Introduction to Digital Decisioning

2. © 2019 Decision Management Solutions 2 Your Goals  Get some basic information on digital decisioning  See how digital decisioning will help your organization  Identify your next steps to get started

3. © 2019 Decision Management Solutions 3 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

4. 4 AGENDA © 2019 Decision Management Solutions AI Opportunities and Challenges Digital Decisioning  A Definition  Principles of Digital Decisioning  Delivering Digital Decisioning Getting Started Q&A

5. © 2019 Decision Management Solutions 5 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

7. 7© 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

8. 8© 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

9. © 2019 Decision Management Solutions 9 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

10. © 2019 Decision Management Solutions 10 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.

11. 11© 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

12. © 2019 Decision Management Solutions 12 Different Kinds of AI Interface AI Natural Language Processing Image Recognition Transcription Search Decision-Making AI Decision Logic Optimizing Algorithms Probabilistic Algorithms

14. © 2019 Decision Management Solutions 14 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

15. © 2019 Decision Management Solutions 15 The Value of Digital Decisioning Improves customer experience Reduces fraud Manages risk Targets individual customers Increases agility Drives business growth

16. © 2019 Decision Management Solutions 16 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

17. © 2019 Decision Management Solutions 17 The Value of Digital Decisioning Improves customer experience Reduces fraud Manages risk Targets individual customers Increases agility Drives business growth

18. © 2019 Decision Management Solutions 18 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

19. © 2019 Decision Management Solutions 19 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

20. © 2019 Decision Management Solutions 20 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

22. © 2019 Decision Management Solutions 22 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

23. © 2019 Decision Management Solutions 23 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

24. © 2019 Decision Management Solutions 24 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.

26. © 2019 Decision Management Solutions 26 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

28. © 2019 Decision Management Solutions 28 There’s Something For Everyone Business Owner Control Analytic Insights in Production Operational Transparency Clean Integration with Legacy Systems Continuous Improvement

29. © 2019 Decision Management Solutions 29 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

31. © 2019 Decision Management Solutions 31 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

Introduction to Digital Decisioning

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Introduction to Digital Decisioning

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