This session will discuss how the master data management platforms are evolving to meet needs of digital economy. A modern master data management platform incorporates graph technology, infuses insights from the data using advanced analytics and ML, and offer big data scale performance in the cloud. Join this webinar to learn about these and other critical capabilities that power connected customer experience, compliance, and business alignment.

1. TOP 7 CAPABILITIES
FOR NEXT-GEN MDM
DATAVERSITY WEBINAR
Sponsored by RELTIO
January 31, 2019
2 PM Eastern / 11 AM Pacific
© 2019 The MDM Institute www.the-MDM-Institute.com

2. TOP 7 CAPABILITIES FOR NEXT-GEN MDM
1. Cloud scalability, flexibility
& elasticity
2. Microservices architecture
3. Graph technology
4. Big Data support incl
omnichannel interactions
5. ML/AI
6. Action enablement
7. Information governance &
compliance
(workflow + collaboration)
All enterprises need to better focus on next-gen MDM requirements as we
move from “system of record” to add “system of reference” & (ultimately)
move into “system of engagement”
Wherein relationship-driven analytics form the foundation of
MDM-innate, data-driven & context-driven “cognitive” applications
to fully enable the “digital enterprise”

3. CLOUD SCALABILITY, FLEXIBILITY & ELASTICITY
• During 2019, Cloud MDM will
continue to attract SMBs (+
increasingly large enterprises) to
achieve MDM benefits
• Such offerings will provide enticing
entry point (opex vs. capex, cost
effective POCs) + potential for
infinite elasticity + federated
architecture for geo-distributed orgs
• Native Cloud MDM must keep
advancing to meet mkt expectations
while concurrently such solutions’
pricing models will stress mega
software vendors’ EBITA
• Thru 2020-21, integration of on-
prem MDM with SaaS apps will
arrive via SFDC, SAP BBD, et al,
however, enterprises will wrestle w/
data integration issues between on-
prem & Cloud; concurrently, cloud-
native solutions must address
privacy & security concerns
• Enterprise reference data remains
an exception; concurrently, MDM-
enabled apps will migrate to public
Cloud
Cloud Economics –Compelling but challenging for customer &
employee data – key sales enabler, but must deliver business value
Strategic Planning Assumption

4. MICROSERVICES ARCHITECTURE
• MDM microservices range from CRUD
(create/read/update/delete) macro services
all the way down to applets for DG
consoles, identity resolution, etc. ;
concurrently, such microservices also
scale in size to BPM/RPA* objects such
as app pkg raw functionality (order-to-
cash)
• During 2019, mega MDM vendors will
increasingly build & market data-driven
apps that compete directly with mega
ERP & vertical industry app providers
• Through 2019-20, SaaS vendors will
struggle to provide integrated/native
MDM
• Select SaaS providers will finesse this issue
via strategic partnerships & investments in
MDM
• Graph DB technology is one area of focus
by all vendors to support the need for
managing & analyzing increasingly
complex relationships & hierarchies, in
turn which will enable data-driven
cognitive apps of all sizes & shapes
• By 2021, the market for data-driven
cognitive (MDM-innate) applications will
exceed that for MDM platform software
*BPM = Business Process Management
RPA = Robotic Process Automation
Microservices (“deconstructed MDM”) – De facto architecture
for modern data management apps
Strategic Planning Assumption

5. GRAPH TECHNOLOGY
• Graph is conceptually threatening MDM
due to ability to simplify complexity, but
also augmenting MDM & DG via UI &
Query
• Simpler modeling of complex
relationships yields more humanistic UI
for all concerned ... model agility +
extensibility enables users to easily &
quickly add new data dimensions,
hierarchies & linkages
• Querying of analytics via graph tech also
simplifies & turbocharges ability to query
(& discover) relationships critical to
“system of engagement”
• Majority of purist graph-specific
implementations are either (a) unable to
transact for high volume scalability in
operational mode or (b) primarily being
used as adjuncts to operational
mode/transactional MDM hubs to cross-
walk/analyze across domains
• As MDM evolves towards “master
relationship management”, analytical
upstarts from Graph world will
increasingly add operational capabilities
for performance & robustness
Graph Technology – Providing “missing link”
between domains + big data analytics + IoT
Strategic Planning Assumption

6. BIG DATA SUPPORT
-- INCLUDING OMNICHANNEL INTERACTIONS
• During 2019, 360° view of “X” will take on new
meaning due to “data blind spots” of traditional
MDM; enterprises will realize need to reconcile
social identity with corporate/household
identity to provide authoritative master data to
drive e-marketing & commerce within social
networks
• Thru 2019-20, next-gen MDM will address
“sphere of influence” to incorporate both
extended & non-obvious relationships to grow
share of wallet from individual to exo-ego
network as disruptive sales strategy (vs. ego-
centric marketing);“system of engagement”
will begin to surpass “system of record” for
most industries and use cases
• Through 2020, Big Data will continue to
repatriate itself into MDM fabric as yet
another source via registry overlays; mining
of Big Data to populate Social MDM &
perform entity matching on Big Data stores
will help provision 360° view of entity from
public, subscription & enterprise data
• By 2021, mobile location-based services
enhanced with location-specific customer
info will raise ante for e-commerce within &
outside major social networks
Big Data – innately requires both MDM & DG to be effective & sustainable;
Graph DB to enable supra layer onto multiple MDMs
Strategic Planning Assumption

7. MACHINE LEARNING/
ARTIFICIAL INTELLIGENCEI
• Not just raw data scalability, but also
human process scalability is enabled by
ML
• ML will augment (more than replace)
MDM+DG to provide increased agility
& scalability
• Areas where ML will be applied
include: data discovery & mapping,
entity resolution, relationship discovery
& mapping, taxonomy & ontology; &
governance & stewardship
• Most of currently-marketed classic DG
tools do not exist as integrated solutions
& also are lagging in “ML-guided”
stewardship
Machine Learning – Scalability, complexity & agility are only certain of
the problems increasingly being solved by machine learning (ML)
Strategic Planning Assumption

8. ACTION ENABLEMENT
• During 2019, MDM solution providers &
BPM/RPA solution providers will
moderately collide in market as former
acquire or build out BPM-centric MDM;
both camps will be challenged to unify
domains as there exist different
business processes for CDI & PIM
• Again, Graph DB technology will be
seen as the solution to domain cross-
walks & rule/data integration/analytics
• Thru 2019-20, however, BPM-centric
MDM will continue to suffer from BPM’s
traditional focus on modeling & not
executing MDM rules, as well as BPM-
centric vendors' ineffectiveness in
marketing against MDM-centric
vendors
• By 2021, all mega MDM & BPM/RPA
vendors will have overcome this
dogmatic bias as enterprise workflow
needs to execute within governance &
vice versa be able to execute MDM
workflows within BPM/RPA
Action Enablement – From the enterprise perspective, a complete
modern data management solution requires both Rules & Reference
Data to be applied across domains
Strategic Planning Assumption

9. INFORMATION GOVERNANCE & COMPLIANCE
(WORKFLOW + COLLABORATION)
• Through 2019, most enterprises will
struggle with enterprise DG while they
initially focus on customer, vendor, or
product
• Integrated enterprise-strength DG that
includes E2E data lifecycle will remain
elusive as most organizations turn to
lightweight glossaries with modest Data
Steward workflows to support devolved
autonomy & multi-disciplinary, bi-modal
teams
• During 2019-20, the majority of MDM
software & service providers will focus
on productizing such lightweight DG
frameworks while mega MDM software
providers struggle to link governance
process with process & data hub
technologies
Information Governance & Compliance – By 2021, mega vendor
DG solutions will finally move from “passive/CSV-level" mode to
“proactive/integrated" Data Governance mode
Strategic Planning Assumption

10. ACTION PLAN FOR 2019-20
• Promote MDM as essential business strategy with IT deliverables to
leverage high-value info used repeatedly across many business processes
• Position MDM as enabler of key business activities such as improving
customer communication & reporting – rather than an important
infrastructure upgrade
• Begin MDM projects focused on either customer-centricity or
product/service optimization
• Plan for next-gen MDM juggernaut evolving from “early adopter” into
“competitive business strategy” while preparing for “Master Relationship
Management” as digital transformation enabler
• Insist on Enterprise MDM software capable of evolving to multiple
usage styles & data domains
Plan now to realize economic value & competitive
differentiation via next-gen MDM during next 2-5 years
© 2019 The MDM Institute www.the-MDM-Institute.com

11. FUTURE IS “NOW”
All enterprises need to focus on next-gen MDM requirements
as we move from “system of record”
to add “system of reference”
& (ultimately) move into “system of engagement”
Relationship-driven analytics will form the foundation
of MDM-innate, data-driven & context-driven “cognitive”
applications to fully enable the “digital enterprise”
BOTTOM LINE

12. MODERN DATA MANAGEMENT
USE CASES
Ajay Khanna | Vice President, Marketing, Reltio

13. CONFIDENTIAL AND PROPRIETARY / 2
BRINGING MODERN DATA TECHNOLOGIES TOGETHER
A
Modern
Master Data
Management
Foundation
Multi-model
with Graph
Analytics &
Machine
Learning
Big Data
Scale &
Performance
Data as
a Service
Workflow &
Collaboration
Data-driven
Applications

14. CONFIDENTIAL AND PROPRIETARY / 3
IMPROVE
RECOMMEND
ALIGN & ANALYZE
Combine profiles with interactions used for
advanced analytics & machine learning
ORGANIZE
HOW A MODERN MDM PLATFORM WORKS
RECOMMEND & AUGMENT
Write-back aggregate profile attributes for
operational context & segmentation
REFINE
Trusted Enrichment
RECONCILE
Smart Matching
RELATE
Relationship Graphs
EVOLVE
Integrate with existing
Applications & Data Warehouses
ALL TEAMS
IT, sales, marketing,
compliance see and
collaborate on a single pool
of data, with full audit and
governance
PRODUCT 360
SUPPLIER 360
CONSUMER 360
ASSET 360
ACCOUNT 360
VISUALIZE &
COLLABORATE
Personalized Views
AGGREGATE
Unlimited Attributes
1
2
34

15. CONFIDENTIAL AND PROPRIETARY / 4
People
Organizations Products
People
Graph
Master Data
(Document)
Interactions
(via Flat files or APIs)
Reference Data
(Hierarchical)
MULTI-MODEL DATA APPROACH

16. CONFIDENTIAL AND PROPRIETARY / 5
MANAGING COMPLEX RELATIONSHIPS &
HIERARCHIES
USE CASES: MANAGING COMPLEX RELATIONSHIPS & HIERARCHIES
People
Organizations
Products Places
Legal Hierarchies Custom Hierarchies Teams & Committees Affiliations & Relationships
Product
Risk
Value
Alignments
● Uncover relationships
● Improve profile matching
● Find influencers
● Recommend products
● Suggest DQ improvements

17. CONFIDENTIAL AND PROPRIETARY / 6
INFUSING INSIGHTS VIA MACHINE LEARNING
Seamless MDM
& Advanced Analytics
Integration
Closed-loop
Data-driven Applications
Shared
Objects
Profile &
Omnichannel
Transaction Data
Reltio IQ
Data Steward
Data Scientist
Business User

18. CONFIDENTIAL AND PROPRIETARY / 7
USE CASES: CONTEXTUAL, RELEVANT INSIGHTS
People-Products-Places
Relationships
Next Best Action
Business Data Quality (Score, Rank)
Identify Data Issues

19. CONFIDENTIAL AND PROPRIETARY / 8
BRINGING ALL DATA TOGETHER

20. CONFIDENTIAL AND PROPRIETARY / 9
INCLUDING OMNICHANNEL TRANSACTIONS

21. CONFIDENTIAL AND PROPRIETARY / 10
USE CASE: TRUE CUSTOMER 360: ACTION ENABLEMENT
Operational
Analytical
Profiles
Recommendations
Insights
Preferences
Relationships

22. CONFIDENTIAL AND PROPRIETARY / 11
GOVERNANCE & COMPLIANCE
Data change requests (DCR), Match Review, Delete Requests
Reltio Cloud
Notify
Submit
request
Approve/
reject
Request more info

23. CONFIDENTIAL AND PROPRIETARY / 12
USE CASE: General Data Protection Regulation
• Discover GDPR data
– Data classification
– Identification of GDPR attributes
– Highlight potential GDPR data in free text
– Relate to consent
• Manage customer data
– Lineage of customer data
– Audit trail
– Quickly assess impact of individual data
requests
• Manage customer Requests

24. CONFIDENTIAL AND PROPRIETARY / 13
EXAMPLE INDUSTRY USE CASES
Life Sciences Reliable HCP (health care provider), HCO (health care organization) data.
Improve sales effectiveness, time to new product launch & better account management.
Uncover affiliations & relationships in real-time. Intelligent recommendations for sales reps.
Product 360 with compliance. Patient Experience.
Healthcare/
Insurance
Customer/Patient-centricity and better service.
Complete member 360° views with affiliations for payers and plans, retention effectiveness &
understanding of consumer life cycle. Reliable physician directories for CMS compliance.
Retail / CPG Digital transformation providing the optimal personalized omni-channel customer experience.
Understand consumers’ needs throughout the journey.
Householding, customer value, GDPR
Financial/
Insurance
Digital Transformation and customer experience.
Leverage data to deliver the right experience, create customized products for consumers.
Hi-tech Complete understanding of B2B accounts & account hierarchy for better sales effectiveness,
including territory alignment, rep compensation.
Supplier 360

25. CONFIDENTIAL AND PROPRIETARY / 14
LEADING DIGITAL ENTERPRISES ARE DATA DRIVEN
Make data the heart
of every decision
Organize data
of all types at unlimited
scale
Unify data sets
to deliver personalized
views
Infuse analytics into
every
business process
Continuously learn
about customers,
products & their
relationships

26. CONFIDENTIAL AND PROPRIETARY / 15
CREATING MEASURABLE BUSINESS VALUE
Increase business agility
Enhance customer experience
Improve ROI
Lower operational costs
Increase IT productivity
Enhance sales productivity
Decrease response times
Avoid fines & penalties
Increase customer confidence
Reduce
Compliance
Risk
Improve
Operational
Efficiency
Gain
Competitive
Advantage