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© 2019 Decision Management Solutions 1
 Welcome
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An Introduction To Digital Decisioning
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© 2019 Decision Management Solutions 2
An Introduction To Digital Decisioning
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© 2019 Decision Management Solutions 3
An Introduction To Digital Decisioning
 You are in the Lobby: Welcome
 We will start on the hour
 There is no audio at this time
 Audio will play through your
computer speakers or headset
This Slide
Use the chat if you have
questions
Some relevant files you
can download while you
wait
Run the audio wizard
under the Meeting menu to
configure your speakers
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© 2019 Decision Management Solutions 4
This Slide
An Introduction To Digital Decisioning
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 Enter any questions in the Q&A panel at any time
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© 2019 Decision Management Solutions
James Taylor
An Introduction To Digital Decisioning
© 2019 Decision Management Solutions 6
Your Goals
 Get some basic information on
digital decisioning
 See how digital decisioning will
help your organization
 Identify your next steps to get
started
© 2019 Decision Management Solutions 7
Our Goals In This webinar
 Show you how digital decisioning delivers value from AI
 Outline the most important drivers of success
 Give you some examples
 Suggest some steps to get started
James
Taylor
8
AGENDA
© 2019 Decision Management Solutions
AI Opportunities and Challenges
Digital Decisioning
 A Definition
 Principles of Digital Decisioning
 Delivering Digital Decisioning
Getting Started
Q&A
© 2019 Decision Management Solutions 9
Quick Payoff for listening
It’s easy to spend money on AI and Machine Learning
Much harder to get value
Digital Decisioning delivers the value of Machine Learning
Critical Success Factors
 Decision Modeling
 Machine Learning AND Business Rules
 Continuous Improvement
10© 2019 Decision Management Solutions
AI Opportunities And Challenges
11© 2019 Decision Management Solutions
AI will add $13T to the global economy
97% are investing in AI
75% AI will enable new businesses
85% AI will allow a competitive advantage
76% AI will “substantially transform” companies
AI will add $13T to the global economy over the next decade
—Building the AI Powered Organization, HBR July-2019
97% of firms are investing in big data and artificial intelligence (AI)
—2019 survey by New Vantage Partners
Three-quarters of executives believe AI will enable their companies to move into new businesses.
Almost 85% believe AI will allow their companies to obtain or sustain a competitive advantage.
—Reshaping Business With Artificial Intelligence, MIT Sloan Management Review September 06, 2017
76% [believed AI] will “substantially transform” their companies within the next 3 years
—Tom Davenport, The AI Advantage
12© 2019 Decision Management Solutions
Gartner 2019:
 86% have initiated AI projects
 4% have AI deployed
Gartner's 2019 CIO survey points to the fact that,
although 86% of respondents indicate that they either
have AI on their radar, or have initiated projects, only
4% have projects currently deployed.
In a 2017 McKinsey survey with 3,000+ respondents,
only 20% had adopted one AI technology in one part of
their business
The gap between ambition and execution is large at
most companies… only about one in five companies has
incorporated AI in some offerings or processes. Only
one in 20 companies has extensively incorporated AI in
offerings or processes. Across all organizations, only
14% of respondents believe that AI is currently having a
large effect on their organization’s offerings.
—Susan Athey, Economics of Technology Professor at
Stanford Graduate School of Business, quoted in MIT
Sloan Management Review September 06, 2017
Many organizations’ efforts with [AI] are falling short.
Most firms have run only adhoc pilots of are applying AI
in just a single business process… Firms struggle to
move from the pilots to companywide programs
—Building the AI Powered Organization, HBR July 2019
Gap between ambition and execution
 20% AI in some processes
 5% Extensive AI
Most firms
 Ad-hoc AI pilots
or AI in one business process
 Struggle to move beyond pilots
© 2019 Decision Management Solutions 13
Enterprises waste time and money on
unactionable analytics
Digital decisioning can stop this insanity
The Dawn Of Digital Decisioning: New Software Automates Immediate Insight-To-Action Cycles Crucial For Digital Business John R. Rymer and Mike Gualtieri
© 2019 Decision Management Solutions 14
Critical Success Factors
Institute a culture of
digital decisions-first
design thinking
Think of digital
decisioning as the nexus
of business rules, data,
analytics, and machine
learning models
Decisions
Matter
ML Does Not
Stand Alone
Experience is that AI
and ML projects must
be focused on a
specific decision from
the beginning. You
cannot simply develop
an AI and then try to
figure out how to
improve a decision
with it.
Core AI algorithms are
machine learning-
based. ML is often
presented as
“replacing” other
decision-making
technologies like
business rules, data
mining or
optimization. However,
not all problems are
best solved by machine
learning.
15© 2019 Decision Management Solutions
Decisions Matter Particularly
Operational Decisions
Especially
Digital Decisions
Focusing AI on decision-making dramatically increases the odds of success.
Because operational decisions are made repeatedly and in large numbers, they generate the data you need for AI and repay an investment in an AI Algorithm.
It also turns out that embedding AI into an automated, digital decision is more effective than presenting the results to a human user, so digital decisions are key.
One smarter, automated decision
can be worth millions in terms of
customer acquisition, retention,
and/or operational efficiency
© 2019 Decision Management Solutions 16
Different Kinds of AI
Interface AI
Natural Language Processing
Image Recognition
Transcription
Search
Decision-Making AI
Decision Logic
Optimizing Algorithms
Probabilistic Algorithms
17© 2019 Decision Management Solutions
Digital Decisioning
© 2019 Decision Management Solutions 18
Digital Decisioning
 Uses Decision Management to Deliver Business Value from AI
 Operationalizes machine learning and artificial intelligence
 Uses business rules to guarantee agility, transparency and compliance
 Supports continuous learning and improvement
 Precise
 Consistent
 Real-time decisions
 … at every touch point
© 2019 Decision Management Solutions 19
The Value of Digital Decisioning
Improves customer experience
Reduces fraud
Manages risk
Targets individual customers
Increases agility
Drives business growth
© 2019 Decision Management Solutions 20
Digital Decisioning
Medical Claims
 Business Problem
 Deliver 20%+ STP of medical claims across
chatbot, mobile, online, direct from hospital
 Results
 50% Straight Through Processing
 Weekly updates
 Business User Control
 Solution
 Manage risk with cautious as-is rollout
 Business-led continuous improvement
 Simulation and impact analysis
 8% STP on day 1, 28% on day 100, 50% on day 250
0%
10%
20%
30%
40%
50%
0 50 100 150 200 250
Days
STP Rate
© 2019 Decision Management Solutions 21
The Value of Digital Decisioning
Improves customer experience
Reduces fraud
Manages risk
Targets individual customers
Increases agility
Drives business growth
© 2019 Decision Management Solutions 22
Digital Decisioning
Up-Sell and Cross-Sell in agent POS
 Business problem
 How to increase the Annual Premium
Equivalent (APE) of sales made by agents
using mobile app to work with new clients
 Results
 $6,000,000 in APE uplift
 >98% Agent adoption
 14-24%+ Acceptance
 Solution
 Decision service used financial data captured
from client and proposed purchase to suggest
intelligent up-sell or cross-sell
 Seamless integration into sales conversation
 Also integrated into customer portal
“It’s like finding dollar bills lying in the
street. The ROI is enormous and the
effort tiny.”—CFO
© 2019 Decision Management Solutions 23
Four Principles of Digital Decisioning
 Operational, transactional decisions
 Not process, not data, not functions
Decisions First
 Design and execution transparency
 Safe business agility
Transparent and
agile
 Predict risk, fraud and opportunity
 Predict decision impact
Predictive not
reactive
 Not a one-time effort
 Continuous improvement & experimentation
Test, learn, and
improve
© 2019 Decision Management Solutions 24
Digital Decisioning Architecture
Performance
Management
Enterprise Platform
Business
Intelligence
Data
Infrastructure
Application Context
Decision Service
Decision
Monitoring
Business Process
Management
Legacy
Applications
Business
Rules
Decision Modeling
Machine
Learning
Optimization
A decision service encapsulates business rules, advanced analytics and even AI technology to deliver
automated decisions to your application context. Leveraging your data, its behavior is defined by a
decision model that also connects its results to business performance for effective decision monitoring.
Packaged
Applications
Apps and Mobile
Applications
© 2019 Decision Management Solutions 25
Decision Management
Lifecycle for Digital Decisioning
© 2019 Decision Management Solutions 26
Decision Discovery and Modeling
Decision Models Show What’s Involved In Digital Decisions
Knowledge
required
Structure of
decision-making
Data required
• Decision models are best
developed using the
Decision Model and
Notation (DMN) standard.
• This defines a notation
showing decisions, their
decomposition into
reusable sub-decisions, the
data each decision needs
and the knowledge
required to define business
rules or analytics for each.
Decision to be
made
© 2019 Decision Management Solutions 27
External
Data
Big Data
Decision Service Definition and Implementation
Analytics,
ML and AI
Business
Rules
• Business Rules are quick
to change
• Good for regulations,
policies, flash updates
• Less insight-rich than
analytics
• Analytics are insight-rich
but often opaque,
especially ML and AI
• Good for patterns,
trends, categorization
• Must be fed new data and
continuously improved
A decision service encapsulates
business rules, analytics, ML and
AI to deliver automated decisions
to your application context.
Data about business outcomes and decisions
made is integrated with external data to
close the loop and improve both rules and
analytics
© 2019 Decision Management Solutions 28
Decision Measurement and Improvement
Continuously Improve by Capturing Decision Outcomes
 Gather data
 What was decided
 Why was that decided
 How did that work out?
 Change the way you decide
Good Machine Learning platforms keep models learning
as new data is gathered. Add data about the decisions
you made, and how they worked out in business terms,
and you can understand your decision-making and turn
your machine learning into business learning.
29© 2019 Decision Management Solutions
Getting Started
© 2019 Decision Management Solutions 30
Three Critical Success Factors For Digital Decisioning
DecisionsFirst
Design Thinking
Mix and Match
Technology
Continuous
Improvement
• DecisionsFirst Thinking - Think about decision design first to build a decision model and drive practical innovation
• Mix and Match Technology – Business rules, analytics and AI under a decision umbrella, deployed as a decision service
• Continuous Improvement – Analyze decision-making to drive business learning and focus on gradual improvement
© 2019 Decision Management Solutions 31
Get Everyone On The Bus
 Business
 IT
 Operations
 Analytics
© 2019 Decision Management Solutions 32
There’s Something For Everyone
Business Owner
Control
Analytic Insights in
Production
Operational
Transparency Clean Integration with
Legacy Systems
Continuous
Improvement
© 2019 Decision Management Solutions 33
Digital Decisioning
Using Decision Management To Deliver Business Impact From AI
 A completely updated version of an established and popular book
“…the only approach that has actually allowed me to
operationalize predictive models and deliver real ROI!”
“Essential reading for COOs looking to rigorously
improve automation through AI.”
“Anyone trying to automate and embed analytics
to support decisions should read this book.”
“Nothing but solid knowledge, sage advice, and great
examples without an ounce of hyperbole or fluff.”
 Forewords by Tom Davenport and Eric Siegel.
 Buy: mkpress.com/DD
34© 2019 Decision Management Solutions
Your Questions
Enter questions
for the Q&A here
James Taylor, CEO
james@decisionmanagementsolutions.com
© 2019 Decision Management Solutions 35
Thank You
 More resources for boosting
insurance productivity on our
website
 decisionmanagementsolutions.com
 Decision Management Solutions
works with clients to improve
their business by applying
business rules and analytic
technology to automate and
improve decisions
 We can help you improve your
productivity with our
DecisionsFirst approach
 info@decisionmanagementsolutions.com
Thank You
For more on
Decision Management, go to:
decisionmanagementsolutions.com
© 2019 Decision Management Solutions

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Introduction to Digital Decisioning

  • 1. © 2019 Decision Management Solutions 1  Welcome  We will start on the hour  There is no audio at this time  Audio will play through your computer speakers or headset An Introduction To Digital Decisioning  You are in the Lobby: This Slide Use the chat if you have questions Some relevant files you can download while you wait Run the audio wizard under the Meeting menu to configure your speakers Use your status indicator to provide feedback
  • 2. © 2019 Decision Management Solutions 2 An Introduction To Digital Decisioning  You are in the Lobby: Welcome  We will start on the hour Audio Check Underway You should hear my voice through your computer speakers or headset If not, run the audio wizard under the Meeting menu This Slide Use the chat if you have questions Some relevant files you can download while you wait Run the audio wizard under the Meeting menu to configure your speakers Use your status indicator to provide feedback
  • 3. © 2019 Decision Management Solutions 3 An Introduction To Digital Decisioning  You are in the Lobby: Welcome  We will start on the hour  There is no audio at this time  Audio will play through your computer speakers or headset This Slide Use the chat if you have questions Some relevant files you can download while you wait Run the audio wizard under the Meeting menu to configure your speakers Use your status indicator to provide feedback
  • 4. © 2019 Decision Management Solutions 4 This Slide An Introduction To Digital Decisioning  If you can’t hear anything, run the audio wizard  Enter any questions in the Q&A panel at any time  The rest of the session will be recorded Use the chat if you have technical issues Run the audio wizard under the Meeting menu if you can’t hear anything Use your status indicator to provide feedback Enter questions for the Q&A here
  • 5. © 2019 Decision Management Solutions James Taylor An Introduction To Digital Decisioning
  • 6. © 2019 Decision Management Solutions 6 Your Goals  Get some basic information on digital decisioning  See how digital decisioning will help your organization  Identify your next steps to get started
  • 7. © 2019 Decision Management Solutions 7 Our Goals In This webinar  Show you how digital decisioning delivers value from AI  Outline the most important drivers of success  Give you some examples  Suggest some steps to get started James Taylor
  • 8. 8 AGENDA © 2019 Decision Management Solutions AI Opportunities and Challenges Digital Decisioning  A Definition  Principles of Digital Decisioning  Delivering Digital Decisioning Getting Started Q&A
  • 9. © 2019 Decision Management Solutions 9 Quick Payoff for listening It’s easy to spend money on AI and Machine Learning Much harder to get value Digital Decisioning delivers the value of Machine Learning Critical Success Factors  Decision Modeling  Machine Learning AND Business Rules  Continuous Improvement
  • 10. 10© 2019 Decision Management Solutions AI Opportunities And Challenges
  • 11. 11© 2019 Decision Management Solutions AI will add $13T to the global economy 97% are investing in AI 75% AI will enable new businesses 85% AI will allow a competitive advantage 76% AI will “substantially transform” companies AI will add $13T to the global economy over the next decade —Building the AI Powered Organization, HBR July-2019 97% of firms are investing in big data and artificial intelligence (AI) —2019 survey by New Vantage Partners Three-quarters of executives believe AI will enable their companies to move into new businesses. Almost 85% believe AI will allow their companies to obtain or sustain a competitive advantage. —Reshaping Business With Artificial Intelligence, MIT Sloan Management Review September 06, 2017 76% [believed AI] will “substantially transform” their companies within the next 3 years —Tom Davenport, The AI Advantage
  • 12. 12© 2019 Decision Management Solutions Gartner 2019:  86% have initiated AI projects  4% have AI deployed Gartner's 2019 CIO survey points to the fact that, although 86% of respondents indicate that they either have AI on their radar, or have initiated projects, only 4% have projects currently deployed. In a 2017 McKinsey survey with 3,000+ respondents, only 20% had adopted one AI technology in one part of their business The gap between ambition and execution is large at most companies… only about one in five companies has incorporated AI in some offerings or processes. Only one in 20 companies has extensively incorporated AI in offerings or processes. Across all organizations, only 14% of respondents believe that AI is currently having a large effect on their organization’s offerings. —Susan Athey, Economics of Technology Professor at Stanford Graduate School of Business, quoted in MIT Sloan Management Review September 06, 2017 Many organizations’ efforts with [AI] are falling short. Most firms have run only adhoc pilots of are applying AI in just a single business process… Firms struggle to move from the pilots to companywide programs —Building the AI Powered Organization, HBR July 2019 Gap between ambition and execution  20% AI in some processes  5% Extensive AI Most firms  Ad-hoc AI pilots or AI in one business process  Struggle to move beyond pilots
  • 13. © 2019 Decision Management Solutions 13 Enterprises waste time and money on unactionable analytics Digital decisioning can stop this insanity The Dawn Of Digital Decisioning: New Software Automates Immediate Insight-To-Action Cycles Crucial For Digital Business John R. Rymer and Mike Gualtieri
  • 14. © 2019 Decision Management Solutions 14 Critical Success Factors Institute a culture of digital decisions-first design thinking Think of digital decisioning as the nexus of business rules, data, analytics, and machine learning models Decisions Matter ML Does Not Stand Alone Experience is that AI and ML projects must be focused on a specific decision from the beginning. You cannot simply develop an AI and then try to figure out how to improve a decision with it. Core AI algorithms are machine learning- based. ML is often presented as “replacing” other decision-making technologies like business rules, data mining or optimization. However, not all problems are best solved by machine learning.
  • 15. 15© 2019 Decision Management Solutions Decisions Matter Particularly Operational Decisions Especially Digital Decisions Focusing AI on decision-making dramatically increases the odds of success. Because operational decisions are made repeatedly and in large numbers, they generate the data you need for AI and repay an investment in an AI Algorithm. It also turns out that embedding AI into an automated, digital decision is more effective than presenting the results to a human user, so digital decisions are key. One smarter, automated decision can be worth millions in terms of customer acquisition, retention, and/or operational efficiency
  • 16. © 2019 Decision Management Solutions 16 Different Kinds of AI Interface AI Natural Language Processing Image Recognition Transcription Search Decision-Making AI Decision Logic Optimizing Algorithms Probabilistic Algorithms
  • 17. 17© 2019 Decision Management Solutions Digital Decisioning
  • 18. © 2019 Decision Management Solutions 18 Digital Decisioning  Uses Decision Management to Deliver Business Value from AI  Operationalizes machine learning and artificial intelligence  Uses business rules to guarantee agility, transparency and compliance  Supports continuous learning and improvement  Precise  Consistent  Real-time decisions  … at every touch point
  • 19. © 2019 Decision Management Solutions 19 The Value of Digital Decisioning Improves customer experience Reduces fraud Manages risk Targets individual customers Increases agility Drives business growth
  • 20. © 2019 Decision Management Solutions 20 Digital Decisioning Medical Claims  Business Problem  Deliver 20%+ STP of medical claims across chatbot, mobile, online, direct from hospital  Results  50% Straight Through Processing  Weekly updates  Business User Control  Solution  Manage risk with cautious as-is rollout  Business-led continuous improvement  Simulation and impact analysis  8% STP on day 1, 28% on day 100, 50% on day 250 0% 10% 20% 30% 40% 50% 0 50 100 150 200 250 Days STP Rate
  • 21. © 2019 Decision Management Solutions 21 The Value of Digital Decisioning Improves customer experience Reduces fraud Manages risk Targets individual customers Increases agility Drives business growth
  • 22. © 2019 Decision Management Solutions 22 Digital Decisioning Up-Sell and Cross-Sell in agent POS  Business problem  How to increase the Annual Premium Equivalent (APE) of sales made by agents using mobile app to work with new clients  Results  $6,000,000 in APE uplift  >98% Agent adoption  14-24%+ Acceptance  Solution  Decision service used financial data captured from client and proposed purchase to suggest intelligent up-sell or cross-sell  Seamless integration into sales conversation  Also integrated into customer portal “It’s like finding dollar bills lying in the street. The ROI is enormous and the effort tiny.”—CFO
  • 23. © 2019 Decision Management Solutions 23 Four Principles of Digital Decisioning  Operational, transactional decisions  Not process, not data, not functions Decisions First  Design and execution transparency  Safe business agility Transparent and agile  Predict risk, fraud and opportunity  Predict decision impact Predictive not reactive  Not a one-time effort  Continuous improvement & experimentation Test, learn, and improve
  • 24. © 2019 Decision Management Solutions 24 Digital Decisioning Architecture Performance Management Enterprise Platform Business Intelligence Data Infrastructure Application Context Decision Service Decision Monitoring Business Process Management Legacy Applications Business Rules Decision Modeling Machine Learning Optimization A decision service encapsulates business rules, advanced analytics and even AI technology to deliver automated decisions to your application context. Leveraging your data, its behavior is defined by a decision model that also connects its results to business performance for effective decision monitoring. Packaged Applications Apps and Mobile Applications
  • 25. © 2019 Decision Management Solutions 25 Decision Management Lifecycle for Digital Decisioning
  • 26. © 2019 Decision Management Solutions 26 Decision Discovery and Modeling Decision Models Show What’s Involved In Digital Decisions Knowledge required Structure of decision-making Data required • Decision models are best developed using the Decision Model and Notation (DMN) standard. • This defines a notation showing decisions, their decomposition into reusable sub-decisions, the data each decision needs and the knowledge required to define business rules or analytics for each. Decision to be made
  • 27. © 2019 Decision Management Solutions 27 External Data Big Data Decision Service Definition and Implementation Analytics, ML and AI Business Rules • Business Rules are quick to change • Good for regulations, policies, flash updates • Less insight-rich than analytics • Analytics are insight-rich but often opaque, especially ML and AI • Good for patterns, trends, categorization • Must be fed new data and continuously improved A decision service encapsulates business rules, analytics, ML and AI to deliver automated decisions to your application context. Data about business outcomes and decisions made is integrated with external data to close the loop and improve both rules and analytics
  • 28. © 2019 Decision Management Solutions 28 Decision Measurement and Improvement Continuously Improve by Capturing Decision Outcomes  Gather data  What was decided  Why was that decided  How did that work out?  Change the way you decide Good Machine Learning platforms keep models learning as new data is gathered. Add data about the decisions you made, and how they worked out in business terms, and you can understand your decision-making and turn your machine learning into business learning.
  • 29. 29© 2019 Decision Management Solutions Getting Started
  • 30. © 2019 Decision Management Solutions 30 Three Critical Success Factors For Digital Decisioning DecisionsFirst Design Thinking Mix and Match Technology Continuous Improvement • DecisionsFirst Thinking - Think about decision design first to build a decision model and drive practical innovation • Mix and Match Technology – Business rules, analytics and AI under a decision umbrella, deployed as a decision service • Continuous Improvement – Analyze decision-making to drive business learning and focus on gradual improvement
  • 31. © 2019 Decision Management Solutions 31 Get Everyone On The Bus  Business  IT  Operations  Analytics
  • 32. © 2019 Decision Management Solutions 32 There’s Something For Everyone Business Owner Control Analytic Insights in Production Operational Transparency Clean Integration with Legacy Systems Continuous Improvement
  • 33. © 2019 Decision Management Solutions 33 Digital Decisioning Using Decision Management To Deliver Business Impact From AI  A completely updated version of an established and popular book “…the only approach that has actually allowed me to operationalize predictive models and deliver real ROI!” “Essential reading for COOs looking to rigorously improve automation through AI.” “Anyone trying to automate and embed analytics to support decisions should read this book.” “Nothing but solid knowledge, sage advice, and great examples without an ounce of hyperbole or fluff.”  Forewords by Tom Davenport and Eric Siegel.  Buy: mkpress.com/DD
  • 34. 34© 2019 Decision Management Solutions Your Questions Enter questions for the Q&A here James Taylor, CEO james@decisionmanagementsolutions.com
  • 35. © 2019 Decision Management Solutions 35 Thank You  More resources for boosting insurance productivity on our website  decisionmanagementsolutions.com  Decision Management Solutions works with clients to improve their business by applying business rules and analytic technology to automate and improve decisions  We can help you improve your productivity with our DecisionsFirst approach  info@decisionmanagementsolutions.com
  • 36. Thank You For more on Decision Management, go to: decisionmanagementsolutions.com © 2019 Decision Management Solutions

Editor's Notes

  1. The speed, volume and complexity of decisions – as well as the impact they have on customer experience – demand automated, real-time decision making. Digital decisioning is an emerging best practice for delivering business impact from AI, machine learning, and analytics. Digital decisioning is an approach that ensures your systems act intelligently on your behalf, making precise, consistent, real-time decisions at every customer touchpoint. Join Digital Decisioning expert James Taylor to learn how organizations are applying digital decisions to operationalize AI and machine learning to automate the customer-facing decisions essential for more profitable, customer-centric business decisions.
  2. JAMES
  3. JAMES
  4. JAMES
  5. JAMES
  6. AI potential is huge AI will add $13T to the global economy over the next decade —Building the AI Powered Organization, HBR July-2019 97% of firms are investing in big data and artificial intelligence (AI) —2019 survey by New Vantage Partners Three-quarters of executives believe AI will enable their companies to move into new businesses. Almost 85% believe AI will allow their companies to obtain or sustain a competitive advantage. —Reshaping Business With Artificial Intelligence, MIT Sloan Management Review September 06, 2017 76% [believed AI] will “substantially transform” their companies within the next 3 years —Tom Davenport, The AI Advantage
  7. AI results are disappointing Gartner's 2019 CIO survey points to the fact that, although 86% of respondents indicate that they either have AI on their radar, or have initiated projects, only 4% have projects currently deployed.   In a 2017 McKinsey survey with 3,000+ respondents, only 20% had adopted one AI technology in one part of their business   There’s a misconception that it’s always going to be better to let an algorithm determine a solution, but that won’t always be the case. AI isn’t a good fit for every sort of problem. —Building the AI Powered Organization, HBR July 2019 The gap between ambition and execution is large at most companies… only about one in five companies has incorporated AI in some offerings or processes. Only one in 20 companies has extensively incorporated AI in offerings or processes. Across all organizations, only 14% of respondents believe that AI is currently having a large effect on their organization’s offerings. —Susan Athey, Economics of Technology Professor at Stanford Graduate School of Business, quoted in MIT Sloan Management Review September 06, 2017 There are relatively few examples of radical transformation with cognitive technologies actually succeeding, and many examples of “low hanging fruit” being successfully picked —Tom Davenport AI Advantage Many organizations’ efforts with [AI] are falling short. Most firms have run only adhoc pilots of are applying AI in just a single business process… Firms struggle to move from the pilots to companywide programs —Building the AI Powered Organization, HBR July 2019
  8. Or as Forrester put it, digital decisioning Analytics not valuable until changing the business Enterprises waste time and money on unactionable analytics Digital decisioning can stop this insanity It is the highest-value next step for a successful digital transformation  Forrester Recommendations: Institute a culture of digital decisions-first design thinking Think of digital decisioning as the nexus of business rules, data, analytics, and machine learning models.  One smarter, automated decision can be worth millions in terms of customer acquisition, retention, and/or operational efficiency
  9. Experience is that AI projects must be focused on a specific decision from the beginning. You cannot simply develop an AI and then try to figure out how to improve a decision with it. Because core AI algorithms are decision-making, AI is often presented as “replacing” other decision-making technologies like business rules, data mining or optimization. However, not all problems are best solved by AI and machine learning. Adopt a business decision-centric approach to AI – one that puts business decisions first. This means focusing on decision-making and changing how you define AI requirements to bring more business knowledge into AI projects. Consider AI as one of a set of decision-making technologies not a standalone technology stack. Specifically, it must be combined with expert knowledge – business rules – to be effective
  10. Decisions matter Especially operational decisions Especially automated operational decisions
  11. JAMES
  12. JAMES
  13. These decision management systems support our existing platforms Providing decision making services to help these systems, and the users of these systems, make better decisions Using both explicit business rules and predictive analytics to make sure these decisions are accurate, compliant and analytically precise And this is where the decision analysis piece comes in as we can collect all the operational data from those systems, reflecting how well our decision-making worked out for us, and feed it back into our big data infrastructure Where, combined with new external big data sources, it drives improved rules and better predictive analytics, closing the loop for continuous improvement.
  14. So, what’s the roadmap to this new way of doing business – three steps turn out to be key DecisionsFirst Thinking –think first about decision design to drive practical innovation Mix and Match Technology – success will require to apply a mix of technology and allow to deliver business-led (not technology-led) automation Learn and Improve –integrate learning and feedback to drive continuous improvement in the decisions. Each step has a couple of keys and we’ll highlight them as we go through. Decision first thinking instead of process Mix and match tech across under decision umbrella CI ok Decision-centric design thinking Adopt decisioning technologies as a set Focus on continuous improvement not big bangs
  15. Digital Decisioning: Using Decision Management to Deliver Business Value from AI “I’ve worked as a C-level executive in multiple insurance companies and engaged countless strategy consultants, IT consultants and technology vendors over the past two decades. This book describes the only approach that has actually allowed me to operationalize predictive models and deliver real ROI!” Digital Decisioning ensures your systems   act intelligently on your behalf, making precise, consistent, real-time decisions at every touch point. It operationalizes machine learning and artificial intelligence, moving you beyond pilots and into production so you can make the best possible decision, every time.  It uses business rules to guarantee the agility, transparency and compliance that established companies and regulated industries demand. Focusing only on decision-making, it supports continuous learning and improvement. Digital Decisioning is the most effective way to put machine learning and artificial intelligence to work. Digital Decisioning improves the customer experience, reduces fraud, manages risk, targets the right offers and actions to each individual customer, increases agility and drives business growth. Digital Decisioning applies machine learning and artificial intelligence at scale to automate the decisions essential for more profitable, more customer-centric and more digital business operations. “Essential reading for COOs looking to rigorously improve automation through AI.” Based on dozens of successful projects around the word, this book lays out the basic elements of the approach in a practical how-to guide. Aimed at managers, not technical teams, this book will focus your efforts to apply machine learning, artificial intelligence and predictive analytics. It emphasizes practical “do this next” advice delivered in non-technical terms, describing. the business value and impact of critical technologies without diving into technical detail. Stories of real implementations, real companies, show what can be done. A completely updated version of an established and popular book on Decision Management, this second edition has forewords by leading analytic experts, Tom Davenport and Eric Siegel. “A wealth of practical knowledge and advice for beginners and experts alike!” -- Written by James Taylor, CEO of Decision Management Solutions and the world’s foremost thinker, writer and consultant on using the decision management approach to deliver Digital Decisioning. “James has been at the forefront of decision management techniques for years. Anyone trying to automate and embed analytics to support decisions should read this book.” —Bill Franks, Chief Analytics Officer, International Institute For Analytics, speaker, and author “An absolute masterclass in analytics from one of the great masters himself. Nothing but solid knowledge, sage advice, and great examples without an ounce of hyperbole or fluff.” —Doug Laney, Principal Data Strategist with Caserta, and best-selling author of 'Infonomics'.  This phrase trips me up. In my mind, digital decisioning isn’t what delivers systems. It’s an approach or a methodology that companies follow to deliver systems…  I feel like we should say something brief about one of the biggest challenges for companies is operationalizing analytics (“last mile”) and that is specifically what digital decisioning is designed to address.  Need to be consistent throughout on small or capital “D” for decisioning.