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THE GOOD, THE
BAD………..
THE DATA
Artificial Intelligence and Robotic Process Automation
Presentation by Ronan Fitzpatrick
March 2019
CEOs need to make better use of data
analytics as a means to identify
efficiencies and opportunities. Using
their data in the right way will also
enable them to take advantage of the
upcoming Artificial Intelligence
revolution. But in order to be confident
that their organisation is fit for the future
they must first solve the key skills
challenge.
2PwC
Digitisation encompasses ‘the process of moving from
analog to digital form’.2 Digitisation is the only way to meet
the greater demand for real- time fulfilment, 24/7
availability, a personalised consumer experience, greater
accuracy, predictive data, faster processing and improved
customer identity management. The digital landscape
spans the use of channels such as websites, social
media, mobile apps and so on to enable a more digitised,
interactive and improved experience. Digitised work is
also quicker, cheaper andmore reliable than manually
processed work, regardless of whether it is insourced,
outsourced, or executed on a perfect manualprocess.
The ultimate goal is to digitise the majority of a
company’s processes, only relying on people where
Digitisation is a logical and necessary next step
PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Organisations both globally and in
Ireland are clear they know the
information they need in order to make
strategic decisions for their ongoing
business success. But, many are
struggling with the comprehensiveness
of that data they receive.
A striking finding from the report is the
significant information gap that exists
between the data CEOs need, and
what they get
Irish organisations lag global counterparts on leveraging data
%3
Irish CEOs said the data about their customers’
preferences and needs was critical or important
for long-term decision making
PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Bridge the gap:
limitations in the data that enables
businesses to perform financial
forecasting, data about their brand and
reputation, and imminent business
risks. Interestingly, there was also a
scarcity of data about how the latest
technological trends will disrupt their
industries,
Irish organisations lag global counterparts on leveraging data
%4
said the data they receive about their
Customers was comprehensive.
PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Build your data foundation
When you are using data to drive
organisational growth, there’s no
room for error. You need to develop a
data framework, build the strategy,
optimise your infrastructure,
processes and systems, and create
the right culture internally to become
a data-driven organisation.
Data & Analytics priorities
5
Apply advanced analytics
You have the right data architecture
and can rely on your data quality.
Now what do you do with it? That’s
where predictive analytics comes in.
It uses your data to give you the
potential to act, not react. Now you
can start filtering the signal from the
noise and look ahead with
confidence.
Improve business performance
Use new data-based insights to
pinpoint opportunities in your industry
to work smarter, focus and prioritise.
Then make change stick, by
delivering data and performance
measures to the right people at the
right time - and set up the right
incentives for people to act on them.
Activating the
AI revolution
64% of Irish CEOs believe that Artificial Intelligence (AI)
will significantly change the way they do business in the
next five years
PwC
PwC DAMA; The Good, The Bad and the Data March 2019
51%
of Irish CEOs have no plans to
pursue any AI initiatives at the
moment
AI Planning lags significantly behind our global peers
7
PwC
PwC DAMA; The Good, The Bad and the Data March 2019
8
Intelligent Automation
PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Automation roadmaps combine more than one technology
10
3
• Documents scanning and verification
• Validation and authentication of individuals
• Global search and screening
engines that provide relevant and
up to date customer information
• Workflow tool enabling
an efficient straight through process
• Data storage
• Self learning systems processing
unstructured data
• Automation of manual activities
using Robotics solutions
Case workflow tracker
and repository Biometric ID verification
Artificial Intelligence
Search & screening
1 2
4
6
Robotic Process
Automation • Standardisation and automated
analysis/ validation of files
Optical Character
Recognition (OCR) tool
5
7 Conversational Interfaces
• a computer program designed to simulate human
conversation, or chat, with a human user.
A simple system to demonstrate the functionality of
a small set of principles, used to prove out the
feasibility of a process use case.
Typically does not involve interfacing with
production systems and has not yet gotten to a
license discussion.
Implementation with end-usage
scenarios, of Production ready quality
but on a smaller scale.
Typically would interface with
production systems and has
secured appropriate licenses. May
or may not drive need for control
room/ orchestration. Typically run
as an attended bot.
Addresses exception handling for
agreed scope.
An early version of a solution with
nearly full functionality, that can be
further tested and refined.
Typically does not involve
interfacing with production
systems and has not yet gotten to a
license discussion.
Takes the “happy path” of the
process and not all error handling,
business referrals.
Deployment of the end solution based on
knowledge and feedback gained from the
pilot.
Interfaces with production systems and
has secured appropriate licenses.
As scale is added drives need for control
room/ orchestration conversations.
Can either run as attended BOT or
scheduled via Orchestrator
Addresses exception handling.
Requires Architecture and further
maturation of process controls, reporting,
error handling.
Agreement should be reached on further
scaling and support processes, who will
be controller for production processes. Is
there a Governance, COE framework
Scaling and establishing a broader
automation agenda within can happen in
parallel
Automation Delivery
PoC
Pilot
Production
Our delivery teams can work through different stages
to Production. The outputs vary in terms of maturity
and discussion is required to ensure expectations
match.
11
PoV
PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Sample growth runway
12
ClientPwC Client Client Client Client Client
Wave 2
‘Do One’
Wave 3+
‘Lead One’
PwC Led
• Client project team identified and trained in approach
• Client project team is coached by the PwC team 0n
delivery
Client led with PwC Support
• Wave 1 Client project team take on coaching of
middle management
• Additional Client project teams identified and coach at team
level
Lead
Support
PwC
Wave 1 (Pilots)
‘See One’
Client
PwC
Client Client
Completely Client led
• Completely led by Client project team
• Quality review and maturity assessment conducted by PwC
Wave 3 responsibilities Time
PwC coach External quality review and maturity
assessment
25%
Client change
agent
Drives change across business teams 100%
Client team
manager
Leads the Client team to drive
implementation
100%
Client team
staff
Implement learnings from Wave 1 and 2
to engage with stakeholders and drive
programme delivery
100%
Wave 2 responsibilities Time
PwC coach Provides support as required to the
Client project team
50%
Client change
agent
Drives change across business teams
with PwC support
100%
Client team
manager
Leads the Client team to drive
implementation with PwC support
100%
Client team
staff
Implement learnings from Wave 1 to
engage with stakeholders and drive
programme delivery
100%
Wave 1 responsibilities Time
PwC coach Leads program by interfacing with the
Client project team
100%
Client change
agent
Shadows implementation to grow
in-house capability
65-80%
Client team
manager
Works directly with PwC to deliver tools 45-60%
Client team
staff
Experience programme approach and
work with project team to embed in
teams
10-25%
PwC
PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Some Process Identification learnings
13
1. Focus on what “should” be automated, not what “can” be automated –
maintain a holistic approach focusing first on eliminating waste, re-
engineering processes, and considering use of existing technology.
2. Plug into continuous improvement initiatives – leverage RPA in
conjunction with broader continuous improvement initiatives as opposed to
only thinking about it as a stand-alone project
3. Consider End-to-End processes – avoid focusing narrowly on specific
activities to automate and consider the End-to-End processes
4. Look for value beyond efficiencies – opportunities may be prioritized
based on controls, scalability, or other non-cost factors
5. Proactively manage workforce implications – think about change
management up front
Traditionally organisations think
vertically, delivering change
and operating in isolation.
We see best benefit when you
join the dots by thinking
horizontally and working cross-
functionally.
PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Accelerators
14
www.pwc.ie/digital
Thank You
ronan.fitzpatrick@pwc.com
+353871888064
PwC
07/02/2019
16
1
Define and develop a future target state for an
organisation to succeed in a digital age;
Disruption and Innovation, Strategy, People,
Agility, Target Op. Model /TOM, Collaboration.
2
Transform Customer Contact/ interactions to
optimise engagement and experience across
all channels; reduce cost, drive revenue,
service and relationship.
3
Drive efficiencies by digitisation from the front
to back-office; Finance, HR, and Human
interactions, Robotic Automation and
message /voice / chatbot leadership.
Digital Evolution:
Strategy and Innovation
Methodology
Digital Experience:
Data Driven Customer
Transformation
Digital Enterprise:
Developing the Workforce
of the future
Primary
Offerings
Strategy, TOM and Transformation
Innovation, BXT and Design Thinking
Ideation, Portfolio and Program
Prioritisation
Partnering with 3rd party Vendors
Enablers
Architecture for a Digital Age (including cloud)
Digital Maturity and Fitness Assessments
1
2
3
4
13
14
Customer Experience Design
Customer Experience Enablement
Conversion and Funnel Optimisation
Digital Marketing Services
5
6
7
8
Intelligent Automation (RPA, SPA, AI) &
Conversational Agents
Contract Digitisation
Unified Collaboration and Communication
(Teams, Workplace, Hangouts)
HR, CRM, eCommerce, CMS, Spec and
Select
9
10
11
12
Cyber Security & Forensics for a Digital Age15
Behavioural & Customer Analytics & Visualisation (Qlik, Tableau, Google Studio)16
17 Realise, BXT, Digital Fitness UX, CRM, MarTech & AdTech expertise Seal Contract Digitisation, RPA, Chatbots
Value
Statement

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THE GOOD, THE BAD, THE DATA - Artificial Intelligence and Robotic Process Automation - DAMA March 2019 Event

  • 1. THE GOOD, THE BAD……….. THE DATA Artificial Intelligence and Robotic Process Automation Presentation by Ronan Fitzpatrick March 2019
  • 2. CEOs need to make better use of data analytics as a means to identify efficiencies and opportunities. Using their data in the right way will also enable them to take advantage of the upcoming Artificial Intelligence revolution. But in order to be confident that their organisation is fit for the future they must first solve the key skills challenge. 2PwC Digitisation encompasses ‘the process of moving from analog to digital form’.2 Digitisation is the only way to meet the greater demand for real- time fulfilment, 24/7 availability, a personalised consumer experience, greater accuracy, predictive data, faster processing and improved customer identity management. The digital landscape spans the use of channels such as websites, social media, mobile apps and so on to enable a more digitised, interactive and improved experience. Digitised work is also quicker, cheaper andmore reliable than manually processed work, regardless of whether it is insourced, outsourced, or executed on a perfect manualprocess. The ultimate goal is to digitise the majority of a company’s processes, only relying on people where Digitisation is a logical and necessary next step
  • 3. PwC PwC DAMA; The Good, The Bad and the Data March 2019 Organisations both globally and in Ireland are clear they know the information they need in order to make strategic decisions for their ongoing business success. But, many are struggling with the comprehensiveness of that data they receive. A striking finding from the report is the significant information gap that exists between the data CEOs need, and what they get Irish organisations lag global counterparts on leveraging data %3 Irish CEOs said the data about their customers’ preferences and needs was critical or important for long-term decision making
  • 4. PwC PwC DAMA; The Good, The Bad and the Data March 2019 Bridge the gap: limitations in the data that enables businesses to perform financial forecasting, data about their brand and reputation, and imminent business risks. Interestingly, there was also a scarcity of data about how the latest technological trends will disrupt their industries, Irish organisations lag global counterparts on leveraging data %4 said the data they receive about their Customers was comprehensive.
  • 5. PwC PwC DAMA; The Good, The Bad and the Data March 2019 Build your data foundation When you are using data to drive organisational growth, there’s no room for error. You need to develop a data framework, build the strategy, optimise your infrastructure, processes and systems, and create the right culture internally to become a data-driven organisation. Data & Analytics priorities 5 Apply advanced analytics You have the right data architecture and can rely on your data quality. Now what do you do with it? That’s where predictive analytics comes in. It uses your data to give you the potential to act, not react. Now you can start filtering the signal from the noise and look ahead with confidence. Improve business performance Use new data-based insights to pinpoint opportunities in your industry to work smarter, focus and prioritise. Then make change stick, by delivering data and performance measures to the right people at the right time - and set up the right incentives for people to act on them.
  • 6. Activating the AI revolution 64% of Irish CEOs believe that Artificial Intelligence (AI) will significantly change the way they do business in the next five years
  • 7. PwC PwC DAMA; The Good, The Bad and the Data March 2019 51% of Irish CEOs have no plans to pursue any AI initiatives at the moment AI Planning lags significantly behind our global peers 7
  • 8. PwC PwC DAMA; The Good, The Bad and the Data March 2019 8
  • 10. PwC PwC DAMA; The Good, The Bad and the Data March 2019 Automation roadmaps combine more than one technology 10 3 • Documents scanning and verification • Validation and authentication of individuals • Global search and screening engines that provide relevant and up to date customer information • Workflow tool enabling an efficient straight through process • Data storage • Self learning systems processing unstructured data • Automation of manual activities using Robotics solutions Case workflow tracker and repository Biometric ID verification Artificial Intelligence Search & screening 1 2 4 6 Robotic Process Automation • Standardisation and automated analysis/ validation of files Optical Character Recognition (OCR) tool 5 7 Conversational Interfaces • a computer program designed to simulate human conversation, or chat, with a human user.
  • 11. A simple system to demonstrate the functionality of a small set of principles, used to prove out the feasibility of a process use case. Typically does not involve interfacing with production systems and has not yet gotten to a license discussion. Implementation with end-usage scenarios, of Production ready quality but on a smaller scale. Typically would interface with production systems and has secured appropriate licenses. May or may not drive need for control room/ orchestration. Typically run as an attended bot. Addresses exception handling for agreed scope. An early version of a solution with nearly full functionality, that can be further tested and refined. Typically does not involve interfacing with production systems and has not yet gotten to a license discussion. Takes the “happy path” of the process and not all error handling, business referrals. Deployment of the end solution based on knowledge and feedback gained from the pilot. Interfaces with production systems and has secured appropriate licenses. As scale is added drives need for control room/ orchestration conversations. Can either run as attended BOT or scheduled via Orchestrator Addresses exception handling. Requires Architecture and further maturation of process controls, reporting, error handling. Agreement should be reached on further scaling and support processes, who will be controller for production processes. Is there a Governance, COE framework Scaling and establishing a broader automation agenda within can happen in parallel Automation Delivery PoC Pilot Production Our delivery teams can work through different stages to Production. The outputs vary in terms of maturity and discussion is required to ensure expectations match. 11 PoV
  • 12. PwC PwC DAMA; The Good, The Bad and the Data March 2019 Sample growth runway 12 ClientPwC Client Client Client Client Client Wave 2 ‘Do One’ Wave 3+ ‘Lead One’ PwC Led • Client project team identified and trained in approach • Client project team is coached by the PwC team 0n delivery Client led with PwC Support • Wave 1 Client project team take on coaching of middle management • Additional Client project teams identified and coach at team level Lead Support PwC Wave 1 (Pilots) ‘See One’ Client PwC Client Client Completely Client led • Completely led by Client project team • Quality review and maturity assessment conducted by PwC Wave 3 responsibilities Time PwC coach External quality review and maturity assessment 25% Client change agent Drives change across business teams 100% Client team manager Leads the Client team to drive implementation 100% Client team staff Implement learnings from Wave 1 and 2 to engage with stakeholders and drive programme delivery 100% Wave 2 responsibilities Time PwC coach Provides support as required to the Client project team 50% Client change agent Drives change across business teams with PwC support 100% Client team manager Leads the Client team to drive implementation with PwC support 100% Client team staff Implement learnings from Wave 1 to engage with stakeholders and drive programme delivery 100% Wave 1 responsibilities Time PwC coach Leads program by interfacing with the Client project team 100% Client change agent Shadows implementation to grow in-house capability 65-80% Client team manager Works directly with PwC to deliver tools 45-60% Client team staff Experience programme approach and work with project team to embed in teams 10-25% PwC
  • 13. PwC PwC DAMA; The Good, The Bad and the Data March 2019 Some Process Identification learnings 13 1. Focus on what “should” be automated, not what “can” be automated – maintain a holistic approach focusing first on eliminating waste, re- engineering processes, and considering use of existing technology. 2. Plug into continuous improvement initiatives – leverage RPA in conjunction with broader continuous improvement initiatives as opposed to only thinking about it as a stand-alone project 3. Consider End-to-End processes – avoid focusing narrowly on specific activities to automate and consider the End-to-End processes 4. Look for value beyond efficiencies – opportunities may be prioritized based on controls, scalability, or other non-cost factors 5. Proactively manage workforce implications – think about change management up front Traditionally organisations think vertically, delivering change and operating in isolation. We see best benefit when you join the dots by thinking horizontally and working cross- functionally.
  • 14. PwC PwC DAMA; The Good, The Bad and the Data March 2019 Accelerators 14
  • 16. PwC 07/02/2019 16 1 Define and develop a future target state for an organisation to succeed in a digital age; Disruption and Innovation, Strategy, People, Agility, Target Op. Model /TOM, Collaboration. 2 Transform Customer Contact/ interactions to optimise engagement and experience across all channels; reduce cost, drive revenue, service and relationship. 3 Drive efficiencies by digitisation from the front to back-office; Finance, HR, and Human interactions, Robotic Automation and message /voice / chatbot leadership. Digital Evolution: Strategy and Innovation Methodology Digital Experience: Data Driven Customer Transformation Digital Enterprise: Developing the Workforce of the future Primary Offerings Strategy, TOM and Transformation Innovation, BXT and Design Thinking Ideation, Portfolio and Program Prioritisation Partnering with 3rd party Vendors Enablers Architecture for a Digital Age (including cloud) Digital Maturity and Fitness Assessments 1 2 3 4 13 14 Customer Experience Design Customer Experience Enablement Conversion and Funnel Optimisation Digital Marketing Services 5 6 7 8 Intelligent Automation (RPA, SPA, AI) & Conversational Agents Contract Digitisation Unified Collaboration and Communication (Teams, Workplace, Hangouts) HR, CRM, eCommerce, CMS, Spec and Select 9 10 11 12 Cyber Security & Forensics for a Digital Age15 Behavioural & Customer Analytics & Visualisation (Qlik, Tableau, Google Studio)16 17 Realise, BXT, Digital Fitness UX, CRM, MarTech & AdTech expertise Seal Contract Digitisation, RPA, Chatbots Value Statement