RPA program. To be successful,
you need to continuously monitor performance so you can address issues right away and make
enhancements where needed.
RPA methodologies will vary in these phases, but the essential thing to look out for is whether you

can tailor them to your specific business requirements and goals. Financial services and banking

ABANCA
ABANCA is the leading financial entity in northwestern Spain with 682 branches in 11 countries
across Europe and America, 6,080 employees and a turnover of more than €107 million.
“We can pay 99% of loans within 24 hours. We managed more than 23,000 financial transactions
with intelligent automation. It was a big, big success.”
Carlos Gonzalez Jardon, IT governance and operations, ABANCA.
Manufacturing
AGCO
AGCO is a leading global manufacturer of some of the world’s most reliable farm equipment. But
look under the hood and the way it operates has many parallels to most corporations of its size.
“We have over 60 processes in production, with only one process controller who is responsible for
the entire operation and maintenance of the processes. He’s able to complete this task in a standard
eight-hour workweek. So, the bots are running very, very reliably.”
Levente Illés, head of intelligent automation, AGCO.
Public sector
Thames Valley Police
While RPA has already been used by police forces across the country to automate processes
perceived as lower risk, Thames Valley Police has been more ambitious. It saw the potential for a
series of applications that could make an instant difference to the way policing operates in the third
decade of the twenty-first century.
“RPA is a no-brainer for us. We’ve released time for officers and staff to do other tasks and we can
focus them to be in the right place at the right time. We’ve saved money and we’re delivering a
much better service to the public.”
Superintendent Robert Brind, digital silver, Thames Valley Police.
Strategize Before You Digitize
RPA plans are a big investment of time, energy and resources – and it can bring huge benefits to
your organization, your people and your customers. But you have to do it right.
The ROM2 is designed to guide you through every step, with tailored solutions to get you wherever
you need to go, at whatever speed. Automate strategically with SS&C Blue Prism.