Information Rich, Knowledge Poor: Overcoming Insurers’ Data Conundrum

Information rich, knowledge
poor
Overcoming insurer’s data
conundrum
November 2014

Contents
Key takeaways 3
State of the industry: Insurers are still information rich, knowledge poor 4
Executing the blueprint 8
The road ahead 17
Contacts 19
2 Copyright © 2014 Deloitte Development LLC. Deloitte Center for Financial Services | Information rich, knowledge poor | @DeloitteFinSvcs | All rights reserved.

Key takeaways
State of the
Industry
• Realizing data as a strategic
corporate asset is a key
differentiator for sustained
growth, efficiency and
compliance.
• However, current data models
are siloed, outdated and too
narrow to capitalize on modern
data management and
analytics.
Develop a
blueprint
• To surmount barriers to
enterprise-wide data
management (EDM) insurers
should develop a blueprint - a
flexible roadmap to balance
short-term objectives and long-term
vision.
Execute the
blueprint
 Assess maturity of data management
capabilities at the start, as well as
periodically, to plan next steps and track
progress
 Secure complete endorsement of top
executives and execute change
management
 Identify a data champion to lead the
initiative from the front
 Identify the business unit to initially
champion the EDM, in line with
overarching enterprise priorities
 Establish and socialize robust enterprise-wide
data governance framework
 Identify talent gaps and consider third
parties or non-industry sources while
incubating internal capabilities
 Ensure full alignment and compliance with
regulations and data privacy standards

State of the industry: Insurers are still
information rich, knowledge poor
“By prevailing over all obstacles and distractions, one may unfailingly arrive
at his chosen goal or destination..”
- Christopher Columbus

Enabling information as a strategic asset is emerging
as an affirmative obligation
Generating advanced insights from
data is now a key differentiator for
insurers
There is an urgency to harvest
and harness the valuable
insights embedded in
exponentially growing data
sources, speed and volumes
Regulators increasingly focus
on EDM as a foundational
element of effective
compliance reporting
The convergence of dynamics suggest that effective enterprise-wide data management
is likely becoming the key success factor for insurers.

Many insurers are still information rich, knowledge
poor
Data is the ‘life blood’ of insurers, but realizing its full value remains elusive
Challenges include:
Siloed, legacy
technology
architecture
Fragmented
governance
processes persist
Shortage of
appropriately
skilled
professionals,
both in-house
and externally
Outdated decision-making
frameworks
on how data is
managed and
consumed
Insurers have to adopt a holistic approach with a long-term vision instead of tweaking
existing systems and business models to elevate data as a strategic asset.

A blueprint can help, but the path is flexible
One size does not fit all
The blueprint should align with the firms strategic priorities and balance short-term
objectives and long-term vision.

Executing the blueprint
“The possibilities are unlimited once you decide to act and not react.”
- George Bernard Shaw

Enterprise Data Management (EDM) maturity
assessment helps determine a starting point
Full master data
integration to business
processes and system for
analytics
Master data management
implementation with
harmonization rules for
standardized data
domains
Processes exist for critical
areas; single version of
truth for critical master
data domains
IT and business
representation in
architecture decisions;
enterprise-wide consistent
data models
Integration at business-unit
level; changes to
architecture goes through
approval process
Local IT team owns
physical and logical data
models; limited integration
of tools
Enterprise-wide data
quality initiatives with
clear ownership; metrics
to measure progress
Consistent data quality
processes, standards, and
tools; centralized data
quality team
Data profile and baselines
established; data
cleansing on critical areas
No formal team recognized
to own the architecture;
point solutions
Data architecture
No consistent data
management processes;
multiple versions of truth
Master data
management
Enterprise-wide
standards; metrics to
assess performance
Cross-functional data
owners and data stewards
in a formal data
management organization;
consistent processes
Limited owners;
governance policies,
processes, and standards
exist for critical areas
No awareness; no formal
data owners or data
stewards
Data governance
Advanced
Defined
and
Predictive
Evolving /
Proactive
Controlled
No data quality processes
or standards; no data
profile or baseline
Data quality
Building an EDM is a multi-year journey with several maturity stages. Progression will
enable advanced insights that can drive decisions from operational to strategic.

A supportive ‘tone at the top’ and alliance across the
enterprise is foundational to success
Securing executive-and
board-level
endorsements are
the first steps
After establishing ‘tone at the top’ change
management initiatives are essential
Conduct workshops that unite business and IT leaders and middle management across the company
Set timelines and
priorities; incorporate
ROI into the blueprint
Communicate and
prioritize short- and long-term
goals of the program
Understand individual
business unit and function
requirements to incorporate
into the blueprint
Absent of high-level backing, data management initiatives will potentially stall or fail, as
line of business and functional teams independently assess the value and cost of
participation and compliance.

Identify and empower a data champion to kick-start
and drive the initiative forward
Data Champion
Often Chief Data Officer
(CDO)
Role 1
Co-ordinate the data
initiative between diverse
business operations,
functions, and IT
Role 2
Identify, shape, and
implement data
management strategies,
standards, procedures,
governance policies, and
enabling tools
Role 3
Elicit funding for all data
initiatives
The data champion (whether or not designated as the CDO) should be an influential
leader across the circles, empowered to execute the vision and plan.

Identify initial business to position data strategically;
align with firms’ strategic priorities
Optimally Positioned Business Functions Potential Strategic Priority
Holistic Customer View
Cost Control
Pricing/ Product
Development
Marketing
Finance
Uses data from all business lines, social media, and external-sources
for information on life stage, demographic, customer
sentiment to capitalize on customer relationships
Uses transactional data from across all lines and functions,
with minimal errors and lag time to generate company’s
books, records and additional analysis
Actuarial
& Under-writing
Uses products and claims related data from each of the
firms business operations, to maintain pricing discipline and
build better products
Perhaps opt for a preliminary strategy that is low in complexity or limited in scope, but
high in value – an ‘easy win’ that could potentially foster greater buy-in among doubters
in the organization.

Data champion establishes data quality and
governance controls for enterprise-wide deployment
Common
language
Continuous
communication
Enabling tools
& technology
Establish firm-wide standards for identification, definition,
adoption and maintenance of meanings, values, descriptions,
and uses for data elements across all business functions
Ownership and governance of data must be a cohesive
alignment between business and IT functions
CDO and IT collaborate to define a target technical environment
and enabling tools to operationalize data storage, aggregation,
accessibility, investigation, modeling, reporting and visualization
Effective and productive communication among all stakeholders along with robust
standardization of processes and terminology will potentially multiply the return on
investment.

Identify talent gaps and implement innovative
solutions
Talent Shortage
Challenge Solution
Talent pool with specialized data-related skills
is low, while demand is rising across all
industries and geographies
Dearth of skills is exacerbated by a general
lack of understanding for the varied
competencies required to reach advanced
maturity stages
Leverage skill-rich third parties to bridge
the immediate competency gaps while
the company incubates its own internal
capabilities
Design a multi-phase training program to
cultivate additional teams of solution
providers, as well as to help socialize
new processes and infrastructure among
the existing talent pool
Data scientists are the pilots who fly the plane, and their shortage is a real challenge
which requires innovative solutions.

And, don’t forget the regulators and the villains…
Legacy system modernization projects must be adapted to
accommodate regulation-driven data aggregation and
processing requirements
Business and IT functions must collaborate with the CDO
to ensure flexibility and capability to meet compliance
obligations
Insurers will be required to demonstrate both financial
benefits of ‘opting in’ and the ongoing security of their
disclosed PII to ensure data privacy
As cybercrime transforms, insurers must remain vigilant
and proactive in development and maintenance of secure
data environments
Business and IT functions must collaborate closely with one another and with the CDO/
DMO to help ensure that the flexibility and capability needed to meet external
compliance and data privacy obligations is put in place.

The Road Ahead
“It's difficult to imagine the power that you're going to have when so many
different sorts of data are available.”
-Tim Berners-Lee

The road ahead
“It's difficult to imagine the power that you're going to have when so many
different sorts of data are available.” -Tim Berners-Lee
Information Rich Knowledge Rich
Data
?
?
? ?
Data
Best Practices
 Develop a blueprint
 Assess the process
maturity
 Identify data
champions
 Get executive buy-in
 Identify pilot function –
align with strategic
priorities
 Build and socialize
data governance
 Ensure compliance

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Contacts
Executive Sponsor
Bertha Fortney
Director
Market Development
Deloitte Services LP
+1 203 918 3920
bfortney@deloitte.com
Industry leadership
Gary Shaw
U.S. Insurance Leader
Deloitte LLP
+1 973 602 6659
gshaw@deloitte.com
Deloitte Center for Financial Services
Jim Eckenrode
Executive Director
+1 617 585 4877
jeckenrode@deloitte.com
Sam Friedman
Research Leader, Insurance
+1 212 436 5521
samfriedman@deloitte.com
Subject Matter Specialists
Marc Zimmerman
Director and Co-Leader
FSI Analytics & Information Management Practice
Deloitte Consulting LLP
+1 203 905 2826
mzimmerman@deloitte.com
Arun Prasad
Principal
+1 212 618 4561
aprasad@deloitte.com
Jojy Mathew
Principal
+1 609 520 2362
jojymathew@deloitte.com
Andrew Liakopoulos
Principal
+1 312 486 2777
aliakopoulos@deloitte.com

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Information Rich, Knowledge Poor: Overcoming Insurers’ Data Conundrum

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