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Part 1
RPA, AI, and Algorithms
Super-Charged Game Changers
SIG Resource Center
Thought Leaders Council
March 2017
Krystelle
Bilodeau
Assistant Director, Retail
and Wholesale Debt, Bank
of Canada
[email protected] 613.782.8962
Tom CiardielloVP Strategic Sourcing,
Options Clearing [email protected] 312. 322.4984
Merrilee EvansDirector Category
Management, [email protected] 416.933.3296
John Fafian Director, PwC [email protected] 646.471.5755
Karen GraySr EDDM Specialist – Due
Diligence & Monitoring,
Lexis Nexis N.A.
[email protected] 214.370.9682
Bill HarrisN.A. Indirect Procurement
Strategy Manager, [email protected] 937.539.1114
Debbie Manos-
McHenryChief Sourcing Officer
Huntington National [email protected] 614.480.5249
Brad PetersonPartner & Attorney,
Mayer [email protected] 312.701.8568
Brian SmithDirector, Global Supply
Chain Services, [email protected] 313.792.4280
Linda
Tuck ChapmanCPO Emeritus &
President, [email protected] 416.452.4635
SRC Thought Leaders Council
Agenda
RPA, AI and Algorithms
Super-Charged Game Changers
These new solutions are changing the face of work as we’ve known it. This session will accelerate your path to “expert advisor” … what you need to know to be successful.
Objectives
To accelerate your understanding from a solutioning, sourcing and risk management perspective, propelling you to the most informed person on your team. You’ll come away with:
• Is RPA new, or a just new term for process automation?
• What is AI and IA, and their impact on RPA?
• Rapid solutioning, leveraging early adopters’ experiences
• Expert tips: selection, contracting and good governance
Critical success factors
Fact-based decision-making is based on competitive intelligence, networking, self-education and structured evaluation.
• RPA, process automation
• AI,IA
• Digital strategies
• Cloud
• Algorithms and models
• Market leaders: providers and buyers
• Benefits and risks
• Recommendations
• Speed and cost to implement
What do we need to know?
RPA, IA, Algorithms and Models
What is RPA?
Robotic Process Automation (RPA):
The application of technology that enables computer software to partially or fully automate human activities which are manual, repetitive and rule-based
RPA gives a company the ability to implement a platform-based business process that is definable, repeatable and rules-based
….. and
to assign to a software “robot” that will manage execution of that process
How does RPA work?
RPA software often works at the “presentation layer” (the user interface) of computer systems and mimics a human user
Because RPA can sit on top of a company’s IT infrastructure and systems, can be implemented without altering existing infrastructure and systems
RPA depends on high quality, structured data, though the data can come from various different systems
Back-office clerical processes that tend to be simple and transactional in nature, requiring little (if any) analysis or subjective judgment, and are good starting points for RPA
Artificial Intelligence (AI) also called Smart Process Automation (SPA) and Intelligent Automation (IA) is intelligent software with “machine-learning” capabilities.
Unlike RPA:
1. AI can train itself, or be trained to automate more complex and subjective work through pattern recognition
2. AI can process natural language (NLP)
3. AI can process unstructured data, learning to process new data and its variations over time
4. AI responds to changes in the environment, adapting and learning new ways for processes, data and information to be managed
What is AI?
How does AI work?
Machine Learning
Programmers don’t encode computers with instructions. They train AI systems.
Demis Hassabis, the leader of Google’s DeepMind AI team:
training AI systems is “almost like an art form to get the best out of these systems. . . . There’s only a few hundred people in the world who can do that really well.”
Black Box Processing
“With machine learning, the engineer never knows precisely how the computer accomplishes its tasks. The neural network’s operations are largely opaque and inscrutable. In other words, it is a black box.”
Source:
-- The Rise of AI – The End of Code, by Jason Katz,
Wired Magazine, May 2016
AI’s capabilities
1) Captures (un)structured information:
• Vision recognition (recognize a face or photo),
• Sound recognition (transcribe spoken words),
• Search (extract data from unstructured documents),
• Data analysis (identify clusters of behaviors in customer data)
2) Turns information into something useful using:
• Natural language processing (extract meaningful data from emails,
voice or other sources)
• Reasoning (act based on the information or not)
• Predictions (predict behavior based on past behavior)
What we’ll talk about today
What you need to know
What are they? Primary objectives?Primary
benefits?
Algorithms
A process or set of rules to be
followed for calculations or
other problem-solving
operations, especially for
computers
Algorithms are make
complex calculations
and are used to
redesign business
processes
• Established
decision points
• Consistent input
• Speed
• Volume agnostic
• Simplifies
complexity
• Accuracy
• Predictive
capabilities
• Analytical
capabilities
Models
Mathematical (symbolic),
representation or simplified
version of a real-life scenario,
relationship, structure, or
system. Models often
incorporate Algorithms
Models improve speed
and consistency of
decisions and can be
used to explain, control
or predict results
Why are these important?
How do Algorithms, Models, RPA and IA interact?
Algorithms are used to create Models and to power decision-
making in IA, bots and RPA software. They are the tools that
drive activities and outcomes based on their input data,
variables, structure and goals.
How are they changing our work?
• Pervasive use of Algorithms in decision-making capabilities
should result in a shift from driving processes to managing
performance of algorithms
• Models unpin the evolution from data analytics to higher
value work
Algorithms and Models
Simple: Random Number Generator
Used in a large number of applications:
interlink connection, cryptography, secure hash algorithm, video games, artificial intelligence, optimization, to initial conditions for
problems, finances, etc.
Complex: Google’s Search Tool
Google's search algorithm, while public the way it organizes search results remains the company's most closely guarded secret.
• “PageRank” is the key to Google's rapid dominance of internet search.
• The algorithm looks at every link to/from every internet page.
• A link to a page is a vote that it’s worth sharing.
• The more inbound links a page has, the higher its PageRank is.
• A 2nd measure: Links from pages which have a high PageRank themselves confer a higher PageRank.
Being linked-to by Stanford University - Google
creators' alma mater - is more valuable than being
linked-to by Stanford’s map shop.
Robotic Process Automation
• New processes are entirely platform-based, including process execution
• Processes must be well documented prior to implementation, Six SIGMA and Leaned
• Embedded bots manage processes
• Machine learning makes the platform nimble and flexible
• Leverages big data for better and different outcomes
• May generate big cost savings
RPA is different from process automation
Process Automation
• Platform and people based
• Outsourcing and transition can occur prior to process improvements being implemented, regardless of the quality of process documentation
• Typically leverages software, Six SIGMA and LEAN to derive process improvements and savings
• FTE reductions may be marginal
Information Security and Fraud Prevention
• A software robot could be used to execute a process as directed, without inappropriate data collection, fraudulent intervention or deviation from prescribed process.
Could be particularly useful with sensitive customer data such as personal pensions and administrative affairs of armed forces personnel, or financial services where having a person access multiple systems could increase the risk of fraud
Promoting self-service
• A principal barrier to the adoption of self-service is often technological
• RPA can be used to deploy new self-service solutions where robots simply mimic the behavior of humans to perform backend transcription and processing activities
Some benefits
More benefits
Promote use of big data.
Can be used to collect and organize inconsistent data from among disparate systems AI then performs big data analytics
Help legacy systems work with cloud-based systems.
RPA software could enable automated ordering and provisioning of services through a cloud interface, translated to work with more traditional systems
Overcome Geographic Hurdles
To create new business opportunities for clients that have political or regulatory impediments to offshoring their IT functions or business processes. Can also reduce to need to relocate operations to take advantage of labor arbitrage
RPA in action: an example
The Scenario:
A construction engineering business produces and sends over 500 invoices per month to customers, each requiring up to hundreds of pages of supporting data from a dozen different systems
The Challenge:
Each invoice takes up to 5 hours to produce
The Solution:
The work was converted to an RPA platform, with bots. Processing time is only 11 minutes per invoice; $$ millions in savings
Competitive Intelligence
1. These are early days, POC is a good approach. The market for
IT robotic automation globally is forecast to reach US$ 4.98 Bn
by 2020
2. Time to implement is typically 30 – 90 days. Robots can be
used for mundane tasks. The cost of the robot is a step-
function. Scale counts: identify multiple areas for RPA usage,
incremental run-cost is low
3. RPA/IA dramatically increases quality, processing speed and
customer satisfaction. Artificial intelligence + Human intelligence
drives the best results
4. Governance really counts! Black box processing brings unseen
risks. When something goes wrong, processing speed will be a
liability. Constant scenario testing is a sensible way to detect
and prevent problems
Recommendations
Recommendation #1: Supplier Setup
A proof of concept to test utilizing RPA for Procurement. POC
focuses on supplier set-up
Using RPA, we can automate administration tasks with Virtual
Workers as our back office admin team. Robotic processes can
handle end-to-end processes over time, performing them quickly
and accurately - every time.
Automation is particularly useful for Procurement to automate
supplier set up processes.
By eliminating repetitive and manually interactive processes,
RPA drives efficiency, enhances productivity, consistency and
accuracy.
This will enables response time and compliance with internal and
external requirements, reducing work effort by our suppliers and
internal resources.
Recommendation #2 Talent Acquisition
• Entrance to RPA solutions through Proof of Concept (POC) modeling
o Honda with support from our talent staffing partners, labor market
analysis experts, and a RPA software provider are developing a RPA
solution to improve efficiencies talent acquisition
• POC focuses on multiple activities such as:
o Identifying benchmark statistics by position/role
o Generate reports for Talent Management, Procurement and
Stakeholders/Requisitions requesters
o Status tracking
• Company MUST have appetite for Change management and Adaptation of
tool
• For RPA to work; Processes and the documentation has to be in certain
format with specific flows
• Integration between multiple systems such as share point, spreadsheet,
ERP(s), Email App was a challenging task
(Case
Stu
dy)
(Learn
ings)
Scotiabank: Collecting Credit Card Debt
Credit card collections is a time consuming and expensive process. The challenge is finding the right “treatment” that will encourage customers to pay.
Scotiabank uses a type of AI called deep learning, or neural network, modelled on the human brain, which combines multiple layers of processing. “You’re trying to find the patterns of behavior that lead you to believe a customer will pay you back.”
The DeepLearni.ng system was tested against the bank’s existing model, using historical data, to see which would generate better results. The technology came out ahead in depth of analysis, speed, and agility.
Scotiabank is testing the potential to broaden its use to car and small business loans and mortgages collections.
Source: Neil Bartlett, Scotiabank’s senior vice-president of Analytics.
Additional ResourcesSIG Sourcing Resource Center
Jobs of the Future and Skills You Need
Additional resources available in the SRC
White Papers Recommended Reading
Weapons of Math Destruction by
Cathy O’Neill
Robotic Process Automation 6 real
world use cases. http://thoughtonomy.com/wp-
content/uploads/2016/09/Thoughtonomy_RPA_white
paper.pdf
Jobs of the Future. David Deming,
Harvard Universityhttps://www.weforum.org/agenda/2016/09/jobs-of-
future-and-skills-you-need/
HBR - Companies Are Reimagining
Business Processes with Algorithms, H.
James Wilson, Allan Alter, Prashant Shukla
Tim Worstall, ‘WEF’s Davos Report on
Robots, Automation and Job Loss: A
Trivial Result of No Matter At All’ in
Forbes on Jan 18, 2016
Forrester: The Future of Jobs 2025:
Working Side by Side with Robots
The Institute for Robotic Process
Automation
ACL: Automating Fraud Detection: The
Essential Guidehttp://src.sig.org/src.php?id=10103
Hyperledger Whitepaper http://www.the-
blockchain.com/docs/Hyperledger%20Whitepaper.pdf
SRC Thought Leaders Council
Krystelle
Bilodeau
Assistant Director, Retail
and Wholesale Debt, Bank
of Canada
Tom CiardielloVP Strategic Sourcing,
Options Clearing Corp
[email protected]. 322.4984
Merrilee EvansDirector Category
Management, [email protected] 416.933.3296
John Fafian Director, PwC [email protected] 646.471.5755
Karen GraySr EDDM Specialist – Due
Diligence & Monitoring,
Lexis Nexis N.A.
Bill HarrisN.A. Indirect Procurement
Strategy Manager, Honda
Debbie Manos-
McHenryChief Sourcing Officer
Huntington National [email protected] 614.480.5249
Brad PetersonPartner & Attorney,
Mayer [email protected] 312.701.8568
Brian SmithDirector, Global Supply
Chain Services, [email protected] 313.792.4280
Linda
Tuck ChapmanCPO Emeritus &
President, [email protected] 416.452.4635
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Super-Charged Game Changers
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