CJ Nakamura & Vikram Anand | Cerner Health Services
September, 2015
Chief Data Officer
Center of Excellence
Develop an Enterprise CoE to Drive
Business Decision Making and Growth
hello
who
why
what
how
q&a
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who | a word about us
CJ Nakamura
Vikram Anand
Cerner Corporation
Siemens Healthcare
Medikin Healthcare
Synestesi Tech
Spark Notes
CampusCareerCenter
Okcupid.com
Merrill Lynch
Societe Generale
Harvard NYU ESE
Multi-Lingual
Chess Champ
Father of Two
Penn State Advisor
Cerner Corporation
Siemens Healthcare
Siemens CAD
ITC InfoTech
Illinois Tech NIE
Athletics Champion
Soccer Buff
Data Science
Father of One
#1 Health IT Company on the Planet
18,000 healthcare facilities in 31 countries
FY14 $3.4B Revs with 22,000 associates
#34 Most Innovative Global Companies –Forbes
Top 100 IT Best Places to Work –Computerworld
HQ’s in Kansas City MO and Malvern PA
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Pag
e 4
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Data Optimize
Data Gov
True Analytics
Performance
Exec Support
Culture
Velocity
People
Data Monetize
Tools
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1310231341_Standard - Cerner PPT template_v2.2 updated: 0115 © Cerner Corporation. All rights reserved.
This document contains Cerner confidential and/or proprietary information belonging to Cerner Corporation and/or its related affiliates which may not be reproduced or transmitted in any form or by any means without the express written consent of Cerner
1310231341_Standard - Cerner PPT template_v2.2 updated: 0115 © Cerner Corporation. All rights reserved.
This document contains Cerner confidential and/or proprietary information belonging to Cerner Corporation and/or its related affiliates which may not be reproduced or transmitted in any form or by any means without the express written consent of Cerner
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day 1 | tactical strategic
Drive increased efficiencies
Uncover new business opportunities
Attain corporate goals and vision
What is the impact to
decision making and
business outcomes with
poor quality and subjective
reports?
What is the risk of
continuously ignore ‘data’
without a clear vision,
strategy and leadership?
What are the costs to pull
large reports queries
requiring minutes vs.
seconds?
What are the risks
not to have an
enterprise data
governance in place?
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day 2 | value drivers
The level of maturity of adopting sophisticated business analytics and data science around data sets,
processes, policies and technologies varies greatly throughout companies. The business and
technology value drivers position corporations for enterprise CDO roll out models. Understanding
each LOB’s data management, quality, integrity and analytics maturity accelerates the CDO value prop.
Gartner
HIMSS Analytics
IBM IBV
Big 5 models
day 3 | business model
Today more than ever, organizations seek to establish an enterprise data vision, strategy and
leadership by appointing the emerging role of the Chief Data Officer (CDO). Wall Street expect
organizations to become data centric. Customers have no different expectations and attitudes towards
companies to build a data centric culture.
The
CDO
creates
and
coordinates enterprise data and
analytics strategies, roadmaps
and
governance
to
drive
maximum
business
value,
serving as the Data Quarterback
with a holistic data vision and
strategy leadership position for
the enterprise.
The CDO executes
“data into dollar” opportunities, optimize inefficient processes, and enrich data
with third party sources. Companies move from an era of reading hindsight data on what has
happened towards an era of Insight and Foresight to predicting, acting and preventing, creating a
Companies drive towards a
[real-time] evidence-based
and data-centric culture,
taking
on
cultural
transformational journey as
an
internal
Change
Management
initiative
transforming
associates
work flows, habits, beliefs,
and values. This mandate
continuously need support,
communication
and
direction
from
the
top
leadership.
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day 4 | implementation methodology
•
Project governance
•
Project charter
•
Project plan
•
Source systems
•
Hardware
•
Network
•
Data sources
•
Data content
•
Data formats
•
Data dictionary
•
Data standardization
•
Data capture
•
Extract, transform, and
load (ETL)
•
Data quality audit (DQA)
•
System testing
•
Performance testing
•
Go-live readiness
assessment
•
“Live in the Dark”
•
Validation of data
•
Go-live stabilization
•
System performance
•
Lessons learned
•
Transition to
production support
•
Expand data use
cases
•
Future state vision
•
Prioritized goals and
objectives
•
Business/use case
•
Business Analytics (BA)
organizational skills
•
Key Performance
Indicators (KPI)
•
Data profiling
•
Categorize data issues
•
DG roles and
responsibilities
•
Establish Chief Data
Office
•
Data access/security
•
Data stewardship
•
Data quality issues list
•
Data lineage / metadata
•
BI education and
certification
•
Manage data quality
issue list
•
CDO and Business
Analytics experience
deepen
•
Implement Data
Science model
•
Measure outcomes
•
Set priorities going
forward
•
CDO Business value
acceleration
•
Stakeholder analysis
•
Competing initiatives
•
Organizational impacts
•
Change resistance
assessment
•
Communication plan
•
Messaging
•
Project kick-off
•
Training plan
•
Policies and procedures
•
Communication
campaign
•
Adoption and
Enforcement metrics
•
Data stewardship
training
•
End user training
•
End user perceptions
•
Validation of adoption
and change
•
Engage Change issues
across LOB laggards
•
Enforce territorial
process owners
•
End user survey
•
Revise change
management plan
•
Leverage change
•
Celebrate project
deliverables and
milestones
Discover
Define
Develop
Adopt
Perform
EXECUTE
INTEGRATE
day 5 | show me the money
The ROI, NPV and IRR analysis measure tangible and intangible outcomes with a measurement
methodology and technique that are aligned with the executive sponsors. The below valuation
framework have proved the costs and benefits in measuring the program success.
Increased Revenue
due to incremental
value (e.g. Data
Monetization)
Improved Net
Promoter Score
(e.g., clients,
associates and
partners)
Data Acquisition
Costs (e.g. ingesting
and transmitting data
from sources)
Reduced Costs and
cost avoidance (e.g.
Data Optimization
initiatives)
Data Service Costs
(e.g. costs of
analyzing, reporting
and preparing)
Data Transformation
and Management
Costs (e.g. costs of
managing,
integrating, cleaning,
standardizing)
Gartner has defined business value for BI,
Analytics and Performance initiatives citing an
improvement of 5-10% topline growth and 3-8%
reduction in operating costs compared to
industry peers.
The Economist interviewed 752 senior execs at large multinationals,
validating a "strong link between financial performance and effective
use of data. Many companies are aware of the power of data, but are
not yet fully exploiting the data they collect. The survey findings
McKinsey analysis of more than 250 engagements over five
years has revealed that companies that put data at the center
of the marketing and sales decisions improve their marketing
return on investment (ROI) by 15 – 20 percent.
Nucleus states of organizations continuing to
make investments in robust analytics ROI case
found the average returns have been
increasing, reaching $13.01 for every $1 spent
in 2014 from just $10.66 in 2011.
“The median ROI for the projects that incorporated
predictive technologies was 145%, compared with
a median ROI of 89% for those projects that did
not. Update: 2011 study showed ROI for
predictive analytics at 250% ”
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20
day 7 | the roadmap
The CDO office suggests a few unique action steps in the
first months of existence. Some of the steps can overlap
each other but the tactical alignment is meant to give the
reader an insight of the tactical road map.
1.
Organize the Chief Data Office
2.
Drive Business Data Ownership
3.
Establish DG, DQ, MDM, DI, DP, DV
4.
Engage Data Communities
5.
Monitor & Enforce Data Governance
6.
Leverage full CDO value model
Tactical Scope
Deliver Pilot Value
Business Plan
Expand the Game
Financial Plan 2.0
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