Chief Data Officer Center of Excellence. Develop an Enterprise CoE to Drive Business Decision Making and Growth

Transcription

1 Chief Data Officer Center of Excellence Develop an Enterprise CoE to Drive Business Decision Making and Growth CJ Nakamura & Vikram Anand Cerner Health Services September, 2015

2 hello who why what how q&a 1

3 who a word about us Cerner Corporation Siemens Healthcare Medikin Healthcare Synestesi Tech Spark Notes CampusCareerCenter Okcupid.com Merrill Lynch Societe Generale Cerner Corporation Siemens Healthcare Siemens CAD ITC InfoTech CJ Nakamura Vikram Anand Harvard NYU ESE Multi-Lingual Chess Champ Father of Two Penn State Advisor Illinois Tech NIE Athletics Champion Soccer Buff Data Science Father of One 2

4 #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 #1 Most Admired Healthcare Company Fortune HQ s in Kansas City MO and Malvern PA 3

5 why 4

6 data silos 5

7 data gov 6

8 data chaos 7

9 lack of insights 8

10 People True Analytics Data Gov Exec Support Performance Tools Velocity Data Optimize Data Monetize Culture 9

11 what 10

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15 how 14

16 day 1 tactical strategic Drive increased efficiencies Uncover new business opportunities Attain corporate goals and vision What are the risks not to have an enterprise data governance in place? What are the costs to pull large reports queries requiring minutes vs. seconds? 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? 15

17 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 Technology vendors 16

18 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. 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. 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 competitive, smart and agile enterprise for optimal value and benefits to clients and partners. 17

19 day 4 implementation methodology Discover Define Develop Adopt Perform INTEGRATE Future state vision Prioritized goals and objectives Business/use case Business Analytics (BA) organizational skills EXECUTE 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 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 CHANGE 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 18

20 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. Data Acquisition Costs (e.g. ingesting and transmitting data from sources) Increased Revenue due to incremental value (e.g. Data Monetization) Data Transformation and Management Costs (e.g. costs of managing, integrating, cleaning, standardizing) Improved Net Promoter Score (e.g., clients, associates and partners) Data Service Costs (e.g. costs of analyzing, reporting and preparing) Reduced Costs and cost avoidance (e.g. Data Optimization initiatives) 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% 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 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 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 suggest that they should not delay." 19

21 day 6 stakeholder map 20

22 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 Financial Plan 2.0 Expand the Game Business Plan Deliver Pilot Value Tactical Scope 21

23 key success factors Executive alignment and support Establish enterprise Data Governance Business ownership with IT support Align on Policy enforcement Mission critical data Communication and Celebration strategy Dream big Start small Persistence & Patience 22

24 Each day data is left without a clear vision opportunities to boost client satisfaction, optimize operations and create revenue growth are missed out in the organization. - Anonymous Thank you Carl-Johan.Nakamura@Cerner.com Vikram.Anand@Cerner.com Certain trademarks, service marks and logos set forth herein are property of Cerner Corporation and/or its subsidiaries. All other non-cerner marks are the property of their respective owners. 23