holistic trusted 360 view 20130917-3
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Holistic Trusted 360 View 20130917-3TRANSCRIPT
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2013 IBM CorporationSeptember 17, 2013
A Holistic, Trusted 360 View of Your Data
Priya Krishnan, IBM InfoSphere MDM Product ManagementMark Myers, Senior Product Marketing Manager, IBM InfoSphere Data Explorer
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2013 IBM Corporation
Available data is growing in volume, velocity and
variety
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Transactional & Application Data
Machine Data Social Data
Volume
Structured
Throughput
Velocity
Semi-structured
Ingestion
Variety
Highly unstructured
Veracity
Enterprise Content
Variety
Highly unstructured
Volume
Today the worlds data is doubling every two years. Are you ready?
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Disruptive forces impact long standing business
models AND create new opportunities
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Data is the new oil.Data is just like crude.Its valuable, but if unrefinedit cannot really be used. Clive Humby
We have an economy based on a resource that is not only renewable, but self-generating. Running out is not a problem, drowning in it is. John Naisbitt
Shift of power to the consumer
Pressure to do more with less
Proliferation of big data
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Transaction Systems
Web, e-business and SOA
New Era Analytics
P
l
a
t
f
o
r
m
s
1960-1980s 1990-2000s 2010s
Mainframe, IMS and CICS
WebSphere Big Data
Platform
IBM recognizes this as a major transformation
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IBM is taking a holistic, integrated approach to big
data
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Almost all big data use cases require an integrated set of big data technologies to address the business pain completely
Reduce time and cost and provide quick ROI by leveraging pre-integrated components
Provide both out-of-the-box and standards-based services
Start small with a single project and progress to others over your big data journey
The Whole is Greater than
the Sum of the Parts
Accelerators
Information Integration &
Governance
Data Warehouse
Stream Computing
Hadoop System
DiscoveryApplicationDevelopment
SystemsManagement
Data Media Content Machine Social
BIG DATA PLATFORM
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Improving the customer experience by better understanding
behaviors drives almost half of all active big data efforts
Customer-centric outcomes Digital connections have enabled
customers to be more vocal about expectations and outcomes
Integrating data increases the ability to create a complete picture of todays empowered consumer
Understanding behavior patterns and preferences provides organizations with new ways to engage customers
Other functional objectives The ability to connect data and
expand insights for internally focused efforts was significantly less prevalent in current activities Total respondents n = 1061
Big data objectives
Top functional objectives identified by organizations with active big data pilots or implementations. Responses have been weighted and aggregated.
Customer-centric outcomes
Operational optimization
Risk / financial management
New business model
Employee collaboration
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The key is to leverage all the data
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But how do you find
the signal from the
noise?
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MDM and Data Explorer
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Business ContextAccount number, customer type, purchase history, @
Professional LifeEmployers, professional groups, certifications @
Legal/Financial LifeProperty, credit rating, vehicles, @
Contact InformationName, address, employer, marital@
LeisureHobbies, interests @
Social MediaSocial network, affiliations, @
A customer is a puzzle made up of many pieces
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Every interaction
requires someone
to piece together
parts of the
puzzle
Information about
your customers is
dispersed, forcing
your employees
to extract it piece-
by-piece
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How do we deliver a holistic view to the users who need it?
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External Content (Twitter, News
Feeds...)
Internal Content (CRM, Warehouses,
ERP, ECM...)
I am monitoring all angles yet I cant connect the dots.
I dont know what I dont know where
is my business exposed?
I cant unlock the value in my data to drive
economic value to my business.
Innovation is falling short as I am unable
to see the full research picture.
I cant find the right answers fast
enough to support my customers.
?
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Unlock the value of information when users need it most
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Create unified view of ALL information for real-time monitoring
Identify areas of information risk & ensure data compliance
Analyze customer data to unlock true customer value
Increase productivity & leverage past work increasing speed to market
Improve customer service & reducecall times
InfoSphereData Explorer
Data access & integrationIndex structured & unstructured datain placeSupport existing security Federate to external sourcesLeverage MDM and governance
Discovery & navigation Leverage taxonomies and metadata Clustering & categorization Contextual intelligence Easy-to-deploy applications All at big data scale
Providing unified, real-time access and fusion of big
data unlocks greater insight and ROI
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MDM delivers trusted customer information
Account/Policy Centric
MDM
Customer Centric
Inconsistent customer experience, poor service
Missed opportunities
Minimal understanding of relationships
Consistent customer experience
Recognize cross-sell/up-sell opportunities
Understand relationships and hierarchies for BI
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Disconnected Product
Information
Streamlined Authoring
& Access
No collaborative authoring of products
Lack of a single view of products
No synchronization with up/downstream applications
No ability to publish to commerce sites or product catalogs
Collaboratively author, aggregate and distribute product information
Align with and enforce existing business processes
Access to consistent product information
Product factory build process (assembly of products)
MDM delivers trusted product information
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MDM and big data must work together
Master Data
Management
Core Big Data
Technologies
MDM creates
context for big data.
MDM system provides
trusted information and
operationalizes
insights from big data
Big data creates
context for MDM.
Big data provides new
insights from social
media and other sources
for citizen/criminal
profile
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Enhanced 360 view of the customer
Requirements
Create a connected picture of the customer
Mine all existing and new sources of information
Analyze social media to uncover sentiment about products
Add value by optimizing every client interaction
Value Proposition MDM creates an accurate and
consistent view of customer.
Organizations link unstructured content from external sources to the golden record for the enhanced 360 degree view.
Optimize every customer interactionby knowing everything about them
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360 view of a customer
Contact
information from
MDM and CRM
List of past purchases by
this contact from order
tracking system and MDM
Consolidated list of products
owned based on account affiliation
determined by MDM
Information about
contact from external
sources
Recent conversations
from multiple sources:
e.g., CRM, e-mail, etc.
MDM ensures consistency,
accuracy and reliable identiy
across all sources
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Enhanced 360 View answers questions that require multiple systems
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WikiExperts
What should I know before calling her for renewal? Social
Media
What marketing materials should I send? Support
Ticketing
Whats going on with this customer TODAY? External
Sources
What products can I upsell this customer? CRM
How can we increase engagement with her? Supply
Chain
Email
How can we get more customers like her? Content
Mgt.
What impact will inventory have on her? DBMS
Fusion of data from
multiple systems enables
deeper insightsnot just
facts
Fulfillment
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CRM
J Robertson
Pittsburgh, PA 15213
35 West 15th
Name:
Address:
Address:
ERP
Janet Robertson
Pittsburgh, PA 15213
35 West 15th St.
Name:
Address:
Address:
Legacy
Jan Baker
Pittsburgh, PA 15213
36 West 15th St.
Name:
Address:
Address:
SOURCE SYSTEMS
360o View of Party Identity
Janet
35 West 15th St
Pittsburgh
Robertson
PA / 15213
F
48
1/4/64
First:
Last:
Address:
City:
State/Zip:
Gender:
Age:
DOB:
InfoSphere MDM
BigInsights Streams Warehouse
Unified view of partys information
InfoSphereData Explorer
IBMs MDM capabilities enrich information about business entities
A true 360 view leverages information access and MDM
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Enhanced 360 View secret sauce
Data Explorer Index
Fusion of data and
analytics from
multiple sources
InfoSphere Data Explorer
Enhanced 360 Degree View
Application InfoSphere Master Data Management
Analytics
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Making each investor feel like theyre #1Large brokerage and financial
services firm
Leading provider of workplace and individual retirement savings plans, mutual funds and other financial products for 20 million customers
Secure access to over 30 different silos to empower agents to engage high-value customers to promote up-selling and cross-selling
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Improve 360 degree view of
customers and organizations
A big data problem due to volumes and sentiment analysis
Big data scale 1.5B+ customer records 20 systems 20% annual growth in records Generates over 300K duplicates daily
Sentiment analysis Intermediary Social Hub collects all
social data and generates a SNAP (Social Network Advocacy Pulse) score
Scoring linked to on premise customer information, and used to help guide customer interactions
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Industry Use cases-Financial Services-Healthcare-Retail-Government
2013
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Insurance
Claims Fraud
Customer Retention
Catastrophe Modeling
Banking
Optimize Offers and Cross Sell
Contact Center Efficiency
and Problem Resolution
Payment Fraud Detection & Investigation
Counterparty Credit Risk Management
Telco
Pro-active Call Center
Network Analytics
Location Based Services
IT/Network Infrastructure Transformation
Smarter Campaigns
Energy & Utilities
Smart Meter Analytics
Distribution Load Forecasting/Scheduling
Condition Based Maintenance
Create & Target Customer Offerings
Media & Entertainment
Business process transformation
Audience & Marketing Optimization
Multi-Channel Enablement
Digital commerce optimization
Retail
Actionable Customer Insight
Merchandise Optimization Playbook
Dynamic Pricing
Travel & Transport
Customer Analytics & Loyalty Marketing
Capacity & Pricing Optimization
Predictive Maintenance Analytics
Consumer Products
Optimized Promotions Effectiveness
Micro-Market Campaign Management
Real Time Demand Forecast
Government
Threat Prediction and Prevention
Social Program Fraud, Waste and Errors
Tax Compliance - Fraud and Abuse
Crime Prediction & Prevention
Healthcare
Measure & Act on Population Health
Engage Consumers in their Healthcare
Automotive
Data Warehouse Optimization
Predictive Asset Optimization (PAO)
Actionable Customer Intelligence
Connected vehicle
Life Sciences
Increase visibility into drug safety and effectiveness
Chemical & Petroleum
EDW Smart Consolidation & Augmentation
Operational Surveillance, Analysis & Optimization
Engineering & Operational Data Exploration & Mining
Aerospace & Defense
Uniform Information Access Platform
Data Warehouse Optimization
Predictive Asset Optimization (PAO)
Electronics / Industrial Products
Channel Driven Customer Analytics (CDCA)
Predictive Asset Optimization (PAO)
Big data & MDM use cases across industries
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Financial Services
2013
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Investment Services
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Role : Chief Marketing OfficerCompany : Portfolio InvestmentScenario : CMO trying to assess investment
opportunities based on Customer Life Trigger events
1. New Data segments identified by Data and market analysis women with 2 or more children between 8 and 12, family income is above $150,000/year, growing cash accounts, and a track record of large investments
2. CMO now has a subset of potential customers( from MDM) as targets and can drill down and look at individual profiles
3. Individual Customer Janet- her transaction history, contact information (including her masked credit cared number), twitter data and chat history, as well as structured information like contact and household details.
4. Data from unstructured sources show Janets propensity to invest in the future and data from MDM gives a solid foundation to trust the investment portfolio of Janet.
5. With all this information on a single page, the CMO is able to confirm the hypothesis of his team and make a confident decision
Data Sources
Customer profiles MDM
Janets contact & HH information
MDM
Recent transactions
Aggregated frommultiple sources
Customer Feed Email database
Product Portfolio MDM
Campaign Information
Campaign Database
Customer Sentiment
Social Media
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CMOs homepage
2013
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Candidate List from MDM
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Individual Customer page
2013
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Customer trusted Information from MDM
Transaction source from DE
Product info from MDM
Unstructured content fromCampaign Database
Customer feed from unstructured source
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HealthCare
2013
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Health care Scenario
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Role : Call Center RepCompany : Consumer oriented Healthcare Payer or ProviderScenario : Healthcare Rep gets a call on a particular Claim from a
consumer. The 360 view provides comprehensive and complete customer information
1. Using the trusted Information from MDM, a customer service rep is able to search for a customer and be sure that the system returns the right person
2. Customers information from other nonMDM sources such as a Claims Database and her recent transactions show the Representative a view of the latest information
3. A summary of Provider information, health Risk score and Clinical Data summary allows the representative to quickly assess any further medical analysis on this customer and claim in question
4. The rep is able to make notes and alerts based on this information to avoid future costs
5. Without the 360 view , the representative will have to access multiple systems to get similar information, while the customer waits on the call.
Data Sources
Customer Critical Information
MDM
Available Plans Plan Administrative System
Recent visits and transactions
Multiple sources aggregated
Clinical Data Summary
Clinical Data Hub
Health Risk Score SPSS
Providerinformaiton
MDM
Claims Information
Claims Database
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Conditions
EXCEL HEALTH
Hom
e
Jan Robertson Logged in as Juanita Ramos I Help
Claims
Date Facility Department Reason
2013-06-05
Peak Hospital Cardiology ED Referral
2013-06-05
Peak Hospital Emergency Dept Erratic heart beat
2013-06-02
Hill Physicians
General Practice Lethargy
2013-05-14
Dr Jones Assoc
Cardiology Routine check-up
Recent visits
Personal Information
Janet Robertson ID R3245632
Janet Davis-Robertson
3216 Norland Ave.Sacramento, CA [email protected]
Contact Information
Additional Profile
Sentiment History
Yelp
Excel Health Good, responsiveDr Jones Cardio: Poor, slow
Interactions
Provider Specialty
Mary Jacobs, MD Primary Care
Angela Tan, NP Wellness
Dr Andrew Jones Cardiology
Dr Bob van Eyck Geriatrics
Care team
Date Time Channel Interaction Resolution
2013-06-02 12:44 Provider Explanation of benefits
2013-06-03 21:20 Online Checked claim status
2013-06-04 14:22 Mobile Chat Claim question Resolved.
Customer
satisfied
2013-06-05 15:39 Text Outbound Text message - Verify
medication adherence
Verified
2013-06-05 21:16 Online Viewed Wellness products
2013-06-06 09:22 Email Inbound email. Customer
upset re co-pay amount
In queue
Id Amount Status Date
93 $323 Open 5/4/13
58 $4305 Paid 3/2/13
Risk Score
LV 77
Campaigns
Showing: All Interactions By Channel By Date By Author
Item/Time Action Detail
Complaint
email
09:22
Contact
provider
Household
Alerts
Name Date Channel
Heart First
2013-06-06 Outbound CC
Healthy Living
2013-04-15 Email
Plan Year Deduct
Medicare 65B 2013 - $147
PPO Gold 1K 2010 - 12 $1000
Chiro-Acu Plus 2011 - 12 N/A
Plan Information
Name Relationship
Mark Davis Spouse
June 06, 2013 09:23
Detail
Problems Allergies Medications Diagnostics
Heart Disease Penicillin Atorvastatin HbA1c = 6.6%
Diabetes Gemfibrozil LVEF = 49%
Metformin
Unstructured customer interaction data analyzed by BigInsights and updated in MDM
Clinical Summary from EHR / HIE / MDM Clinical HubHealth Risk Score calculated by SPSS on PDA
Plan info from Plan Administrative System
Householding Info from MDM
Consumer Info from MDM
Information from all sources aggregated by Data Explorer
Customers Physician Relationships from MDM
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Retail
2013
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Sporting Goods
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Role : Marketing ExecutiveCompany : Sporting Goods/RetailScenario : Assess market and product specific
information to make significant strategic decisions on products, direct marketing techniques and investment strategies
1. A quick overview of sales and marketing campaign shows decline in sales inspite of successful campaign
2. Data from multiple aggregated sources show consumer club has stopped Golf sale. The issue has been bubbled up to the attention of the executive and he can begin to understand why
3. A targeted marketing line called Golf Pro Bag shows all the information from MDM about this particular product. This gives confidence about the trustworthiness of the product and its associated attributes
4. Customer complaints and sentiments from other data sources expose a weatlh of information about this product
5. Using all this information, the executive can change the strategy about Consumer Club dropping the golf line and take corrective actions
Data Sources
Product Sentiment Vs Sales
Cognos BI reporting
ProductInformation
MDM
ProductTransaction
Aggregated transactionalsource
Customer support Customer Support Database
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Product info from MDM Product Transaction
history
Email related to the product
Cognos BI reporting against Sentiment Analysis
Retail Industry Use case
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Government
2013
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London XXX Council
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Role : Council WorkerCompany : London XXX councilScenario : Search for a particular citizen in that
council and get a 360 view of issues, complaints and resolutions, while providing a real time update on the citizen interaction with the system
1. The council worker searches for Dave Thatcher. The MDM system brings back a set of Citizen matching records.
2. Council worker can then select the right person and see all related trusted MDM information , including Householding
3. Clicking on the Household information shows all members related ( from MDM relationships) and other information such as maps pulled from external sources
4. Information from internal sources such as emails and SharePoint can also be linked on this page
5. The council worker can directly update the activity feed in real time and it will show up in his home page, which aggregates his contact list ( From MDM) Eg: Update of a phone complaint can be logged into this feed and will show up on the home page
Data Sources
Citizen name,contact and other information
MDM
Household Information
MDM
Emails, sentiment analysis
Sharepoint, email internal database
Customer issues Aggregated from multiple sourcesand shown as a graph
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Citizen Page
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Household Information
37 Go to 'View > Header and Footer' to change this footer text to the event title
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Home Page for Council worker
38 Go to 'View > Header and Footer' to change this footer text to the event title
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IBM InfoSphere MDM and InfoSphere Data Explorer combine to give a holistic view
InfoSphere Data Explorer
Find and navigate customer
information regardless of
format or where it is stored
Enable discovery and
navigation
Present a unified view,
combined with analytics
InfoSphere Master Data
Management
Ensure consistency and
accuracy of customer and
product data
Uncover relationship links in
customer information
Distribute trusted information
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THINK
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