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Appendix A: RPA Consultants

Atos ( www.atos.net/en/ ) is an IT consulting firm that has over 110,000 employees in 73 countries and annual revenues of more than 11 billion euros. In Europe, the company is a leader with cloud computing, cybersecurity, and high-performance computing.

Regarding the RPA segment, the company has much experience, starting with UiPath implementations back in 2015. Atos also has a major focus on providing advisory services with AI. What’s more, the company acquired Syntel, which brought with it the SyntBots RPA platform (it is generally focused on IT operations).

Accenture ( www.accenture.com/us-en ) is a top professional services company for strategy, digital, and operations, with experience in more than 40 industries. The company has 492,000 employees in more than 120 countries.

No doubt, Accenture can implement RPA at scale. There is also deep experience with analytics and AI.

Capgemini’s ( www.capgemini.com/us-en/ ) roots go back more than 50 years. As of now, Capgemini has over 200,000 employees across 50 countries. In 2018, the revenues were 13.2 billion euros.

While the company has experience with multiple RPA vendors, the primary focus has been with UiPath implementations. The company has also been investing heavily in AI/ML with its “Perform AI” framework.

Conduent ( www.conduent.com/ ) is one of the world’s largest business process companies (it was spun off from Xerox in December 2016). There are about 82,000 employees and the company serves a majority of the Fortune 100 companies and more than 500 government entities.

Conduent has developed its Automated Suite, which helps with RPA and other automation approaches like case management and intelligent automation.

Cognizant ( www.cognizant.com/ ) is ranked 193 on the Fortune 500 and has an extensive set of professional service offerings. In 2019, Forrester gave the firm the highest possible rating for customer and business outcomes as well as partner ecosystem and commercial model criteria for RPA. According to the report: “Cognizant is the RPA turnaround specialist. Cognizant differs from many of its SI peers in that its organizational structure pivots around digital business, giving it a slight advantage in having a value-centric, business-first view of the impact of automation. Its RPA services business has significantly more engagements within line-of-business functions than the typical back-office mix of its peers.” ¹

The company has about 2,500 specialists that focus on RPA deployments.

Deloitte ( www2.deloitte.com/us/en.html ) provides a broad range of services, such as for audit, consulting, and tax across more than 20 industries. The firm has about 80,000 employees and generates close to $20 billion in annual revenues.

Note that Forrester named Deloitte the top consulting firm for RPA (the firm was referred to as the “North Star”). ² Given its overall specialization, it should be no surprise that the company targets finance and accounting. There is also a set of prebuilt tools, including a process discovery system.

DXC Technology ( www.dxc.technology/ ) is one of the early IT consultants (the company is the result of a merger between CSC and the Enterprise Services business of Hewlett Packard Enterprise). There are more than 6,000 private- and public-sector clients that span 70 countries and there are over 138,000 employees worldwide.

DXC has built a large RPA business, which involves its “robotics-as-a-service” platform (with this, a customer can have their software managed and hosted on the cloud). The department has more than 1,000 automation experts.

In early 2018, the company launched its DXC Agile Process Automation (APA) platform, which involves a blend of RPA with AI. ³ This also involved partnerships with Blue Prism and UiPath.

EY ( www.ey.com/en_gl ) provides professional services for assurance, tax, and complex transactions. The firm has 260,000 employees and 1 million alumni.

For RPA, EY’s largest deployment is its own! The firm also has focused primarily on Blue Prism for its implementations and there is a growing business with SAP. Furthermore, EY has built EYSight, which helps with assessing a company’s processes.

In 2018, HFS Research named the firm as the top player for RPA services (the survey included 29 vendors). According to Elena Christopher, who is the research VP of HFS Research: “Though RPA has emerged as a powerful change agent for enterprises, it is still a nascent market and service providers play an important role throughout the life cycle of planning, implementation, management, operation and optimization. EY teams have leveraged RPA to support and scale end-to-end process transformation for clients and exhibited a strong mix of service execution excellence, applied innovation and vision, and verified customer satisfaction to rise to the top of our RPA services study.” ⁴

Genpact ( www.genpact.com/ ) provides both consulting and BPO services. There are more than 87,000 employees and revenues of $3 billion.

Interestingly enough, with BPO, the company already has access to the various major processes in a company – say, for finance or IT – and has continued to look at ways to optimize systems, say, with lean and Six Sigma. Because of this, RPA services are a natural extension. All this is part of a “lift-shift-transform” model. Genpact has also made a string of acquisitions, such as for PMNsoft, TandemSeven, and RAGE Frameworks, to bolster its automation efforts.

Hexaware (hexaware.com) is a provider of IT and BPO consulting services (its moto is “Automate Everything, Cloudify Everything, Transform Customer Experiences”). The firm has 33 global offices, more than 18,000 employees, and annual revenues of $677.7 million.

Hexaware has a detailed business process framework that helps deal with the complexity, transaction volumes, and legal/regulatory requirements. After this, the company helps put together a strategy for a comprehensive implementation. Hexaware has partnerships with the following RPA vendors: Automation Anywhere, WorkFusion, UiPath, Blue Prism, and PEGA.

HCL Technologies ( www.hcltech.com/ ), which has been around for more than four decades, has developed the Mode 1-2-3 strategy for providing IT services to clients to help with trends like the cloud, analytics, IoT, and automation. The framework covers core services and next-generation services, products, and platforms.

HCL has more than 147,000 employees (which the company calls “ideapreneurs”) that work across 44 countries. It also serves half of the Fortune 500 and 650 of the Global 2000.

With RPA, the company has full-on services and has deep experience with verticals like banking, capital markets, public services, healthcare, telecom, consumer services, and manufacturing.

Infosys ( www.infosys.com ) was founded in 1981 by seven engineers in India (the start-up capital was a mere $250). But the company would ultimately become one of the largest IT consulting firms. Today it has 229,000 employees (10,000 are based in the United States) and revenues of $12.4 billion. In 2019, Forbes named Infosys No. 3 for the World’s Best Regarded Companies, based on factors like “trustworthiness, honesty, social conduct, fairness to its employees and the performance of its products and services.” ⁵

The company’s RPA practice has more than 1,000 consultants and developers that use a proprietary platform called AssistEdge, which is used by 360 enterprise customers. In fact, it has realized $2 billion in savings and currently process 50+ million transactions every month. ⁶

Infosys also has support for RPA providers like Automation Anywhere, Blue Prism, UiPath, and WorkFusion.

KPMG ( https://home.kpmg/xx/en/home.html ) operates in 147 countries and has 219,000 employees. Regarding RPA, the company has emphasized process mining. Consider that KPMG has a major relationship with Celonis, which is the top software provider in the category. The firm has also developed the RPA-TOM (Target Operating Model) approach, which is a six-step process for RPA implementations.

Mphasis ( www.mphasis.com ) operates with a system it created called Front2Back, which leverages cloud and cognitive technologies to allow for more personalized digital experiences. There is also its system that helps with the transformation of legacy IT environments.

PwC ( www.pwc.com/ ) was founded in London over 100 years ago as an accounting services firm. But since then, PwC has expanded significantly, with over 276,000 employees in 157 countries. Just some of its services include assurance, tax, cybersecurity, HR, and forensics.

What about RPA? It’s certainly a growing part of PwC’s portfolio. The firm helps with the initial implementation and ongoing management, such as with the development of a CoE. There has also been success in specialized areas for RPA like the audit function.

TCS ( www.tcs.com/ ) is an IT services and business solutions powerhouse, with more than 450,000 employees in 46 countries and consolidated revenues of $20.9 billion. Note that the firm has a long history with providing advisory services for automation, such as with its outsourcing operations. And yes, RPA is a major part of this. Among the large firms, TCS is known to have relatively lower costs.

Appendix B: RPA Resources

RPA web sites :

Horse for Sources Blog: www.horsesforsources.com
RPA Today: www.rpatoday.net
CIO.com: www.cio.com/
TechRepublic: www.techrepublic.com/
The Enterprisers Project: https://enterprisersproject.com
IEEE: www.ieee.org/

Software review sites that cover RPA:

RPA influencers:

Alastair Bathgate, Blue Prism CEO: @AlastairPRSM
Pat Geary, evangelist at Blue Prism: @EvangelistBlue
Mihir Shukla, Automation Anywhere CEO: @MihirAndNow
Gary Conway, chief evangelist at Automation Anywhere: @GaryGConway
Daniel Dines, UiPath CEO: @danieldines
Guy Kirkwood, chief evangelist at UiPath: @guykirkwood
Kirk Borne, principal data scientist and executive advisor at Booz Allen Hamilton: @KirkDBorne
Frank Casale, the founder of The Outsourcing Institute: @FrankCasale
Mike Quindazzi, the digital alliances sales leader at PWC: @MikeQuindazzi
J. P. Gownder, the VP tech analyst at Forrester: @jgownder

Other Books:

Service Automation, Robots, and the Future of Work (2016), Willcocks and Lacity
Robotic Process Automation and Risk Mitigation: The Definitive Guide (2017), Lacity and Willcocks
Robotic Process Automation and Cognitive Automation: The Next Phase (2018), Lacity and Willcocks
Becoming Strategic with Robotic Process Automation (2019), Willcocks, Hindle, and Lacity

Appendix C: Glossary

AI (artificial intelligence ): Involves computers that are capable of learning from experience. This is generally done by processing data with sophisticated algorithms. AI is a broad category that involves subsets like machine learning, deep learning, and natural language processing (NLP).

API (application programming interface ): This is software that connects two applications. It is actually a more complex form of automation vs. RPA because it requires the assistance of developers.

Assisted RPA (or attended RPA): This involves automation of processes that still require human collaboration. This is the first generation of RPA technology.

Autonomous RPA : This is essentially a blend of attended and unattended RPA.

Big Data : Technology that allows for processing enormous amounts of data. Data is often described as having the three V’s: volume, variety, and velocity.

Black box testing : This is a form of testing software where the tester does not know the internal code but instead looks at the input and output to see if there are any problems.

Boolean : This is a data type that is either true or false.

Bot : This is at the heart of an RPA system. A bot automates a set of instructions, such as moving data and pressing buttons on an app.

Bot Store : This is a marketplace, similar to iTunes or Google Play, where you can download bots into your platform.

Breakpoint : This is used for debugging code. That is, there is a termination of the program at certain points allowing for the coder to see what is happening.

Business analyst : This person manages the duties between the company’s SMEs (subject matter experts), RPA supervisors, and developers.

Business continuity plan : This is a document that sets forth the goals and actions to be taken when things go wrong with a bot or an RPA implementation.

Business process management (BPM) : This type of software has been around since the 1980s. Generally, it is much more comprehensive than RPA. Although, because of this, the implementation of BPM can be more costly and time-consuming. The technology also requires much effort from an organization to maintain.

Business process outsourcing (BPO) : This is an organization that manages outsourced services, such as for back-office operations.

Categorical data : Data that lacks numerical meaning but instead has textual meaning, say, with describing race or gender.

Center of excellence (CoE): This is a group of people who implement, deploy, and manage an RPA system. It can be small (say, a few people) and may involve persons outside of the company, such as consultants.

Chatbot: AI software that allows for the communication with people. Examples include Siri, Alexa, and Cortana.

Cloud: This is where you can store and manage data and applications from the Internet, which is known as the public cloud. But there is also the private cloud (where access to the servers are restricted for security purposes) and the hybrid cloud (a combination between private and public clouds).

CoE: See Center of excellence.

Cognitive RPA: This is where AI is used with RPA technologies. One of the common approaches is NLP, which interprets voice commands and written content. By using this type of technology, the RPA system will learn over time (such as how to understand invoices and other business documents).

CRISP-DM Process: Developed by academics, consultants, and experts, this is a 7-step process for managing data in a project.

Customer relationship management (CRM) software : This helps to manage a company’s relationships and interactions with contacts, leads, and customers.

Database: Software that allows for storing and retrieving information, which is critical for any type of application.

Data type : The kind of variable used in a programming language, such as a Boolean, integer, string, or floating point number. Note that data types are often used in building bots.

Deep learning : This is a subset of AI that involves the use of sophisticated neural networks. During the past decade, much of the innovation in the AI field has come from deep learning research.

Enterprise resource planning (ERP) software : This helps to manage the core functions of a company, such as financials, human resources, and the supply chain.

ETL (extraction, transformation, and load ): A kind of data integration that is typically used in a data warehouse.

Explainability: This is where you try to understand the underlying rationale of a deep learning model.

Flowchart: This is a visual representation of the steps in a process. This is also core to an RPA system. A flowchart may also be referred to as a sequence.

Gartner Hype Cycle : A framework for describing the cycles of a new technology. It involves five stages: the technology trigger, peak of inflated expectations, trough of disillusionment, slope of enlightenment, and plateau of productivity.

GPUs (graphics processing units ): These are semiconductors that are for high-speed video games because of the ability to process large amounts of data quickly. But GPUs have also proven to be adept at handling AI applications.

Grey box testing : This is testing of software that includes both white box and black box testing. Essentially, it is a very comprehensive approach.

Hadoop : Open source software that helps with managing Big Data, say, by making it possible to create sophisticated data warehouses.

Hidden layers: The different levels of analysis in a deep learning model.

Hybrid cloud : This is when a company uses both a private and public cloud.

Integer: This is a data type that holds a number without decimal points.

Intelligent automation (IA) : This is where AI is used to enhance an RPA platform.

Key recording: This is a standard feature in an RPA system, which captures a person’s keyboard/mouse movements. These are then embedded in a bot.

Lean: This is a process methodology whose origins go back to Toyota during the 1950s. The focus is on constantly finding ways to improve a system.

Lean Six Sigma : Involves a combination of the two process methodologies. With lean, there is a focus on the elimination of waste and other inefficiencies and Six Sigma helps with data and statistics. A typical approach is to first use lean and then go to Six Sigma.

Log message : This is a comment you can make within a step in an RPA process, which will show up in the orchestrator. Log messages can be very helpful with documenting and debugging.

Loop: A common structure in programming languages that allows for repeating a set of instructions until a condition is met.

Low code: Allows the development of software applications with little hand coding, which often means quicker development.

Macro: This is a series of steps or actions that are automated for a particular application, such as Excel. This is not really RPA, though. RPA instead is much more comprehensive in terms of what can be automated.

Machine learning: This is a subcategory of AI, which uses traditional statistical techniques to help with predictions and insights from processing data.

Metadata : This is data about data – that is, descriptions. For example, a music file can have metadata like the size, length, date of upload, comments, genre, and artist.

Natural language processing (NLP): A subcategory of AI that involves the use of software to understand and manipulate language. Common uses of NLP include Siri and Alexa.

No code: Allows the for the development of software applications by using simple approaches like drag and drop.

Normal distribution: A plot of data that looks like a bell and the midpoint is the mean. A normal distribution (also known as a bell curve) has been shown to be common in nature, such as with weights and heights.

NoSQL system : This is a next-generation database. The information is based on a document model in order to allow for more flexibility with analysis as well as the handling of structured and unstructured data.

OCR (optical character recognition): This is a document scanner that recognizes text, such as from images or even handwriting.

On-premise software : Where a company installs and maintains its own technology within its data center, which allows for more control, security, and privacy. But it can be costly and difficult to customize. This is why more companies have been moving to the cloud.

Open source: This is software that is freely available. Anyone can enhance the code so long as they agree to provide this for everyone without a fee. Open source is also becoming more of a factor for RPA.

Orchestrator : This is a platform that helps to manage the bots, such as with scheduling, tracking, and termination.

Private cloud : This is a cloud system in which a company has its own data center.

Process mining : Sophisticated software – which leverages Big Data and algorithms – to map, monitor, and improve company processes. This is becoming an increasingly important part of RPA implementations.

Public cloud : This is when a company will store and maintain its software and databases on another cloud platform, such as Amazon Web services or Azure.

Python: A computer language that has become the standard in developing AI models.

Reinforcement learning : This is a type of algorithm that is trained by rewarding accurate predictions and punishing for those that are not.

Relational database : A database, whose roots go back to the 1970s, that creates relationships among tables of data and has a scripting language, called SQL. Relational databases are the most common within corporate environments.

Robotic process automation (RPA): A software platform that allows you to automate specific business tasks, such as moving data and making keyboard inputs. Often, this is done with applications like a CRM or ERP.

RPA champion : This is the evangelist for the project. He or she will focus on such things as creating videos, workshops, and blog posts.

RPA developer : This person designs, deploys, and monitors the bots.

RPA infrastructure engineer : This person is responsible for managing the server installation.

RPA solution architect: This is someone who assists with the early stages of a project, such as with the design of the core technology foundation.

RPA sponsor: This is a person from the business side of the organization that provides support for the implementation.

RPA supervisor: This person manages the team players of the project.

Scope: This is the part of a program where a variable can be used.

Screen scraping: Involves the transferring of data from one application to another. This is one of the features of an RPA system.

Script: This is a set of programming instructions, such as for the creation of a bot.

Semi-structured data: This is a blend of structured and unstructured data, which usually includes internal tags for categorization.

Sequence: This is a visual of the different steps of a bot in an RPA process. It is usually from top to down and has different icons to note things like decisions and so on. A sequence may also be referred to as a flowchart.

Six Sigma : This is a process methodology that was developed in the 1980s by Motorola. Six Sigma relies heavily on statistical techniques to help reduce defects in a system.

SME: See Subject matter expert.

Standard deviation: This measures the average distance from the mean, which gives a sense of the variation in the data.

Strong AI: This is true AI, in which a machine is able to engage in humanlike abilities like open-ended discussions. However, current technology is far from achieving this.

Structured data : This is data that has a certain format (social security number, address, point of sale information) that can be stored in a relational database or spreadsheet.

Studio designer: This is the part of an RPA software platform where you can design bots. Often this involves light code and drag and drop.

Subject matter expert (SME): This is a person within an organization that has expertise with certain processes.

Supervised learning: This is a type of algorithm that analyzes labeled data. Supervised learning is the most common in AI.

Test data: After a model is created, you use this type of data to evaluate the results.

Training data: This is the data used for creating a model, such as for machine learning or deep learning.

Unassisted RPA (or unattended RPA): Where the software completely automates a process or task.

Unstructured data: This is data that is unformatted, such as images, videos, and audio files.

Unsupervised learning: This is a type of algorithm that uses unlabeled learning. This process often involves looking for clustering of the data.

Variable: This is a container that holds data that can be manipulated in computer code.

Virtual assistant : An AI device that helps a person with his or her daily activities.

Weak AI : This is where AI is used for a particular use case, such as with Amazon.com’s Alexa.

White box testing: This is testing of a software’s source code.

Index

ABBYY

Algorithms

reinforcement learning

semi-supervised learning

supervised learning

unsupervised learning

American Institute of Certified Public Accountants (AICPA)

AntWorks

Application Performance Monitoring (APM)

Application programming interfaces (API)

Artificial general intelligence (AGI)

Artificial intelligence (AI)

components

conquer disease

contract management

corporate e-mail inboxes

deep learning

digital customer service platform

insurance claims

invoice automation

issues

bias

black box

brain

causation

common sense

comprehension

conceptual thinking

static

machine learning

NLP

structured data

unstructured data

AssistEdge platform

Attended automation

Automation Anywhere

benefits

integration and AI

RPA career

scaling RPA

Attended bots

Attended RPA

Automate

alerts

customer cancellation process

data migration

data updates

description

documentation

factors

tracking

Automated testing

Automation Anywhere

Blue Prism

SeeBlue Prism

Bot Store

cloud computing

cloud platform

comprehensive training program

customer entities

Enterprise A2019

IQ Bot

iterations, platform

mobile app

small-and medium-sized business market

validations

vision

Automation of consumer-facing activities

Automation strategy

Automotive industry

Autonomous RPA

AWS

Benefits, RPA

compliance

customer service

data quality

digital transformation

employee satisfaction

impact of small improvements

relative ease of implementation

ROI

scalability

Bias

Big Data

definition

issues

structured and unstructured

variety

velocity

volume

Big data and business analytics (BDA)

Black box testing

Blue Prism

AI Research Labs

cloud-based RPA deployments

connected RPA

development

DTE Energy

rigorous security practices

security

Boolean

Bot

Bot development

SeeUiPath Studio

activities

best practices

flowcharts and sequences

log message activity

UiPath installation

Bot Store

Bot support

Brainstorming

Breakpoint

Breedvs. end-to-end

Business analyst

Business continuity plan

Business process automation (BPA)

Business process management (BPM)

Business process outsourcing (BPO)

Cascading style sheets (CSS)

Categorical data

Celonis

Center of excellence (CoE)

advantages

business analyst

communication

deploy, organization

developer

high-level definition

implementing

Intuit (case study)

investments of time and money

operating models

performance

RPA solution architect

RPA supervisor

RPA system, implementation

setting up, RPA project

team forming

Centralized model

Change management

factors

Kotter’s 8-step strategy

anchoring new approaches

change vision

communicating the vision

consolidating gains

empower broad-based action

generating short-term wins

guiding coalition, building

sense of urgency

Kotter’s methodology

myriad of frameworks

store design and pricing

Chartered Institute of Management Accountants (CIMA)

Chatbots

Cloud computing

Cloud-native applications

CloudStorm

Cognitive automation

Coherent digital process automation

Common UiPath functions

Communication

Comprehension

Computer vision

Conduent

Consultants

Accenture

Cognizant

Conduent

Deloitte

DXC Technology

Genpact

HCL Technologies

Hexaware

Infosys

KPMG

Mphasis

PwC

TCS

Consulting firm

Consulting success, case studies

Consumer willingness, automation

Convolutional neural networks (CNNs)

Costs

Critical-to-quality (CTQ)

Cross-industry standard process for data mining (CRISP-DM)

Customer relationship management (CRM)

Customer service representatives (CSRs)

CyberArk

Cybersecurity

Danaher business system (DBS)

Databases

Data migration

Data preparation

binning

consistency

duplication

global data

merging

one-hot encoding

outliers

staleness

validation rules

Data privacy laws

Data process, CRISP-DM process

business understanding

data preparation

data understanding

deployment

modelling and evaluation

Data type

Data updates

Decentralized model

Deep learning

Defects per million opportunities (DPOM)

Defects per opportunity (DPO)

Deloitte

Demand management

Deployment process

Developer

DevOps

Digital Exchange (DX)

Digital process automation (DPA)

Digital transformation

Direct follows graphs (DFGs)

DoWhile Loop

Duplication

DXC technology

Ecosystem

EdgeVerve

End-to-end intelligent automation

Enterprise resource planning (ERP)

Enterprise scale

Enterprise software system

Ernst & Young (E&Y)

Extraction, transformation, and load (ETL)

Federated model

Flowcharts

Fluxicon

For Each loop

Free software

Full-time equivalent employees (FTEs)

Future, RPA

Chatbots

consolidation and IPOs

Hype Factor

Microsoft

privacy and ethics

SaaS and Open Source

Gartner Hype Cycle

Generative adversarial networks (GANs)

Genpact

Google Cloud

Governance

Graphics processing units (GPUs)

Grey box testing

Hadoop

HCL Technologies

Hexaware

Hybrid cloud

Hype Cycle

I, J

IBM Watson

IF/THEN/ELSE conditional

Infosys

Infrastructure engineer

Integrated Automation Platform (IAP)

Intellibot

Intelligence automation (IA)

Intelligent process automation (IPA)

Internet of Things (IoT)

IQ Bot

Kanban

Kofax

Kotter’s methodology

Kryon systems

Kubernetes

Launch-and-forget system

Lean

communication

DBS engine

flow

fuzzy

perfection

pull

value

value stream

Lean Six Sigma

lean implementation

statistics and data techniques

wastes

defects

inventory

motion

overprocessing

overproduction

transportation

waiting

Log message

Loops

Machine learning (ML) technology

Meta data

Microsoft

Microsoft’s Azure

Monitoring

Natural language processing (NLP)

Nearshore

Neptune Intelligence Computer Engineering (NICE)

Net promoter score (NPS)

Next-generation technologies

Nintex

Nonhuman RPA access

NoSQL system

Offshore

On-premise RPA system

On-premise software

On-premise technology

Onshore

OpenRPA

Open Source Software

advantage

business model

description

drawbacks

features

OpenRPA

Orchestra

Robocorp

Robot Framework

TagUI

UI.Vision

OpenSpan

Operating model

Optical character recognition (OCR)

Orchestra

Organizational change management

PEGA

CSR market

OpenSpan

Pega Infinity

real-time AI

robotic desktop automation

robotic process automation

robot manager

RPA modules

visual models

Pega Infinity

People enablement

Per-bot pricing

Personally identifiable information (PII)

Petri nets

Planning

high-level objectives and goals

preliminaries

RPA consulting

RPA implementation

chaos and failure

E&Y

PostgreSQL

Private cloud

Process automation identification and elaboration

Process definition documents (PDD)

ProcessGold

Process mining

ABBYY

analytics

Celonis

conformance

definition

DevOps

discovery

ERP migration

event data

event log

factors

Fluxicon

future

high-level view

internal audit

IoT

origins

perception

Petri nets

product development

ProM

Signavio

sophisticated Big Data techniques and algorithms

Task Force

ProM

Public cloud

Quality assurance (QA)

Recurrent neural networks (RNNs)

Red Hat

Reinforcement learning

Relational database

Representational state transfer (REST)

Resources, RPA

Return on investment (ROI)

Robocorp

Robot Framework

Robotic process automation (RPA)

actions/tasks

attended

bots

BPA

BPM

BPO

core determination

definition

evolution, RPA market

history

inherent limitations and complexities

cost of ownership

enterprise scale

expectations

preparation

security

Technical Debt

virtualized environments

IPA

Kryon Systems

lean and Six Sigma, applying

macro

PEGA

platforms

ROI

software robot

technology

UiPath

unattended

use cases

Robotics-as-a-service (RaaS)

RPA

champion

change manager

developer

infrastructure engineer

supervisor

Salesforce.com

SanityBot

SAP Contextor

Scalable automation execution engine

Scaling

challenges for global organizations

CoE

planning

ROI

strategic priority

Scrum

Security

Semi-structured data

Service-level agreement (SLA)

Service support

Servicetrace

Signavio

Six Sigma

approaches, apply

chart of

complexity

DMAIC, workflow

effectiveness

levels of proficiency

quality program

roles

standard deviations, mean

statistical approaches for manufacturing

Softomotive

Software-as-a-Service (SaaS)

Software bots and automation

Solution architect

StaffBot

Structured data

Structured query language (SQL)

Subject matter experts (SMEs)

Supervised learning

Switch statement

TagUI

Task Force

Technical definition documents (TDD)

Technology strategy

Test Automation (TA)

Testing

Time-series data

Time tracking

Total quality management (TQM)

Training data

UI automation

UiPath

aggressive approach to product development

AI Fabric

Apps

connect enterprise

debug system

enterprises

evaluation, top research firms and third-party organizations

features, UiPath platform

integrations

security

UiPath academy

frontline and backline operations

insights

Orchestrator

platform, additions

scale

StepShot

UiPath Studio

activities

debug

DoWhile Loop

For Each loop

IF/THEN/ELSE conditional

installation

activities tab

community edition

design screen

enterprise platform

initial screen

options

pop-up menu

portal screen

sequence/activit

log message activity

loops

Switch statement

variable, creation

While Loop

UiPath StudioX

UI.Vision

Unattended RPA

Unstructured data

Unsupervised learning

Use cases

User events

Variables

Vendor evaluation

breedvs. end-to-end

costs

design

ecosystem

full-on support

funding

industry expertise

minimum capabilities

next-generation technologies

relationship

security, monitoring, and deployment

tedious and time-consuming

third parties

thought leadership and vision

training and education

user

Vendors

AntWorks

automation anywhere

SeeAutomation Anywhere

EdgeVerve, ,

Intellibot

Kofax

Kryon

NICE

Nintex

PEGA

SeePEGA

SAP

Servicetrace

Softomotive

UiPath

SeeUiPath

Verint

WorkFusion

Verint

Vertical-specific companies

Virtual assistant

Virtual-based RPA consulting

Virtual workers (robots)

Virtual workforce

Visualization

W, X, Y, Z

Waterfall

Weak AI

Web technology

White box testing

Workflow automation tool

Workforce

Workforce optimization suite

WorkFusion

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Back Matter