awareness session - cfa institute...awareness session –robotics ©2017 kpmg international...

Awareness SessionRobotics

18 April 2018

2

Awareness session – Robotics

©2017 KPMG International Cooperative ("KPMG International"), a Swiss entity. Member firms of the KPMG network of independent firms are affiliated with KPMG International. KPMG International

provides no services to clients. No member firm has any authority to obligate or bind KPMG International or any other member firm vis-à-vis third parties, nor does KPMG International have any such

authority to obligate or bind any member firm. All rights reserved.

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Three activity spheres within the current business function

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Commodore 64

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Time

Pro

du

cti

vit

y

yy

1 100 year

2

Mechanic systems

Information systems

Cloud

4 5 year

Cognitivesystems

5

35 year

3

Internet systems

15 year

Cognitive automation will enable next wave of automation

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AdvancementsinProcessAutomation

Advancements in Machine Intelligence

Human labour

Robotics (Enhanced

Process Automation)

Autonomic/Cognitive

Robotics

Basic Process

Automation

Two dominant routes leading to Cognitive Robotics

Rules

mapping

Sreen

scraping

Processing of Unstructured Data and Base Knowledge

Workflow

Adaptivealteration

Natural language processing

“Big Data” Analytics

Artificial Intelligence

MachineLearning

Large-scaleProcessing

Adaptivealteration

NaturalLanguageProcessing

“Big Data”Analytics

Large-scaleProcessing

MachineLearning

ArtificialIntelligence

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The influence of Robotics on the business function

Business

Partner

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Shifting human workforce to value-adding activities

Cognitive

Robotics

Process

Robotics

Business Function 2016

Business Function 2020

Business Partner

Functional Business

Transactional Business

Business Partner

Functional Business

Transactional Business

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Po

int-

to-P

oin

tG

en

eri

c

Process robotics Cognitive roboticsEnhanced & Machine Learning

PtP

SDA

RPA

Cognitive

ERA

Robotics solution overview

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Process Robotics key ingredients

Work QueuesProcess mapping Object studio Control room

The work queue holds the

backlog for each of your

defined processes

Visual representation of

tasks and steps

performed by robot

A library of reusable

objects that can be used

when performing

processes

Manage your robots from

the control room

Map your processes

using level 4 detailed

working instructions

Most tooling allows the

process owner to monitor

the processes (e.g. how

often does a specific

exception occur?)

Process mapping speed

increases as more

objects have been

defined

Highlights specific

elements of

SAP/Oracle/Websites/

Excel…

Keep track of your

backlog

Decide which processes

to run based on the size

of the work queue

Decide which processes

to run

Assign processes

manually, or

automatically (when the

work queue >100 items,

every night at 03.00h or

when a file is saved at a

specific folder location)

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Demo RPA – BleuPrism

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Demo process example

Open Mailbox &

Read Structured Invoice Request

Open SAP

Use data from e-mail to make

Intercompany booking

Generate invoice

Store outcomes &

Send E-mail to requestor

Open Mailbox &

Read Structured Invoice Request

Open SAP

Use data from e-mail to make

Intercompany booking

Generate invoice

Store outcomes &

Send E-mail to requestor

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Benefits

Accuracy

Efficiency

Process

ImprovementQuality

Costs

Governance

Control

Compliance

Benefits of Robotics

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6Demo example of IPsoft Amelia

How does IPsoft Amelia work? Implementation of IPsoft Amelia

at public sector company

(Enfield Council London)

Demo 1 Demo 2

https://www.youtube.com/watch?v=M7X0i53nG0s

https://www.youtube.com/watch?v=M7X0i53nG0s

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Awareness Workshop

■ Build the Finance Robotics solution for each use case

■ Enable and train users in Finance Robotics tool for adaptation and implementation purposes

■ Run Finance Robotics solution once steady-state is achieved

■ Roll-out to other identified target processes

Process Workshop

■ Understand the impact of Finance Robotics on the business

■ Raise awareness

■ Usually C-level audience

Proof of Concept

■ Understand business target areas

■ Identify potential (E2E) target processes for Finance Robotics

■ Usually processowner audience

Pilot

■ Perform vendor selection process (including long-list, short-list and demonstrations)

■ Implement Finance Robotics for the ‘happy flow’ of the target process(es) to demonstrate the product feasibility

Implementation & Further Roll-out

■ Use design thinking and rapid prototyping to finalize detailed solution architecture

■ Integrate with enterprise systems

■ Configure and teach software robots

■ Test and deploy solution

2 hours 1 week2 weeks per

POC process

Depending

on

scope

Depending

on

scope

A typical Process Robotics journey

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Robotics implementation framework

Organisational

Structure and

Governance

Process

delivery and

deployment

Technology

Vendor

Management

Performance

and Risk

Management

People and

Competences

Robotics

1

2

35

4

6

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Criteria

Proces Robotics criteria

Evaluatie van doelprocessen voor RoboticsProces Robotics kan werk sneller en efficiënter uitvoeren dan de huidige handmatige methode. Als we processen evalueren voor Proces Robotics, dan identificeren we transactionele activiteiten die voldoen aan de volgende criteria:

Hoog volumeTransactioneelRule Based HerhaalbaarGestructureerde

Data

Criteria

Geavanceerde / Cognitieve Robotics criteria

Geavanceerde / Cognitieve Robotics kan gebruikt worden om taken die gespecialiseerde menselijke kennis nodig hebben te transformeren. Als we processen evalueren voor Geavanceerde / Cognitieve Robotics, dan identificeren we activiteiten die voldoen aan de volgende criteria:

Ongestructureerde

Data

Complexe

ProcessenGedragspatronen

Meerdere

Databronnen

Grote Data

Sets

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Earlier experience with project implementationsOur findings from previous Finance Robotics project implementations can be clustered into five themes:

Finance Robotics implementation is not an IT project

Detailed working instructions and specific training materials are required

After cost savings, quality improvement is a key advantage of implementing

Finance Robotics

Support functions like IT, HR, Legal and Tax must be involved with the Finance

Robotics Implementation

Change management is a critical success factor

1

2

3

4

5

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How tangible isRobotics foryou?

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The Digital Finance Stack requires a selection of solutionsImpact of disruptive technologies

Data management & data mining

iBPMS

System backbone: Cloud ERP and

EPM

Robotic process automation

Cognitive

Digital analytics and delivery

Natural language processing

Machine learning

— Use of behaviour patterns for cognitive hypothesis

generation / advanced predictive analytics

— Support the best possible business decision and

transaction

— Use of algorithms that iteratively learn from structured and

unstructured data

— Generation of data-driven predictions or decisions

— Use of structured data within well defined parameters

— Use of technologies like screen scraping, rules

engine and process orchestration

— Autonomous completion of transactional and rule-based

tasks

— System backbone is the basis of the digital finance stack

— Structured and unstructured data with an increasing variety and

complexity

— Management of flexible data structures coming from

heterogeneous data sources without a predetermined

scheme

— Process mining technology provides insights into

processes

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KPMG Digital Chain

System backbone

Big Data analytics

BPM RPA

Machine Learning

Cognitive

ERP / DWHDocuments and

emails

Machines

Devices / IoT

Social Media / Web

Data ingestion and

integrationProcess mining

Rules

engine

Screen

scraping

Adaptive

alteration

Artificial

intelligence

Natural lang.

process.

• Internal and external data

sources

• Structured and unstructured data with an

increasing variety and complexity

• Management of flexible data structures coming from

heterogeneous data sources without a predetermined

scheme

• Use of structured data within well defined parameters

• Autonomous completion of transactional and rule-based tasks

• Use of algorithms that iteratively learn from

structured and unstructured data

• Generation of data-driven predictions or

decisions

• Use of behaviour patterns for cognitive hypothesis generation / advanced

predictive analytics

• Support the best possible business decision and

transaction

Advanced Search

Process Orchestration

Learning Algorithms

What is Appian?

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Robotics focuses on the long-tail of automationIT Resourced and

DeliveredBusiness Resourced

Pro

cess

Val

ue

System Coverage

Enterprise IT

Business Ownership

• Procedural Automation• Previously Uneconomic Projects• Short Term Regulatory Requirements• Competitive or Rapid Response

Thank youContactJoris Juttmann

Robotics & Process Excellence

Director KPMG Advisory N.V.

Tel: +31 20 656 7916

Mob: +31 6 52 75 59 50

[email protected]