with Analytics and Automation Session #6945 · right technologies to automate enough of the...
Transcript of with Analytics and Automation Session #6945 · right technologies to automate enough of the...
Delivering Excellent Customer Experienceswith Analytics and Automation—Session #6945
Stephane MeryIBM DE, Digital Business Automation, Decisions Chief ArchitectJames TaylorCEO, Decision Management SolutionsRyan TrollipCTO, Decision Management SolutionsThink 2019 / 6945 / February 14, 2019 / © 2019 IBM Corporation
IBM’s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice and at IBM’s sole discretion.
Information regarding potential future products is intended to outline our general product direction and it should not be relied on in making a purchasing decision.
The information mentioned regarding potential future products is not a commitment, promise, or legal obligation to deliver any material, code or functionality. Information about potential future products may not be incorporated into any contract.
The development, release, and timing of any future features or functionality described for our products remains at our sole discretion.
Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user’s job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here.
2
Please note
IBM Cloud 2019 / © 2019 IBM Corporation
Artificial Intelligence is a Key Driver to Product Innovation
and enhanced Customer Experience
of companies believe AI is key to competitive advantage94%
companies have extensively incorporated AI in their offerings or processes
5%
IBM Cloud 2019 / © 2019 IBM Corporation
What is Artificial Intelligence?
To get the value, AI must be made
actionable through the Automation
of business operational decisions.
Rule-based
systems
Operational
Systems
Natural
Language
Processing
Image
Recognition
IBM Cloud 2019 / © 2019 IBM Corporation
It is not prescriptive by itself
In other words, you can’t make decisions with ML alone
Use ML to get insights from your
historical data.
Use Business Rules to control how insights
are turned into action.
Machine Learning is a descriptive/predictive technology
to transform your data into insights
IBM Cloud 2019 / © 2019 IBM Corporation
https://www.forrester.com/report/The+Dawn+Of+Digital+Decisioning/-/E-RES141568
https://www.forrester.com/report/The+Forrester+New+Wave+Digital+Decisioning+Platforms+Q4+2018/-/E-RES141571
IBM Cloud / © 2018 IBM Corporation
Key Takeaways
Digital Decisioning Platforms are a new generation of systems that bring together
business context, processes, ML and rules to deliver intelligent decisions.
They are the “brain” of your digital operations
IBM Cloud / © 2018 IBM Corporation
Combine analytics with business rules
to implement your operational decisions
Provide the ultimate
business agility by
managing business
decisions outside of
applications
Execute your enterprise
operational decisions at scale
Use IBM Operational Decision Manager, the market-leading Decisioning Platform,
to inject intelligence in your business operations
A major insurance company in Asia is processing claims and takes approval decisions based on potential fraud score, historical similar decisions and prescriptive decision logic.
IBM Cloud 2019 / © 2019 IBM Corporation
EXPECTED BENEFIT
Most simple cases automatically processed.
Improve customer experience with no-delay payments.
UNIQUE CHALLENGE
Need to combine several predictive models (fraud, claim complexity…) with regulation-compliant and business-led decision logic
Balance automation and human control to maximize speed and reduce errors.
What Clients are saying?
✓ Decisions are everywhere, touching every steps of the Customer journey, from Marketing, to Sales, to Claims.
✓ Best decisions leverage insights from the past and business knowledge and regulation.
✓ All operational systems should be supported by a “Decision Hub” that brings data, ML and business rules to automate decisions.
10© 2019 Decision Management Solutions
Next Best Offer
$6,000,000 in APE uplift
>98% Agent adoption
14-24%+ Acceptance
One smarter, automated decision can be worth millionsThe Dawn Of Digital Decisioning: New Software Automates Immediate Insight-To-Action Cycles Crucial For Digital Business John R. Rymer and Mike Gualtieri
• An automated decision picks the best offer to make to a customer based on
the insurance products they have already selected. Using information
about the customer, it personalizes the message and picks a suitable offer.
• The offer is always for a relevant product, never for something they have
already selected and always something easy to add to their purchase.
Think 2019 / 6945 / February 14, 2019
© 2019 Decision Management Solutions 11
A Smarter, Automated Decision:Next Best Offer
Multi-channel Agents mobile app (iPad) initially
Reused in customer portal
Under Marketing Control Analyze decision outcomes
Manage decision logic
Analytics Propensity
Product sequence
Segmentation
Business Rules Suitability
Affordability
Restrictions
Product rules
Next Up: Machine Learning
Think 2019 / 6945 / February 14, 2019
© 2018 Decision Management Solutions 12
External Data
Big Data
Decision Services Deliver Digital Decisions to Your Systems
Business
RulesAnalytics,
ML and AI
• 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
Think 2019 / 6945 / February 14, 2019
© 2019 Decision Management Solutions 13
Three Steps to Delivering 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
Think 2019 / 6945 / February 14, 2019
© 2019 Decision Management Solutions 14
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
Think 2019 / 6945 / February 14, 2019
© 2019 Decision Management Solutions 15
Mix and Match Business Rules, Analytics and AI
Decision Modeling shows all the elements of a decision and enables you to mix and match the right technologies to automate enough of the decision to take advantage of your predictive analytic models and machine learning.
Automate Policies
Enforce Regulations
Encapsulate Expertise
Put Analytics, ML and AI to Work
Think 2019 / 6945 / February 14, 2019
© 2019 Decision Management Solutions 16
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.
Think 2019 / 6945 / February 14, 2019
© 2019 Decision Management Solutions 17
Continuous ImprovementMedical Claims
Straight Through Processing Before: 0%
Day 1: 8%
Day 100: 28%
Business-led Continuous Improvement
The project developed a decision model, then implemented the business rules that
match that model in IBM ODM.
To manage risk the initial implementation was very cautious – just 8% auto
adjudication.
But because ODM Simulation and a decision outcomes dashboard had been developed
using the decision model, the claims team could see which claims were not being auto
paid that could have been.
Using Decision Center they were able to make the changes they wanted, simulate
them and deploy them.
This resulted in a steady increase to exceed their target and positioned them to
integrate analytic insight using ML in the coming months.
0%
10%
20%
30%
-30 -20 -10 0 10 20 30 40 50 60 70 80 90 100
Think 2019 / 6945 / February 14, 2019
© 2019 Decision Management Solutions 18
What the Customer Says about Maximizing Impact
It’s a journey
It’s lots of small positive changes
It’s about transparency
It’s a lot about people
• It’s a journey• Start with rules/data insights, then build up
sophistication leveraging A.I./machine
learning as appropriate
• It’s lots of small positive changes• Leverage built-in experimental capabilities to
manage unexpected risk/outcome and
improve decisions overtime
• It’s about transparency• Break down logic of complex
decisions for easy understanding.
• It’s a lot about people • Provide traceability for each decision
made. Require new roles/skills to
manage decision performance. Focus
on training to build inhouse
competencies/capabilities.
Think 2019 / 6945 / February 14, 2019
© 2018 Decision Management Solutions 19
Challenges with ML Ops
Data Accessibility & performance learning
Age & quality
Prescriptive noise
Development & Deployment Very long development cycle
Reliant on technical deployment
Visibility Model performance
Result explainability
© 2018 Decision Management Solutions 20
Rule Maintenance
DecisionsFirst Modeler
Design Time - Real-Time Decision ArchitectureDecision models managed
by business SMEs
coordinate business rules
and analytic models
Watson Studio
Decision explanation and outcomes
integrated into decision dashboard
Decision Dashboard
Model
Configuration
Prescriptive
Decisions
Predictive
DecisionsSupporting
Variables /
Features
HTAP
© 2018 Decision Management Solutions 21
Rule Maintenance
DecisionsFirst Modeler
Deployment - Real-Time Decision ArchitectureDecision models managed
by business SMEs
coordinate business rules
and analytic models
Watson Studio
Model
Configuration
Prescriptive
Decisions
Predictive
Decisions
Decision Service
Explanation e.g.
LIME, AI Open
Scale
© 2018 Decision Management Solutions 22
Decision Service
Execution - Real-Time Decision Architecture
Decision-making logs
Business
outcome data
Explanation e.g.
LIME, AI Open
Scale
Dynamic query in-memory HTAP database
Decision explanation and outcomes
integrated into decision dashboard
Decision Dashboard
Transaction
Dynamic Model Exec
Execution Data
Events update
variables
© 2018 Decision Management Solutions 23
Business Results ViewExplainers Integrated in Claims Dashboard
Non-Disclosure
model Score
Which features contributed
what to the score?
Review data at a per
claim level or for a
group of claims
How was the score used
in the overall decision
Explanation e.g.
LIME, AI Open
Scale
Decision-making logs
Business
outcome
data
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
The Dawn Of Digital Decisioning: New Software Automates Immediate Insight-To-Action Cycles Crucial For Digital Business John R. Rymer and Mike Gualtieri
Think 2019 / 6945 / February 14, 2019 / © 2019 IBM Corporation
Thank you
25Think 2019 / 6945 / February 14, 2019 / © 2019 IBM Corporation
Stephane MeryIBM DE, Digital Business Automation, Decisions Chief Architect—[email protected]
James TaylorCEO, Decision Management Solutions—[email protected]+1 650 400 3029decisionmanagementsolutions.com
Ryan TrollipCTO, Decision Management Solutions—[email protected]+1 774 641 3666decisionmanagementsolutions.com
Notices and disclaimers
26Think 2019 / 6945 / February 14, 2019 / © 2019 IBM Corporation
© 2018 International Business Machines Corporation. No part of this document may be reproduced or transmitted in any form without written permission from IBM.
U.S. Government Users Restricted Rights — use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM.
Information in these presentations (including information relating to products that have not yet been announced by IBM) has been reviewed for accuracy as of the date of initial publication and could include unintentional technical or typographical errors. IBM shall have no responsibility to update this information. This document is distributed “as is” without any warranty, either express or implied. In no event, shall IBM be liable for any damage arising from the use of this information, including but not limited to, loss of data, business interruption, loss of profit or loss of opportunity. IBM products and services are warranted per the terms and conditions of the agreements under which they are provided.
IBM products are manufactured from new parts or new and used parts. In some cases, a product may not be new and may have been previously installed. Regardless, our warranty terms apply.”
Any statements regarding IBM's future direction, intent or product plans are subject to change or withdrawal without notice.
Performance data contained herein was generally obtained in a controlled, isolated environments. Customer examples are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual performance, cost, savings or other results in other operating environments may vary.
References in this document to IBM products, programs, or services does not imply that IBM intends to make such products, programs or services available in all countries in which IBM operates or does business.
Workshops, sessions and associated materials may have been prepared by independent session speakers, and do not necessarily reflect the views of IBM. All materials and discussions are provided for informational purposes only, and are neither intended to, nor shall constitute legal or other guidance or advice to any individual participant or their specific situation.
It is the customer’s responsibility to insure its own compliance with legal requirements and to obtain advice of competent legal counsel as to the identification and interpretation of any relevant laws and regulatory requirements that may affect the customer’s business and any actions the customer may need to take to comply with such laws. IBM does not provide legal advice or represent or warrant that its services or products will ensure that the customer follows any law.
Notices and disclaimerscontinued
27Think 2019 / 6945 / February 14, 2019 / © 2019 IBM Corporation
Information concerning non-IBM products was obtained from the suppliers of those products, their published announcements or other publicly available sources. IBM has not tested those products about this publication and cannot confirm the accuracy of performance, compatibility or any other claims related to non-IBM products.Questions on the capabilities of non-IBM products should be addressed to the suppliers of those products. IBM does not warrant the quality of any third-party products, or the ability of any such third-party products to interoperate with IBM’s products. IBM expressly disclaims all warranties, expressed or implied, including but not limited to, the implied warranties of merchantability and fitness for a purpose.
The provision of the information contained herein is not intended to, and does not, grant any right or license under any IBM patents, copyrights, trademarks or other intellectual property right.
IBM, the IBM logo, ibm.com and [names of other referenced IBM products and services used in the presentation] are trademarks of International Business Machines Corporation, registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at “Copyright and trademark information” at: www.ibm.com/legal/copytrade.shtml.
28
®
https://www.ibm.com/legal/us/en/copytrade.shtml