You need processes that are dynamic, and change over time based on real-time data from many data sources. Predictive analytics, machine learning, self-documenting hardware, point and click integrations, and automated regression and performance testing is the future for ERP, EPM, analytics, and integration professionals. The future is here and you need to be in the know.

1. Automation Isn’t Enough:
You Need Robotics or AI
Doug Hahn

2. www.datavail.com 2
Doug Hahn, Principle Solution Architect
25+ years in IT; 15 consulting, 10 IT executive
Teams of 70+
Experience across multiple disciplines
Active in IOUG, OAUG and QUEST
• Chair OAUG Content Generation Sub Committee
• Ex-Chair of the OAUG Customer Support Council
• Former board member BIWA (IOUG)
• Conference Presentations for all three
Multiple public speaking engagements, Oracle OpenWorld, Collaborate
and regional users groups
Publications:
• OAUG Insight Magazine Summer 2009 edition -- R12 and OBIEE: Intelligence
Investments for Turbulent Times
• OAUG Insight Magazine Fall 2015 – Oracle Support Identifier Groups
OAUG Speaker of the Year 2017
Presenter

3. About Datavail

4. www.datavail.com 4
Professional Services
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Oracle Analytics Capabilities
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Supported BI Applications
BICS
Business
Intelligence
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Service
EssCS
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OBIEE
Oracle
Business
Intelligence
Enterprise
Edition
OBIA
Oracle
Business
Intelligence
Applications
Essbase
Extended
Spreadsheet
Database
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Oracle
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Some baseline definitions
• Automation
• Robotics
• Artificial Intelligence
• Machine Learning
• Difference between Automation, Robotics, Artificial
Intelligence
• Machine Learning as part of AI
• Types of Analytics
Applying automation, robotics and AI to the Business
Historical approach for ERP/EPM/HCM/CRM
How these techniques will change the business
Agenda

8. www.datavail.com 8
General term for work performed by
information technology
Static and predictable condition.
Takes exact inputs and creates exact outputs
Testing Scripts, Screen Scrapers, Keyboard
Recording/Playback
Requires knowing scenarios, use cases and
results
Example: Entering in an Invoice, of defined
types, payment terms etc
Automation

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Advanced form of automation
that is autonomous or semi-
autonomous
Controlled or
directed by systems
or people
Makes decisions or
navigates new situations
without outside help
Able to handle wider
range of inputs and
scenarios
Better suited to deal
with real world or non-
predicted conditions
Robotics
Example: How to
deal with a new type
of Invoice or a new
payment term that is
currently undefined,
using a generic
algorithm
Can’t learn or
expand

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Example: Robotics
would quarantine or
try to handle the new
Invoice
Artificial Intelligence
Ability to learn and improve Even better at dealing with
new situations or conditions
AI would look at various ways
to handle the invoice and
determine which way is best
May use historical data, or a
defined criteria to determine
what is “best”
Solution may even change
over time as more scenarios
are identified

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Machine Learning
Algorithms that use what they
learn from their mistakes to
improve future performance
Process where an AI construct learns
new approaches and how it evaluates
success, or an improvement.
Artificial intelligence technique where
algorithms are given data and process
it without predetermined rules.
May not result in the best
solution initially, but improve
over time

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AI
Automation
Robotics
Manual Testing

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Software Testing
Manual testing is the lowest value and is time
consuming.
If the steps are well known, repeatable, and
the outcome is predictable, this is a candidate
for automation
Robotics is where the input and/or output are
variable, and enough intelligence is required to
deal with a new, unknown scenario.
AI and/Machine Learning to be more dynamic
on how to handle non-planned scenarios

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Robots in the movies tell and incorrect story.
Robots are not inherently dangerous because
they cannot learn or behave outside of human
direction or control.
AI however CAN make new or difference
choices, and can compound decisions, one on
another, to an entirely new method.
This is their power, and can be considered self-
designing and self-coding.
Robots in the movies tell an incorrect story
Robots are not inherently
dangerous because they
cannot learn or behave
outside of human
direction or control.
AI, however,
CAN make new
or difference
choices, and can
compound
decisions, one
on another, to an
entirely new
method.
This is their power,
and can be
considered self-
designing and self-
coding.

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Automation
Perform repetitive tasks
over and over, in a
predictable fashion
Robotics
Autonomous capability
or ability to react to
unpredicted situations
AI
Ability to learn and
improve capabilities
without direct supervision
or direction
Differences

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Analytics
The review of historical information (as well as
external data) to find patterns.
Descriptive analytics describes past activity and
the current state of things.
• It breaks the story of “what happened” or “what is
happening” down into smaller chunks
Diagnostic analytics determines why it happened
• Removes unrelated data and assigns relevance to
each component.
• Can identify relationships previously not understood.

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Predictive analytics uses historical data to forecast
the most likely scenario
• Compares current conditions to historical data
Prescriptive analytics provides suggestions for
future decisions by evaluating multiple outcomes
of various courses of action
Analytics

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Why we need all of these techniques
Data is
growing
exponentially
Ever growing
complexity in
systems
Complex
relationships
between systems
Need to make
decisions at the
speed of NOW

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Why we need all of these
techniques
We need Automation
Free us up from routine tasks, testing,
activities
Helps define the business and what we
know today
We need Robotics
Can’t predict every scenario
How to handle new situations
Intelligent error handling

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Why we need all of these
techniques
We need AI
Can’t learn every situation and write an
acceptable outcome
Can’t see the correlation of every system, data
collection
Can’t code for what we haven’t thought of
We need Analytics and Machine Learning
Feed historical and external data to AI
Make better decisions over time
Evaluate the results of the effort, not the effort
itself

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The future of
ERP/EPM/HCM/CRM is not
more code, but more
autonomous learning
systems that can handle
more data, faster and more
accurately over time

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Takeaways
Automate to free you up
Robotics to build smarter error handling
AI to handle the unexpected
Analytics and Machine Learning to
make AI better

23. Doug Hahn
Principle Solution Architect
Doug.Hahn@Datavail.com
www.datavail.com

24. Thank you