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Robotic Process
Automation & Cognitive
Technologies
Accelirate Inc.
Table of Contents
2
Empowering Business with Automation Technology………….4
Screen-Scraping…………………………………..…………..5
Enterprise Application Integration……………….…..6
BPA and BPM……………………………………..…………….7
Robotic Process Automation………………………………………..……9
Why RPA?……………………………………………………….12
RPA vs. BPM Technology………………………….……..13
Cognitive Technologies…………………………………..14
What’s Next?……………………….…………………………15
What About Security?……………………………….......16
Case Studies…………………………………………………………….………18
Accounting – AR Aging Follow-Up………….………….21
Accounting – AR Invoice Processing………………..23
HR Employee Onboarding………………..………….……..25
CRM to Accounting Data Migration………….……..27
Empowering Business
with Automation
Technology
FREmpowering Business with Automation Technology
Automation has been around within the Software Industry since the early 1990’s; The big PC
revolution during the late 80’s and early 90’s is what seeded the Client/Server software
development revolution within the Enterprise world. The Client/Server Technology revolution
made it possible for Businesses (no matter the size) to build applications that could be deployed
quickly using mass-scale Operating Systems such as Windows and Mac. This changed the game
because the age-old mainframe technology used prior was expensive and required massive
infrastructure investments, which put it out of reach for many Enterprises. A few years later (late
1990’s), the internet was commercialized and Internet-based Web Applications became the
standard for most Enterprise Software projects.
Almost immediately after there was a need to integrate the new breed of Client/Server and Web
applications with the mainframe-based legacy systems. Many solutions addressed the integration
issues, but the “quick-and-dirty” solution in most cases was “Screen-Scraping” technology.
4
FRScreen-Scraping
Screen-Scraping is normally associated with the programmatic collection of visual data from a
source instead of parsing data which is associated in Web-scraping. Originally, screen-scraping was
defined as the practice of reading text data from a computer display terminal’s screen. It also was
commonly used to refer to the bidirectional exchange of data. This could be a simple process in
which the controlling program navigates through the user interface, or a more complex scenario in
which the controlling program enters data into an interface meant for use by a human.
Although Screen-Scraping was a viable option in many cases, the end product lacked common
features, tied companies to old hardware, was unable to address changing business needs, and
was difficult to maintain. In the end, even though screen-scraping required a considerable
investment of resources, it left companies worse off than when they started. In addition, screen-
scraping was also never a scalable solution.
5
FR
To integrate disparate mainframe, Client/Server, and
Web-based applications, a new breed of EAI Tools,
also referred to as “middleware”, evolved rapidly
during the late 90’s. These tools were based on Hub
& Spoke or Service Bus-based integration
approaches. However, many EAI projects were not as
successful in integrating many enterprise
applications due to change management challenges,
competing standards, a lack of coordination, and
conflicting priorities between various business and IT
groups.
6
Enterprise Application Integration
FRBusiness Process Automation & Business Process Management
The ERP Software revolution of the 1990’s created a massive
multi-billion-dollar industry for an integrated suite of
business applications. ERP (Enterprise Resource Planning)
Systems initially focused on the back office (General Ledger,
Finance Reporting, Supply Chain, etc.) but quickly expanded
to include front-end business functions such as CRM
(Customer Relationship Management) technologies. For
those processes beyond the reach of ERP standardization and
automation, a new industry emerged – Business Process
Outsourcing (BPO). Business Process Outsourcing is defined
as contracting operations and responsibilities of a specific
business process to a third-party service provider. Between
these two approaches, workflow costs were transformed, at
least for companies large enough to justify an ERP
investment or global labor arbitrage. The BPO/Offshoring
Industry today is a $63 Billion industry, however, there are
plenty of opportunities to automate a large chunk of this
work using RPA and Cognitive Technologies instead.
7
Business
Process
Management
Objectives
& Strategy
Model
Assessment
Solution
Modeling
Solution
Analysis
Implement
Analyze &
Optimize
FR
As most IT systems are inherently automation engines in themselves, a valid option is to extend
their functionality to enable the desired automation, creating customized linkages between the
disparate application systems, including ERP systems, where needed. Business Process Automation
is an all-encompassing term which includes ERP systems and other systems that automate
processes around the ERP systems; for example, an OCR-based document imaging and workflow
management system integrated with an ERP system. In the late 90’s and early 2000’s, another
workflow processcentric approach was evolving, namely, Business Process Management (BPM).
BPM software is more comprehensive than Business Process Automation (BPA) software because it
is designed to manage multiple workflows within an organization. Rather than focusing on
automating a single process, BPM software allows businesses to achieve greater overall efficiency
and evolve along with changing business needs. Another result of a successful BPM software
implementation is the reduction in Human error, because, for instance, less manual data entry is
typically involved and there is a clearer understanding of roles and responsibilities.
8
Business Process Automation & Business Process Management
Robotic Process
Automation
FR
If you are a Business practitioner, the previous information is enough to give you a headache. A
Business uses IT to either increase revenue by marketing its products and services through new
channels, optimizing existing ones, or decreasing costs by creating efficiencies through the
deployment of the type of software mentioned above. Although there is no doubt that technology
approaches like ERP, EAI, BPA and BPM have made the Business World tremendously powerful and
scalable, the fact remains that such technology solutions in many cases have created their own
overhead infrastructure as well as a need for expensive IT staff. Today, whenever a business goes to
IT for solving any type of business challenge, the answer usually involves complex business process
re-engineering, custom software developments, or any other enterprise software deployment. The
advent of the Cloud in some ways democratizes access to technology solutions for businesses, but
there are many business processes for which a simpler solution is needed. For example,
Salesforce.com vs. an in-house CRM or BPM system solution.
10
Robotic Process Automation
FR
This is where RPA and the emerging Cognitive Technologies come into play. For example, consider a
workflow involving the processing of a large number of Invoices in the Accounts Payable
department. The Invoices can be received in any available format, including Excel, PDF, image files
or paper (which would need to be processed through OCR software). The downstream ERP system
would be ready to receive the standardized input, but in between, some sort of IT solution must be
put in place to standardize the data and the data entry. RPA-trained Business Analysts could
potentially use RPA software, which itself uses a rules-based GUI interface to quickly put together a
solution. In addition, if the Invoice images received are not standardized, it is possible for Cognitive
technology to extract the information and standardize it.
11
Robotic Process Automation
FR
The acronym RPA was introduced to the market only a few years ago. This is not something new,
but it was formalized over time by combining the capabilities provided by a combination of
traditional automation tools, including screen-scrapping, API integration, Macros, Scripts, etc. RPA
brings all of those capabilities within a GUI-based platform and has the ability to orchestrate a
business process along with the various steps and workflows required to execute that process. The
processes can also be linked together or performed individually to formulate an “assembly line” or
workflow. In addition, an RPA platform provides a full audit trail for actions performed by the
Robots.
RPA technology is not going to replace any of the ERP or BPM platforms, but it does enable the
business to achieve a very high level of automation ROI within a very short period of time. RPA
Platforms do not require extensive coding or technical capabilities; however, the business must
partner with IT to make sure IT security concerns are addressed and that governance processes are
put in place. This is important because the Robots must be provisioned as humans. Yes, you can
name your Robot “Leo” or whatever your heart desires, but IT must work with the business to
ensure that the Robotic workforce is subject to security and audit requirements that are similar to
those of its human counterparts.
12
Why RPA?
FR
BPM isn’t a specific piece of software, it’s an approach to streamlining business processes for maximum
efficiency and value. It is an in-depth look at how processes are operating that identifies areas for
improvement and builds solutions – usually from the ground up. BPM is about making sure the
infrastructure for your business processes is solid.
RPA, on the other hand, is designed to operate processes as a human would, so it exists on a surface
level. It’s faster to implement, ready to use with almost any software, and can easily be altered or
updated to adapt to the changing world. RPA and BPM share the same goal, just with different
implementation strategies.
While you could certainly use RPA to handle high-frequency processes previously performed by humans,
perhaps what is really needed is an overhaul of your original workflow. If a certain type of transaction
constitutes the bread-and-butter of your organization’s service for example, you’ll want to make sure the
process is as tight, efficient, and self-contained as possible. There are times when you must transform
the process itself rather than rely on a surface-level fix. BPM is a more comprehensive option for such
situations.
We know that given enough time and money, any large-scale solution can be implemented. However,
we also know that transforming a business structure isn’t always feasible. That’s where RPA can
potentially provide a quick ROI. If nothing else, you can use RPA to continue operations while
investigating a deeper fix.
13
RPA vs. BPM Technology
FR
Cognitive Technologies come into play when we are dealing with semi-structured or non-structured
input data. Traditional RPA technology is very good at processing structured data based on the
rules and the process orchestration.
Cognitive Technologies exist in different forms. The prepackaged software available in the market
today includes OCR (Optical Character Recognition), Handwriting recognition, Image recognition,
Natural Language Processing (NLP), and much more. Such prepackaged software, when combined
with RPA technology, can be very powerful. Self-learning-enabled RPA tools can be trained to
handle processes using built-in Machine Learning technology. In such systems, the software
“learns” based on the historical input data and the iterative observation of new data, this is
sometimes referred to as neural networks. For example, a Robot can be trained to recognize
multiple Invoice formats and standardize the Invoice data before feeding it into an ERP system.
Although cognitive technologies are emerging very quickly, it won’t be long before humans,
coupled with RPA and Cognitive technology, are able to take enterprise productivity to new levels.
14
Cognitive Technologies
FR
It is important to understand that although these technologies may have a “rocket science” feel to
them, they are quite simple to implement. For example, when we consume Internet on our
browser, no one really cares much about the underlying TCP/IP protocols that form the Internet’s
backbone. Or that when you flip the switch to turn on the light, you don’t really care where the
electricity comes from. RPA tools are powerful because they are relatively easy to implement and
empower the business. RPA can be put to good use very quickly in an array of use cases and over
time can be developed to utilize evolving cognitive technologies in a multi-layered approach. For
example, Invoices received in any format can be processed by a robot for data entry and parsed by
an OCR system capable of recognizing handwriting and images. Any exceptions that the systems
are not able to process can be handled by self-learning Robots, which will use a combination of
structured and unstructured data to recognize patterns of input data and ultimately handle the
exceptions themselves. Lastly, another important point is that it is rare for a cognitive RPA
implementation to completely automate the process end-to-end, as cognitive tools are hardly ever
100% accurate. Cognitive robotic automation is human-assisted; most data-entry-driven processes
consist of two job functions: the maker, in which an operator enters data into a system, and the
checker, in which the accuracy of the data is verified. The manual effort in the maker stage can
usually be eliminated, but the human checker stage is still required in most cases.
15
What’s Next?
FR
Security concerns of “Robots running amok” in your enterprise are often overstated. After all,
Robots, by design, are intended to do ONLY what they are told to do and nothing else. They do not
get distracted by catchy email subject lines and open virus-laden attachments, nor do they leave
the desktop unattended and leave their passwords written on Post-It notes under the keyboard.
Concerns are diminished by audits and controls. The only time issues surface is when Robots and
humans share credentials to perform similar tasks, or when Robots hand over a process to humans,
and humans hand that process back over to the Robots.
Best practices suggest that security and audit policies be applied to Robots exactly the way they
are applied to human workers. This includes individual credentialing and access provisioning.
Security is further strengthened by ensuring that automated processes run on virtual machines
inside the data center. However, process automation is also prone to erroneous logic and human
design errors. Exhaustive process analysis and documentation, stringent standards for
development, a rigorous testing process, and strict source code control governance policies are
required to ensure that automated processes are accurately implemented and are tamper-proof.
Experts conclude that when implemented using the best practices mentioned above, robotic
process automation results in a net reduction of the security risk by removing the risk associated
with humans.
16
What About Security?
FR
Security concerns of “Robots running amok” in your enterprise are often overstated. After all,
Robots, by design, are intended to do ONLY what they are told to do and nothing else. They do not
get distracted by catchy email subject lines and open virus-laden attachments, nor do they leave
the desktop unattended and leave their passwords written on Post-It notes under the keyboard.
Concerns are diminished by audits and controls. The only time issues surface is when Robots and
humans share credentials to perform similar tasks, or when Robots hand over a process to humans,
and humans hand that process back over to the Robots.
Best practices suggest that security and audit policies be applied to Robots exactly the way they
are applied to human workers. This includes individual credentialing and access provisioning.
Security is further strengthened by ensuring that automated processes run on virtual machines
inside the data center. However, process automation is also prone to erroneous logic and human
design errors. Exhaustive process analysis and documentation, stringent standards for
development, a rigorous testing process, and strict source code control governance policies are
required to ensure that automated processes are accurately implemented and are tamper-proof.
Experts conclude that when implemented using the best practices mentioned above, robotic
process automation results in a net reduction of the security risk by removing the risk associated
with humans.
17
What About Security?
Case Studies
FR
Over the next few pages are use cases for the deployment of RPA technology abound. Solutions
vary depending on the maturity of the existing Business Process Automation and the systems in
use. In organizations that are newly exploring the efficiencies that can be gained by automation, it
would be wise to start with a simple, repeatable process that has well-defined rules and data, such
as data entry from CRM to the Accounting system or the follow-up of AR pending Invoices via
email.
The next level of automation involves both Humans and Robots working together to complete a
task. The Robot handles well-defined tasks such as data extraction, collation, and entry, whereas
the human performs the intelligent operation of making decisions based on this information, then
handing the decision back to the Robot for further processing. A good example of this is the KYC
process at a Bank for a customer opening an Account. This requires the extraction of data from
various systems and websites as well as the collation of this data into a single report, which a Robot
is well-suited to do. This report can then be emailed to the decision maker for final processing.
19
Background Information
FR
The highest level of automation involves the use of AI and Machine Learning capabilities whereby
the automated worker understands unstructured data such as PDF documents in different formats,
or human conversations, and responds to such inputs by executing an appropriate workflow. For
example, a Robot can monitor a mailbox that receives various types of documents. The Robot is
able to “read” the document and execute a given workflow, for example, “This is an Invoice, so
enter this Invoice into the accounting system” or “This is a new customer form, so start a new
customer onboarding case in the CRM”. Such systems require seed data and “learn” from humans
when they encounter data that has not been previously observed.
Another example of such “intelligent” automation is a “chatbot”. A chatbot is able to converse with
a human and to respond with data or actions as required. For example, a bank may use a chatbot
to respond to customer queries. When a customer says, “I want to check the status of a check I
wrote,” the chatbot recognizes that the customer wants the check status and responds with “Could
you please give me the check number?” Once received, the chatbot interacts with the bank’s
internal systems to retrieve the relevant information and present it to the customer.
20
Background Information
FR
Accounts Receivable Staff spends a considerable amount of time chasing payable invoices. An out-of-control
or aging AR can result in considerable strain on business cash flows; hence, accounting teams are under
intense pressure to keep AR current.
This “chasing Invoice” activity includes:
1. Running the AR Aging report
2. Opening each Invoice to check Invoice details
3. Accessing the customer record to retrieve contact information
4. Writing an email to the customer, including a copy of the Invoice
The Automated solution is able to access both the accounting and email systems and perform all of these
actions in an automated fashion, giving your Accounting staff more time to address customer responses to
these follow-ups.
21
Accounting – AR Aging Follow-Up
Complexity – Simple
FR
22
Accounting – AR Aging Follow-Up
Complexity – Simple
Manual Labor
Reduction
90%
Implementation Cost
$12K
Week Implementation
2
FR
Invoice processing is a time-consuming task; Invoices must be scanned and read, and various checks must be
applied before they can be entered into the Accounting System.
The process generally includes:
1. Receiving and reading the Invoice
2. Checking the Invoice against the vendor and purchase orders
3. Sending it for approval if discrepancies are found
4. Entering the Invoice into the accounting system
5. Marking PO’s as complete
The Automated solution is able to receive invoice documents and access the accounting system to perform
the Vendor Name and PO validations. If any discrepancies are found, these are escalated for human
intervention. Once all validations pass, the invoice is entered into the accounting system and the PO status is
updated accordingly.
23
Accounting – AR Invoice Processing
Complexity – High
FR
24
Productivity Gain
40%
Implementation Cost
$43K
Week Implementation
4-6
Accounting – AR Invoice Processing
Complexity – High
FR
Employee Onboarding requires various verifications and data entry into multiple systems. These onboarding
tasks can include employment and background verification and the submission of information into the payroll
and IT provisioning systems, to name a few; these tasks can be time-consuming processes. A typical Employee
Onboarding RPA process may include:
1. Sending and receiving onboarding documents to/from the new employee
2. Performing employment eligibility verification
3. Creating a new employee record in the payroll system
4. Entering the employee’s tax information in the payroll system
5. Creating IT system accounts (login, email, etc.) for the new employee
The Automated solution is able to access and receive verified documents via email or a file folder and perform
the various checks required, including E-Verify or background verification. Upon completion of these checks,
the bots access various internal systems to perform the actions necessary to onboard the employee.
25
HR – Employee Onboarding
Complexity – Medium to High
FR
26
Manual Labor
Reduction
75%
Implementation Cost
$36K
Week Implementation
4
HR – Employee Onboarding
Complexity – Medium to High
FR
Data migration or updates between systems can be a hassle and requires extensive IT involvement. The usual
solution to this dilemma is manual human processes which are time consuming, expensive, and error-prone.
For example, new entries or updates of customer records from a CRM to Accounting System require manual
data entries and emails between Sales and Accounting teams. In high-volume businesses, this can create an
extensive backlog for the Accounting teams and can lead to customer onboarding delays.
This process generally includes:
1. The Sales team sends a new customer email to the Accounting team
2. The Accounting team receives new customer data via spreadsheets or email
3. The Accounting team creates a new customer record
The automated solution polls the CRM periodically to look for new and updated customer records. Once a
record is found, an automated process is kicked off to update the customer data in the accounting system
27
CRM to Accounting Data Migration
Complexity – Simple to Medium
FR
28
Productivity Gain
40%
Implementation Cost
$18K
Week Implementation
3
CRM to Accounting Data Migration
Complexity – Simple to Medium
Want to Learn More?
info@accelirate.com
www.accelirate.com
Thank You!

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A Guide to Robotic Process Automation & Cognitive Technologies

  • 1. Robotic Process Automation & Cognitive Technologies Accelirate Inc.
  • 2. Table of Contents 2 Empowering Business with Automation Technology………….4 Screen-Scraping…………………………………..…………..5 Enterprise Application Integration……………….…..6 BPA and BPM……………………………………..…………….7 Robotic Process Automation………………………………………..……9 Why RPA?……………………………………………………….12 RPA vs. BPM Technology………………………….……..13 Cognitive Technologies…………………………………..14 What’s Next?……………………….…………………………15 What About Security?……………………………….......16 Case Studies…………………………………………………………….………18 Accounting – AR Aging Follow-Up………….………….21 Accounting – AR Invoice Processing………………..23 HR Employee Onboarding………………..………….……..25 CRM to Accounting Data Migration………….……..27
  • 4. FREmpowering Business with Automation Technology Automation has been around within the Software Industry since the early 1990’s; The big PC revolution during the late 80’s and early 90’s is what seeded the Client/Server software development revolution within the Enterprise world. The Client/Server Technology revolution made it possible for Businesses (no matter the size) to build applications that could be deployed quickly using mass-scale Operating Systems such as Windows and Mac. This changed the game because the age-old mainframe technology used prior was expensive and required massive infrastructure investments, which put it out of reach for many Enterprises. A few years later (late 1990’s), the internet was commercialized and Internet-based Web Applications became the standard for most Enterprise Software projects. Almost immediately after there was a need to integrate the new breed of Client/Server and Web applications with the mainframe-based legacy systems. Many solutions addressed the integration issues, but the “quick-and-dirty” solution in most cases was “Screen-Scraping” technology. 4
  • 5. FRScreen-Scraping Screen-Scraping is normally associated with the programmatic collection of visual data from a source instead of parsing data which is associated in Web-scraping. Originally, screen-scraping was defined as the practice of reading text data from a computer display terminal’s screen. It also was commonly used to refer to the bidirectional exchange of data. This could be a simple process in which the controlling program navigates through the user interface, or a more complex scenario in which the controlling program enters data into an interface meant for use by a human. Although Screen-Scraping was a viable option in many cases, the end product lacked common features, tied companies to old hardware, was unable to address changing business needs, and was difficult to maintain. In the end, even though screen-scraping required a considerable investment of resources, it left companies worse off than when they started. In addition, screen- scraping was also never a scalable solution. 5
  • 6. FR To integrate disparate mainframe, Client/Server, and Web-based applications, a new breed of EAI Tools, also referred to as “middleware”, evolved rapidly during the late 90’s. These tools were based on Hub & Spoke or Service Bus-based integration approaches. However, many EAI projects were not as successful in integrating many enterprise applications due to change management challenges, competing standards, a lack of coordination, and conflicting priorities between various business and IT groups. 6 Enterprise Application Integration
  • 7. FRBusiness Process Automation & Business Process Management The ERP Software revolution of the 1990’s created a massive multi-billion-dollar industry for an integrated suite of business applications. ERP (Enterprise Resource Planning) Systems initially focused on the back office (General Ledger, Finance Reporting, Supply Chain, etc.) but quickly expanded to include front-end business functions such as CRM (Customer Relationship Management) technologies. For those processes beyond the reach of ERP standardization and automation, a new industry emerged – Business Process Outsourcing (BPO). Business Process Outsourcing is defined as contracting operations and responsibilities of a specific business process to a third-party service provider. Between these two approaches, workflow costs were transformed, at least for companies large enough to justify an ERP investment or global labor arbitrage. The BPO/Offshoring Industry today is a $63 Billion industry, however, there are plenty of opportunities to automate a large chunk of this work using RPA and Cognitive Technologies instead. 7 Business Process Management Objectives & Strategy Model Assessment Solution Modeling Solution Analysis Implement Analyze & Optimize
  • 8. FR As most IT systems are inherently automation engines in themselves, a valid option is to extend their functionality to enable the desired automation, creating customized linkages between the disparate application systems, including ERP systems, where needed. Business Process Automation is an all-encompassing term which includes ERP systems and other systems that automate processes around the ERP systems; for example, an OCR-based document imaging and workflow management system integrated with an ERP system. In the late 90’s and early 2000’s, another workflow processcentric approach was evolving, namely, Business Process Management (BPM). BPM software is more comprehensive than Business Process Automation (BPA) software because it is designed to manage multiple workflows within an organization. Rather than focusing on automating a single process, BPM software allows businesses to achieve greater overall efficiency and evolve along with changing business needs. Another result of a successful BPM software implementation is the reduction in Human error, because, for instance, less manual data entry is typically involved and there is a clearer understanding of roles and responsibilities. 8 Business Process Automation & Business Process Management
  • 10. FR If you are a Business practitioner, the previous information is enough to give you a headache. A Business uses IT to either increase revenue by marketing its products and services through new channels, optimizing existing ones, or decreasing costs by creating efficiencies through the deployment of the type of software mentioned above. Although there is no doubt that technology approaches like ERP, EAI, BPA and BPM have made the Business World tremendously powerful and scalable, the fact remains that such technology solutions in many cases have created their own overhead infrastructure as well as a need for expensive IT staff. Today, whenever a business goes to IT for solving any type of business challenge, the answer usually involves complex business process re-engineering, custom software developments, or any other enterprise software deployment. The advent of the Cloud in some ways democratizes access to technology solutions for businesses, but there are many business processes for which a simpler solution is needed. For example, Salesforce.com vs. an in-house CRM or BPM system solution. 10 Robotic Process Automation
  • 11. FR This is where RPA and the emerging Cognitive Technologies come into play. For example, consider a workflow involving the processing of a large number of Invoices in the Accounts Payable department. The Invoices can be received in any available format, including Excel, PDF, image files or paper (which would need to be processed through OCR software). The downstream ERP system would be ready to receive the standardized input, but in between, some sort of IT solution must be put in place to standardize the data and the data entry. RPA-trained Business Analysts could potentially use RPA software, which itself uses a rules-based GUI interface to quickly put together a solution. In addition, if the Invoice images received are not standardized, it is possible for Cognitive technology to extract the information and standardize it. 11 Robotic Process Automation
  • 12. FR The acronym RPA was introduced to the market only a few years ago. This is not something new, but it was formalized over time by combining the capabilities provided by a combination of traditional automation tools, including screen-scrapping, API integration, Macros, Scripts, etc. RPA brings all of those capabilities within a GUI-based platform and has the ability to orchestrate a business process along with the various steps and workflows required to execute that process. The processes can also be linked together or performed individually to formulate an “assembly line” or workflow. In addition, an RPA platform provides a full audit trail for actions performed by the Robots. RPA technology is not going to replace any of the ERP or BPM platforms, but it does enable the business to achieve a very high level of automation ROI within a very short period of time. RPA Platforms do not require extensive coding or technical capabilities; however, the business must partner with IT to make sure IT security concerns are addressed and that governance processes are put in place. This is important because the Robots must be provisioned as humans. Yes, you can name your Robot “Leo” or whatever your heart desires, but IT must work with the business to ensure that the Robotic workforce is subject to security and audit requirements that are similar to those of its human counterparts. 12 Why RPA?
  • 13. FR BPM isn’t a specific piece of software, it’s an approach to streamlining business processes for maximum efficiency and value. It is an in-depth look at how processes are operating that identifies areas for improvement and builds solutions – usually from the ground up. BPM is about making sure the infrastructure for your business processes is solid. RPA, on the other hand, is designed to operate processes as a human would, so it exists on a surface level. It’s faster to implement, ready to use with almost any software, and can easily be altered or updated to adapt to the changing world. RPA and BPM share the same goal, just with different implementation strategies. While you could certainly use RPA to handle high-frequency processes previously performed by humans, perhaps what is really needed is an overhaul of your original workflow. If a certain type of transaction constitutes the bread-and-butter of your organization’s service for example, you’ll want to make sure the process is as tight, efficient, and self-contained as possible. There are times when you must transform the process itself rather than rely on a surface-level fix. BPM is a more comprehensive option for such situations. We know that given enough time and money, any large-scale solution can be implemented. However, we also know that transforming a business structure isn’t always feasible. That’s where RPA can potentially provide a quick ROI. If nothing else, you can use RPA to continue operations while investigating a deeper fix. 13 RPA vs. BPM Technology
  • 14. FR Cognitive Technologies come into play when we are dealing with semi-structured or non-structured input data. Traditional RPA technology is very good at processing structured data based on the rules and the process orchestration. Cognitive Technologies exist in different forms. The prepackaged software available in the market today includes OCR (Optical Character Recognition), Handwriting recognition, Image recognition, Natural Language Processing (NLP), and much more. Such prepackaged software, when combined with RPA technology, can be very powerful. Self-learning-enabled RPA tools can be trained to handle processes using built-in Machine Learning technology. In such systems, the software “learns” based on the historical input data and the iterative observation of new data, this is sometimes referred to as neural networks. For example, a Robot can be trained to recognize multiple Invoice formats and standardize the Invoice data before feeding it into an ERP system. Although cognitive technologies are emerging very quickly, it won’t be long before humans, coupled with RPA and Cognitive technology, are able to take enterprise productivity to new levels. 14 Cognitive Technologies
  • 15. FR It is important to understand that although these technologies may have a “rocket science” feel to them, they are quite simple to implement. For example, when we consume Internet on our browser, no one really cares much about the underlying TCP/IP protocols that form the Internet’s backbone. Or that when you flip the switch to turn on the light, you don’t really care where the electricity comes from. RPA tools are powerful because they are relatively easy to implement and empower the business. RPA can be put to good use very quickly in an array of use cases and over time can be developed to utilize evolving cognitive technologies in a multi-layered approach. For example, Invoices received in any format can be processed by a robot for data entry and parsed by an OCR system capable of recognizing handwriting and images. Any exceptions that the systems are not able to process can be handled by self-learning Robots, which will use a combination of structured and unstructured data to recognize patterns of input data and ultimately handle the exceptions themselves. Lastly, another important point is that it is rare for a cognitive RPA implementation to completely automate the process end-to-end, as cognitive tools are hardly ever 100% accurate. Cognitive robotic automation is human-assisted; most data-entry-driven processes consist of two job functions: the maker, in which an operator enters data into a system, and the checker, in which the accuracy of the data is verified. The manual effort in the maker stage can usually be eliminated, but the human checker stage is still required in most cases. 15 What’s Next?
  • 16. FR Security concerns of “Robots running amok” in your enterprise are often overstated. After all, Robots, by design, are intended to do ONLY what they are told to do and nothing else. They do not get distracted by catchy email subject lines and open virus-laden attachments, nor do they leave the desktop unattended and leave their passwords written on Post-It notes under the keyboard. Concerns are diminished by audits and controls. The only time issues surface is when Robots and humans share credentials to perform similar tasks, or when Robots hand over a process to humans, and humans hand that process back over to the Robots. Best practices suggest that security and audit policies be applied to Robots exactly the way they are applied to human workers. This includes individual credentialing and access provisioning. Security is further strengthened by ensuring that automated processes run on virtual machines inside the data center. However, process automation is also prone to erroneous logic and human design errors. Exhaustive process analysis and documentation, stringent standards for development, a rigorous testing process, and strict source code control governance policies are required to ensure that automated processes are accurately implemented and are tamper-proof. Experts conclude that when implemented using the best practices mentioned above, robotic process automation results in a net reduction of the security risk by removing the risk associated with humans. 16 What About Security?
  • 17. FR Security concerns of “Robots running amok” in your enterprise are often overstated. After all, Robots, by design, are intended to do ONLY what they are told to do and nothing else. They do not get distracted by catchy email subject lines and open virus-laden attachments, nor do they leave the desktop unattended and leave their passwords written on Post-It notes under the keyboard. Concerns are diminished by audits and controls. The only time issues surface is when Robots and humans share credentials to perform similar tasks, or when Robots hand over a process to humans, and humans hand that process back over to the Robots. Best practices suggest that security and audit policies be applied to Robots exactly the way they are applied to human workers. This includes individual credentialing and access provisioning. Security is further strengthened by ensuring that automated processes run on virtual machines inside the data center. However, process automation is also prone to erroneous logic and human design errors. Exhaustive process analysis and documentation, stringent standards for development, a rigorous testing process, and strict source code control governance policies are required to ensure that automated processes are accurately implemented and are tamper-proof. Experts conclude that when implemented using the best practices mentioned above, robotic process automation results in a net reduction of the security risk by removing the risk associated with humans. 17 What About Security?
  • 19. FR Over the next few pages are use cases for the deployment of RPA technology abound. Solutions vary depending on the maturity of the existing Business Process Automation and the systems in use. In organizations that are newly exploring the efficiencies that can be gained by automation, it would be wise to start with a simple, repeatable process that has well-defined rules and data, such as data entry from CRM to the Accounting system or the follow-up of AR pending Invoices via email. The next level of automation involves both Humans and Robots working together to complete a task. The Robot handles well-defined tasks such as data extraction, collation, and entry, whereas the human performs the intelligent operation of making decisions based on this information, then handing the decision back to the Robot for further processing. A good example of this is the KYC process at a Bank for a customer opening an Account. This requires the extraction of data from various systems and websites as well as the collation of this data into a single report, which a Robot is well-suited to do. This report can then be emailed to the decision maker for final processing. 19 Background Information
  • 20. FR The highest level of automation involves the use of AI and Machine Learning capabilities whereby the automated worker understands unstructured data such as PDF documents in different formats, or human conversations, and responds to such inputs by executing an appropriate workflow. For example, a Robot can monitor a mailbox that receives various types of documents. The Robot is able to “read” the document and execute a given workflow, for example, “This is an Invoice, so enter this Invoice into the accounting system” or “This is a new customer form, so start a new customer onboarding case in the CRM”. Such systems require seed data and “learn” from humans when they encounter data that has not been previously observed. Another example of such “intelligent” automation is a “chatbot”. A chatbot is able to converse with a human and to respond with data or actions as required. For example, a bank may use a chatbot to respond to customer queries. When a customer says, “I want to check the status of a check I wrote,” the chatbot recognizes that the customer wants the check status and responds with “Could you please give me the check number?” Once received, the chatbot interacts with the bank’s internal systems to retrieve the relevant information and present it to the customer. 20 Background Information
  • 21. FR Accounts Receivable Staff spends a considerable amount of time chasing payable invoices. An out-of-control or aging AR can result in considerable strain on business cash flows; hence, accounting teams are under intense pressure to keep AR current. This “chasing Invoice” activity includes: 1. Running the AR Aging report 2. Opening each Invoice to check Invoice details 3. Accessing the customer record to retrieve contact information 4. Writing an email to the customer, including a copy of the Invoice The Automated solution is able to access both the accounting and email systems and perform all of these actions in an automated fashion, giving your Accounting staff more time to address customer responses to these follow-ups. 21 Accounting – AR Aging Follow-Up Complexity – Simple
  • 22. FR 22 Accounting – AR Aging Follow-Up Complexity – Simple Manual Labor Reduction 90% Implementation Cost $12K Week Implementation 2
  • 23. FR Invoice processing is a time-consuming task; Invoices must be scanned and read, and various checks must be applied before they can be entered into the Accounting System. The process generally includes: 1. Receiving and reading the Invoice 2. Checking the Invoice against the vendor and purchase orders 3. Sending it for approval if discrepancies are found 4. Entering the Invoice into the accounting system 5. Marking PO’s as complete The Automated solution is able to receive invoice documents and access the accounting system to perform the Vendor Name and PO validations. If any discrepancies are found, these are escalated for human intervention. Once all validations pass, the invoice is entered into the accounting system and the PO status is updated accordingly. 23 Accounting – AR Invoice Processing Complexity – High
  • 24. FR 24 Productivity Gain 40% Implementation Cost $43K Week Implementation 4-6 Accounting – AR Invoice Processing Complexity – High
  • 25. FR Employee Onboarding requires various verifications and data entry into multiple systems. These onboarding tasks can include employment and background verification and the submission of information into the payroll and IT provisioning systems, to name a few; these tasks can be time-consuming processes. A typical Employee Onboarding RPA process may include: 1. Sending and receiving onboarding documents to/from the new employee 2. Performing employment eligibility verification 3. Creating a new employee record in the payroll system 4. Entering the employee’s tax information in the payroll system 5. Creating IT system accounts (login, email, etc.) for the new employee The Automated solution is able to access and receive verified documents via email or a file folder and perform the various checks required, including E-Verify or background verification. Upon completion of these checks, the bots access various internal systems to perform the actions necessary to onboard the employee. 25 HR – Employee Onboarding Complexity – Medium to High
  • 26. FR 26 Manual Labor Reduction 75% Implementation Cost $36K Week Implementation 4 HR – Employee Onboarding Complexity – Medium to High
  • 27. FR Data migration or updates between systems can be a hassle and requires extensive IT involvement. The usual solution to this dilemma is manual human processes which are time consuming, expensive, and error-prone. For example, new entries or updates of customer records from a CRM to Accounting System require manual data entries and emails between Sales and Accounting teams. In high-volume businesses, this can create an extensive backlog for the Accounting teams and can lead to customer onboarding delays. This process generally includes: 1. The Sales team sends a new customer email to the Accounting team 2. The Accounting team receives new customer data via spreadsheets or email 3. The Accounting team creates a new customer record The automated solution polls the CRM periodically to look for new and updated customer records. Once a record is found, an automated process is kicked off to update the customer data in the accounting system 27 CRM to Accounting Data Migration Complexity – Simple to Medium
  • 28. FR 28 Productivity Gain 40% Implementation Cost $18K Week Implementation 3 CRM to Accounting Data Migration Complexity – Simple to Medium
  • 29. Want to Learn More? info@accelirate.com www.accelirate.com