Intelligent Process Automation (IPA)

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Framework Primer
Intelligence Process Automation
(IPA)
Presentation created by
Robotic Process
Automation (RPA)
Machine Learning
(ML) & Advanced
Analytics
Smart Workflow
Natural Language
Generation (NLG)
Cognitive Agents
1 2 3 4 5

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Contents
Overview
Fourth Industrial Revolution
5 Core Technologies of IPA
IPA Transformation Process
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Intelligent Process Automation (IPA) is a combines process redesign with
Robotic Process Automation (RPA) and Machine Learning (ML)
Presentation Overview
Intelligent Process Automation (IPA) is a set of emerging Digital Technologies that combine process
redesign with Robotic Process Automation (RPA) and Machine Learning (ML). IPA can be viewed as a
suite of Business Process Improvements and Digital Transformation tools that assists the employee
IPA essentially augments RPA technology with additional emerging Digital Transformation
technologies. In its full extent, IPA is comprised of 5 core technologies:
Robotic Process Automation (RPA)
Smart Workflow
Machine Learning (ML) & Advanced Analytics
The disruptive power of IPA is that is supplements traditional rule-based automation with decision-
making capabilities driven by emerging Deep Learning and Cognitive Technologies. The benefits of
IPA are numerous and significant in impact. They center around enhanced productivity and efficiency,
reduction in operational risks, and improved Customer Experiences.
Additional topics discussed include IPA use cases, IPA Transformation process, Operating Model
design, Minimal Viable Product (MVP), Change Management, Customer Journey, and Value Creation.
IPA will be a foundational part of organizations’ next-generation Operating Models.
Natural Language Generation (NLG)
Cognitive Agents

IPA seeks to automate and improve upon the routine tasks traditionally
by humans—this is achieved largely via RPA and ML
IPA Overview
IPA takes the robot out of the human.
Intelligent Process Automation (IPA) is a set of emerging Digital Technologies that combine process
redesign with Robotic Process Automation (RPA) and Machine Learning (ML). IPA replicates
activities traditionally performed by humans (via RPA) and, over time, learns to do them even better
(via Machine Learning).
What are RPA and ML?
DEFINITION
Robotic process automation (RPA) is an emerging
form of process automation technology based on
software robots or artificial intelligence (AI) workers.
RPA represents a tremendous opportunity for
organizations to increase performance, improve
productivity, decrease costs, among a plethora of
other benefits.
Machine Learning (ML) is a type of AI that provides
computers with the ability to learn and self-improve,
without being explicitly programmed.
ML focuses on the development of computer
programs that can change when exposed to new
data. Over time, as a ML program runs, it gets
better and better at the task at hand.
RPA Overview Machine Learning Overview

IPA has disruptive benefits to the organization—this ranges from cost and
operational efficiencies to growth and customer-focused improvements
IPA Benefits
IPA can significantly improve Customer Journeys by simplifying customer interactions
and accelerating business processes.
IPA can be viewed as a suite of
Business Process Improvements
and next-generation Digital
Transformation tools that assists the
employee.
It does this by removing tasks
that are:
The disruptive power of IPA is that is augments
traditional rule-based automation with decision-
making capabilities driven by emerging Deep
Learning and Cognitive Technologies.
Through this, IPA creates the following
primary benefits:
Repetitive
Replicable
Routine
Enhanced efficiencies
Increased employee productivity
and performance
Reduction of operational risks
Improved response times
Improved Customer Journey experiences

IPA offers significant impacts across the areas of Manual Activities,
Backend Processes, and Frontend Processes
IPA Use Cases
Even RPA alone—without the increased automation and efficiency
from the other technologies—can drive significant productivity gains.
Here are several examples of areas and tasks where IPA can offer a significant impact. They are
grouped into 3 categories of: Manual Activities, Backend Processes, and Frontend Processes.
Automation of Data
Aggregation
Automation of Data Rekeying
Automation of “not-in-good-
order” checks for new
applications or benefits
Automation of policy
maintenance and customer
data changes
Automation of data feed into
analytics-enhanced rules to
facilitate automatic decision
making (e.g. payment
approvals, claims processing,
suspicious activity flagging)
Automation of small
transactions with lower, but
incremental impact
Automation of correspondence
creation and sending
Automation of multiple system
information updates
Automation of application
checks to authorize
commissions
MANUAL ACTIVITIES BACKEND PROCESSES FRONTEND PROCESSES

Contents
Overview

The Fourth Industrial Revolution is now underway—driven by IPA, RPA,
and Artificial Intelligence
Fourth Industrial Revolution – Overview
"Mastering the Fourth Industrial Revolution" was the theme of the World Economic Forum
(WEF) Annual Meeting in 2016.
Coined by the World Economic Forum (WEF) in 2016, the Fourth Industrial Revolution, also
referred to as 4IR and Industry 4.0, is the fourth major industrial era, since the initial Industrial
Revolution of the 18th century.
The Fourth Industrial Revolution can be described as a range of new technologies that are fusing
the physical, digital and biological worlds, and impacting all disciplines, economies, and
industries. Major drivers to the Fourth Industrial Revolution include IPA, RPA, and AI.
First Industrial
Revolution
Second Industrial
Revolution
Third Industrial
Revolution
Fourth Industrial
Revolution
We are here

Each revolution destroys and creates new jobs, industries, and
ways of life
Fourth Industrial Revolution – Industrial Revolution Overviews
Stay ahead of the industry—you can receive the latest news related on 4IR by joining this
group on LinkedIn: https://www.linkedin.com/groups/13504373.
First Industrial
Revolution
Second Industrial
Revolution
Third Industrial
Revolution
Fourth Industrial
Revolution
The First Industrial
Revolution took place from
the 18-19th centuries in
Europe and America. It was
a period that saw the
transition from mostly
agrarian, rural societies
became industrial and
urban. Notable
developments include the
iron and textile industries
and the steam engine.
The Second Industrial
Revolution took place
between 1870 and 1914,
just before World War I.
Triggered by the advent of
electric power to create
mass production, this was a
growth period for pre-
existing industries and
expansion of new ones,
such as the steel, oil, and
electricity fields.
The Third Industrial
Revolution, or the Digital
Revolution, refers to the
advancement of technology
from analog electronic and
mechanical devices to the
digital technology available
today. The era started to
during the 1980s and is
ongoing. This era was
triggered by the rise of the
personal computer,
Internet, and mobile
communications.
The Fourth Industrial
Revolution builds on the
Digital Revolution,
representing new ways in
which technology becomes
embedded within societies
and even the human body.

The Fourth Industrial Revolution group is managed by Flevy—join to learn
about any of the below topics
Fourth Industrial Revolution – LinkedIn Group
Click here to join our community:
https://www.linkedin.com/groups/13504373.
Click here to join our community:
https://www.linkedin.com/groups/13504373.
Topics we discuss in our group
include, but are not limited to:
• Cyber-physical systems
• Artificial Intelligence / Singularity /
Machine Learning
• Internet of Things (IoT)
• 3D printing
• Cloud Computing
• Blockchain Networks
• Nanotechnology
• Biotechnology
• Automation / Robotics / RPA / IPA
• Quantum Computing
• Digital Transformation
Technologies

Contents
Overview

In its full extent, IPA is drive by 5 emerging Digital technologies—RPA, ML,
Smart Workflow, NLG, and Cognitive Agents
IPA will become an integral component of the operating models of organizations
in the future.
Source: Intelligent Process Automation: The Engine at the Core of the Next-generation Operating Model, McKinsey, 2017
In its full extent, IPA is comprised of 5 core technologies:
Robotic Process
Automation
(RPA)
RPA is process
automation technology
based on software
robots or artificial
intelligence (AI)
workers that allows for
automation of routine
tasks
ML is a type of AI that
provides computers
with the ability to learn
and self-improve—
these tools identify
patterns in structured
data
Smart Workflow is a
process management
software that
integrates tasks
performed by groups
of humans and
machines
NLG generates natural
language from a
machine
representation system,
such as a knowledge
base or a logical
form—i.e. it translates
data into a natural
language
representation
Cognitive Agents are
tools that combine ML
and NLG to build a
completely virtual
workforce—i.e.
“agent”—that is
capable of performing
a variety of tasks
Machine
Learning (ML) &
Advanced
Analytics
Smart Workflow
Natural
Language
Generation
(NLG)
Cognitive
Agents
1 2 3 4 5

RPA and ML are at the heart of IPA
Core Technologies Details (1 of 3)
Robotic Process
Automation (RPA)
• RPA automates routine tasks, such as data extraction and cleansing, through
existing user interfaces
• The RPA “robot” has a user ID just like a normal employee. It can perform
rules-based tasks, such as accessing emails and systems, performing
calculations, creating documents and reports, checking files, customer
complaint processing, etc.
• End-to-end processes can be fully automated and executed by the robot. The
employee will only handle exceptions
• The RPA market is growing at an extremely fast pace—doubling every 6
months and projected to reach $5B by 2020
Machine Learning
(ML) & Advanced
Analytics
• These are algorithms that identify patterns in structured data, e.g. daily
performance data. This is done through “supervised” and “unsupervised”
learning algorithms
– Supervised algorithms learn from structured data sets of inputs and outputs
before beginning to make predictions (based on new inputs) on their own
– Unsupervised algorithms observe structured data and begin to immediately
provide insights on recognized patterns
• Advanced Analytics has already been implemented extensively within HR
organizations to determine and assess key behavioral attributes in leaders and
managers, so as to better predict behaviors, develop career paths, ad plan
leadership successions

Smart Workflow and NLG further enhance the software automation
capabilities
Smart Workflow
• The Smart Workflow process management software integrates tasks
performed by groups of humans and machines. It can do this by sitting on top
of RPA to help manage the full process
• This allows employees to initiate and track the status of an end-to-end process
in real time
• The Smart Workflow software will manage handoffs between various groups,
including between robots and human employees, and provide statistical
reporting on process bottlenecks
Natural Language
Generation (NLG)
• These are software engines that create seamless interactions between the
human employees and technology by following rules to translate observations
from into natural language
– Broadcasters have already been using NLG to draft stories about games in
real time
• Structure performance data can be imported into an NLG engine to write
internal and external management reports automatically
– In fact, NLG has been utilized by a top tier financial institution to replicate its
weekly management reports

Cognitive Agents are “virtual agents”—they are commonly used now in
customer support
Cognitive Agents
• These are technologies that combine ML and NLG to build a completely virtual
agent that is capable of execution tasks, communicating, learning from data
sets, and even making decisions based on “emotion detection.”
• Cognitive Agents are being utilized to support employees and customers over
the phone or via live chat.
– In one example, a UK auto insurer used Cognitive Agents and realized a
22% increase in conversion rates, a 40% reduction in validation errors, and
a 330% Return on Investment (ROI)
As IPA handles more mundane business processes, human employees can focus
on delighting customers and intellectually challenging work.

Contents
Overview

The approach to IPA Transformation follows a 6-phase process
IPA does not require a significant infrastructure investment, as it leverages
the existing enterprise architecture and IT systems.
Operating Model
Alignment
IPA Portfolio
Buildout
Minimum
Viable Product
(MVP)
Development
Value
Creation
Capabilities
Development
Change
Management
To develop a success IPA Transformation at scale, follow this 6-phase process:
1 2 3 4 5 6

In the initial phase, our organization rapidly aligns on IPA’s role in its
future state Operating Model
Phase 1. Operating Model Alignment
Automation is coming—now it’s time think strategically on how to apply it
to the future state of the organization.
Operating Model
Alignment
Rapidly align on IPA’s
role in Operating Model.
1
For a successful IPA Transformation, we must have a clear understanding of the
overarching corporate strategy and the role of the next-generation Operating
Model to help achieve this strategy.
This requires a clear understanding of the desired future state—and likewise the
journeys to focus on to reach this state.
Management must evaluate and align on the approaches and capabilities to
implement this target Operating Model. In many cases, IPA plays a critical,
perhaps dominant, role in driving this change.
The greatest value of IPA derives from when organizations understand how this
technology can be leveraged to bolster other capabilities and approaches in the
Operating Model.

In the second phase, we design around the full portfolio of IPA solutions
to maximize the business impact and ROI
Phase 2. IPA Portfolio Buildout
A fundamental process redesign is necessary to transform the way a group
or process works.
IPA Portfolio Buildout
Design around the full
portfolio of IPA solutions
to maximize impact.
2
In the Digital Age, technologies are rapidly advancing. This means we need to
move quickly and holistically. Organizations should not focus on a select few IPA
technologies. Rather, an effective solution with maximum impact arises when a
multitude of IPA technologies are launched and collaborate together.
In other words, organizations need to envision and implement holistic
optimization programs to maximize ROI.
It may appear easier and faster to implement IPA initiatives in silos. However,
this approach is inherently flawed, as individually, these initiatives are insufficient
to capture enough value.
A detailed implementation roadmap needs to be developed to identify all
automation-enhancement opportunities. This also allows businesses to
sequence the IPA projects by balancing their impact with the feasibility of scaling
solutions from initial use cases.

The development and rollout approach is to build a rapid Minimum Viable
Product (MVP) first—then, go for more complete solutions
Phase 3. MVP Development
The rapid returns from the MVP pilots also help secure early support from stakeholders and
the broader organization.
MVP Development
Build a rapid minimum
viable product (MVP)
solution.
3
As aforementioned, the eventual goal is to design a full IPA portfolio. How-ever,
we should start with a minimum viable product (MVP) as a pilot project.
A MVP is the most stripped-down version of the product that can still accomplish
the task and satisfy early adopters. The final, complete set of features is only
designed and developed after considering feedback from the product's initial
users and learning from the mistakes of the MVP.
Many executives have the mistake of going for the full solution immediately.
They end up overpromising and under-delivering, as the project takes too long to
complete and runs vastly over budget.
As with most Digital initiatives, it is best to select an –end-to-end process of
Customer Journey to redesign and enhance using IPA—and then work to launch
that MVP first.
IPA can therefore deliver tangible value in weeks, rather than years, in the form
of fewer (manual) errors and free up time for back-office employees to work on
higher value activities.

We need to build momentum and capture value—it’s a combination
of quick wins and long-term developments
Phase 4. Value Creation
Value Creation
Build momentum and
capture value.
4
The approach IPA implementation should be a combination of quick wins with
larger, long-term developments.
The IPA roadmap should be grounded in a fundamental process redesign that
sequences automated modules for production and reimagine the way groups and
functions capture value in the future state.
Every product line has a different degree of potential for standardization and
automation. These differences needed to be carefully considered, examined,
and sequenced. A good tool for this exercise is a 2x2 matrix with Degree of
Standardization on one axis and Impact through Automation on the other. See
example below for the Insurance industry.
High
Low
High
Processes are
repetitive and
predictable
Processes are stable
over time
Processes have
lower level of
customization
Process adopt
common industry
standards and
specifications
Processes are
repetitive and
predictable
Processes are stable
over time
Processes have
lower level of
customization
Process adopt
common industry
standards and
specifications
Impact through Automation Low
Worker’s
comp
Property
Auto
General &
other
liability
Financial
Crop
Inland
marine
Fire
Medical
malpractice
Improve customer &
intermediary
satisfaction, quality &
turn around time; build
core competencies
Engage employees
through automation,
robotics, and analytics
leadership
Variabilize cost & allow
for pace and flexibility
Improve customer &
intermediary
satisfaction, quality &
turn around time; build
core competencies
Engage employees
through automation,
robotics, and analytics
leadership
Variabilize cost & allow
for pace and flexibility
Degree of
Standardization

With any large scale Transformation program, we strive for developing
lasting capabilities with sustainable results
Phase 5. Capabilities Development
The most successful way to build lasting IPA capabilities is via a “lean-by-doing” approach
that combines coaching, on-the-job training, and knowledge sharing.
Capabilities
Development
Embed lasting
capabilities to achieve
sustainability.
5
For last capabilities, we need to embed critical business analysis and
digital skills into the business units, so that they can own and sustain the
redesigned processes.
We also need to redesign existing organizational structures to achieve
the following objectives:
– Capture value
– Establish a future state Operating Model to scale up IPA initiatives
– Create blueprints for future structures to capture impact and embed
new capabilities; and
– Offer training and workshops to explain why automation of manual
processes will free up resources to focus on more value-added activities.
To capture value at the enterprise scale, technology skills alone is not enough.
We need team with deep skills in IPA technologies, business process redesign,
Lean Management principles, and domain expertise. Many companies decide to
bring in external support to supplement their existing talent pool and accelerate
the IPA Transformation.

The last phase is to carefully coordinate Change Management and
Communications efforts
Phase 6. Change Management
The ease of transition is dependent on how adaptable our employees
are to agile practices.
Change Management
Carefully coordinate
change management and
communications.
6
Any Transformation initiative requires a Change Management stream for
successful and sustainable implementation.
We need to identify and develop Change champions to minimize Change
resistance and make the Transformation a success.
A robust Communications plan is also needed to help management employee
redeployment, generate excitement, and align the Change story with the
corporate strategy.
We need to ensure the new execution model resulting from the IPA
Transformation is aligned with our corporate culture.

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1
Flevy (www.flevy.com) is the marketplace
for premium documents. These
documents can range from Business
Frameworks to Financial Models to
PowerPoint Templates.
Flevy was founded under the principle that
companies waste a lot of time and money
recreating the same foundational business
documents. Our vision is for Flevy to
become a comprehensive knowledge base
of business documents. All organizations,
from startups to large enterprises, can use
Flevy— whether it's to jumpstart projects, to
find reference or comparison materials, or
just to learn.
Contact Us
Please contact us with any questions you may have
about our company.
• General Inquiries
support@flevy.com
• Media/PR
press@flevy.com
• Billing
billing@flevy.com

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