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Data Management Planning & Analysis Summit
San Francisco, The Palace Hotel, 8/15 & 16, 2011




Keynote: Competitive Advantage
  Through Data Management
Terry Jabali, Chief Information Architect / Managing Director
Applied Enterprise Dynamics, Inc.
889 Menker Ave, San Jose, CA, 95128
tjabali@pmoiq.net
(408) 644-8565
OBJECTIVES


                                        1.   Overview of key trends and practices
                                        2.   Use cases and discussion




© Terry Jabali; tjabali@pmoiq.net
INDUSTRY
                                    BENCHMARKS




© Terry Jabali; tjabali@pmoiq.net
data issues
                             Area                                   Benchmark
                             People can't find the data they need   Knowledge workers spend 30% of their
                                                                    time searching data they need,
                                                                    unsuccessfully half the time.
                             Incorrect data                         10-25% of data record contains
                                                                    inaccuracies.
                             Poor data definition                   Data frequently misinterpreted, can't
                                                                    connect data from different
                                                                    departments.
                             Data inconsistency across sources      The norm when there are multiple
                                                                    databases.
                             Too much data                          Half of all data never used for anything,
                                                                    uncontrolled redundancy.
                             Organizational confusion               Can't answer basic questions such as:
                                                                    How much created each day?
                                                                    Which are most important
                                                                                        Source: CIO Zone
© Terry Jabali; tjabali@pmoiq.net
trends
                               Benchmarks
                               •    Enterprise data will grow about 650% over the next five years
                               •     Employers will allow in workplace the use of Wikis, Twitter, or Facebook, to
                                    communicate for business
                               •    Companies are unifying as much of their communications as possible
                               •    More and more people are utilizing applications for mobile and wireless
                                    applications
                               •    Mashups created by users are also something that IT has to manage
                                                                            Source: Excerpt from the Top 10 Trends, CIO/Gartner, 2009




            IMPACT: enterprise processes, data
            capture, measurement & analytics
© Terry Jabali; tjabali@pmoiq.net
cost of bad data?
                             85 percent of survey respondents             For one-fifth of them, losses were in
                             agreed that their organizations              excess of an astounding $20 million
                             "treat information as a strategic            per year.
                             asset
                             More than four out of five (82 percent)      While many IT and line-of-business
                             of respondents agreed that "bad              executives in the survey agreed that
                             information leads to costly mistakes by      information in their organizations has its
                             business managers                            problems, they differ widely on where
                                                                          and why these data quality issues exist
                             79 percent of IT managers surveyed said      fragmented data ownership" is the single
                             data-quality responsibility was theirs       biggest roadblock to a successful
                             AND                                          enterprise information management
                             74 percent of the finance, sales and         program; this differing perspective puts IT
                             marketing respondents said it their job to   and business executives in conflicting
                             ensure data quality.                         camps
                             51 percent of their companies were           But just 25 percent of business
                             engaged in data quality management           executives reported that their companies
                             work                                         had similar projects
                                                                   Source: Gartner
© Terry Jabali; tjabali@pmoiq.net                                  200 executives at companies with more than $500 million in revenues
investments and competitive
      advantage
   “At a time when companies in many industries offer similar products
   and use comparable technology, high-performance business
   processes are among the last remaining points of differentiation.”
                                             Tom Davenport, “Competing on Analytics”


                                                                       Ten Most Important Visionary Plan Elements
                                                                  Interviewed CIOs could select as many as they wanted

BI/Analytics                       Business Intelligence and Analytics                                                                          80%
                                                                                                                                                       86%



#1                                                         Virtualization
                                                                                                                                             77%
                                                                                                                                            76%


investment to                        Risk Management and Compliance                                                                  70%
                                                                                                                                        73%



improve                                                Mobility Solutions                                                      66%
                                                                                                                                      71%



competitiven                       Customer and Partner Collaboration                                                         64%
                                                                                                                                          73%



ess                                                Self-Service Portals                                                   63%
                                                                                                                                      71%

                                                                                                                                                   Low
                                             Application Harmonization                                                   62%
                                                                                                                                67%
                                                                                                                                                   growth
                                                                                                                                     70%
                                       Business Process Management                                                      61%                        High
                                                                                                                                    68%
                                                                                                                                                   growth
                                                    SOA/Web Services                                             55%

                                                                                                                          63%
                                                 Unified Communication                                            57%

                                                                                          7
Source: IBM Global CIO Study 2009; n = 2345 (slide contributed by Perficient)
evolutions

                                                              IMPACT:
                                                              enterprise
                                                              processes,
                                                              data capture,
                                                              measurement
                                                              & analytics



                                                 Source:
© Terry Jabali; tjabali@pmoiq.net                Technology services industry association
PLANNING &
                                    EXECUTING
                                    use cases and
                                    discussion of
                                    underlying
                                    foundational elements




© Terry Jabali; tjabali@pmoiq.net
processes and inter-dependencies
                                     continue to evolve

                        Follow the Customer:
                                                                          Phone
                                    Ex. 1: Self-service and             support
                                    social networks are in a
                                    state of convergence        Self-
                                                               service

                                                                             Social Media


        How can an organization plan and
        execute in an era of convergence?
© Terry Jabali; tjabali@pmoiq.net
foundation: process & data maturity
                                                   PROCESS                     DATA


                                                           Optimized   Governed
                                                                       • Governance,
                                                                         monitoring,
                                                                         continuous improv.
                                              Quantitatively Managed
                                                                       Proactive
                                                                       • Data definition,
                                         Defined                         taxonomy ,
                                                                         cleansing

                                                                       Reactive
                               Managed
                                                                       • Sporadic data fixes

                                                                       Undefined
            Initial                                                    • Data is not defined
Copyrights CMMi®)
© Terry Jabali; tjabali@pmoiq.net
                                          Inventory of processes and data
impetus for analytics                                  Optimal
                                                                                      Performance Point




                                                                                           Defined and
                                                                                           Measured
                                                                       Process             (include customer
                                                                                           touch-points)
                                               Optimized



                                     Quantitatively
                                     Managed
                                                              Data              Metrics
                               Defined                        (& systems)




          How do organizations                             Validated and
                                                           Proactively
                                                                                      Profiled and
                                                                                      Cleansed
          ensure metrics                                   Reported

          accuracy?
© Terry Jabali; tjabali@pmoiq.net                                       BI, EDW, DM
process+data+metrics+DQ in action
                                                                Improves
                                                            Improvement Loop

                                                                                                Perfect Order
                                                                                                     (L1)

                                             1.Process      Transactions                           % orders not
                                              Order entry     Sales order      3. Metrics            touched
                                              Scheduling      Shipments
                                                                                WHO: QTC               OTS
                                                                                 Mfg Ops



                                                                                                Drives
                                                            Data Quality and
                                                              Governance
                                      Analytics                                            2. Data
                                                                1.   Profile                BDOs
                                                                2.   Cleanse
                                                                3.   Monitor      Sales Order       Inventory Org
                                                                4.   Govern
                                                                                    Product             Time



© Terry Jabali; tjabali@pmoiq.net
actionable analytics
                                    (simplified view)


                                                        Process and data scopes
                                                              defined E2E

                                                        Processes qualitatively &
                                                        quantitatively measured
                                                                (100%)

                                                          Data governed and
                                                              integrated


                                                          Data standardized/
                                                              validated




                                                            Actionable
                                                             Analytics


© Terry Jabali; tjabali@pmoiq.net
100%: data should provide the full
                                        picture
                                                                                                            •Analytics
                                                                                                             should
                                                   Customer Cases by Category
                                                                                                             provide easy
                                        400
                                        350
                                        300
                                                                  80.8%
                                                                                 92.0%     96.5%   100.0%
                                                                                                   90.0%
                                                                                                   80.0%
                                                                                                   70.0%
                                                                                                             information of
                                                                                                             “what to do”?
                                        250                                                        60.0%
                                Total




                                              186 46.5%
                                        200           137                                          50.0%
                                        150                                                        40.0%
                                                                                                   30.0%
                                        100
                                         50
                                                                     45
                                                                                      18     14
                                                                                                   20.0%
                                                                                                   10.0%    I need to improve:
                                          0                                                        0.0%
                                                                                                            1. Performance and
                                                                                                                Quality (drilldown)
                                                                                                            2. Application
                                                                                                                Intuitiveness
                                                Resolved Customer Cases for Q1/Q209
                                                         Source: DCT Alliance cases


                                                                                                                (drilldown)
                                                                Source: Alliance customer support cases     3. Application
                                                                                                               Functionality
                                                                                                                (drilldown)
© Terry Jabali; tjabali@pmoiq.net
(use case:          validation: Q-scorecard
        mapping)
                                                                                                                                                Weight
                                     Frequenc                                     Source System                    Target System                   %
Data Quality Data                    y of                   Expected      (define SOR, Up/Down stream)    (define SOR, Up/Down stream)          Allocati
Filters           Metric             Metric   Data Standard Behavior                  INBIZ                            QMX                Delta    on
          Select
     appropriate                                                                     Record                                              (define
 filter category                                                       Field         value  Table        Field         Record Table      value)
       Accurate
      Consistent
        Relevant
          Timely
            Valid
                                                   99%: PCA
            # of PCA                          created with #
            records created                   of goal value in                                                                          -
            in Pact without                            target          CPN                  MTL_SYSTEM_I                     QMx PCA 985.00
  Complete 1a goal in QMx Weekly                                       (Segment 1)      2653TEMS_B       PCA                 Master                50.00%
             # of QMx                                                                                                                   -
            records not in                     99%: (“ not in          QMx PCA                           CPN                 MTL_SYSTE 987.00
  Complete 2Pact            Weekly                   source)           Master           2812PCA          (Segment 1)     2653M_ITEMS_B             50.00%

                                                                                                                              Confidence Score      0.6389
                       If PCA item number is in PACT however not in                  +/- 2%=alert
                                                                                                             CONFIDENCE SCORE = 64%
                       QMx, return an exception (also return an
                       exception of missing count)
 DESIGN                If QMX yield is set, however, PCA is not in
 EXPERIMENT            PACT, return an exception (quality rule)

                                                  Monitoring dash



 © Terry Jabali; tjabali@pmoiq.net
(use case)
                         governance & analytics

                                          “Direct the
                                          Business”
                                          Executive
                                          Metrics
                   Metric /
                   Reporting            “Manage the                • Performance
                   Trustees                                          Analytics
                                        Business”
                                        Analytical
BI , Strategy                           Reports & Metrics
and Data
Governance                              “Run the Business”
                                        Operational Reports &
                                        Metrics
                                       Process Excellence

                   Data
                   Architecture     Data Architecture & Metadata


                   Data Quality
                   (Trustees,                                      IT / Data
                                           Data Sources
                   Stewards)                                       Custodians



Data management spans the entire information delivery
lifecycle, enabling a consistent, reliable source of truth for
metrics, analysis and reporting
(use case)
                                    mdm governance & analytics
                                                            Enterprise Governing Councils

                                                Business Intelligence Data Services )
                                                                                                                             • MDM is concerned with
                        Enterprise BI org                                                                                      Single Source of Truth

                                                   DMSC
                                                     Enterprise Data Management Office
                                                    Enterprise Data Management Office                                          (SSOT) and increasingly
                                                    (EDMO)
                                                                                                                               with data stewardship;
                                                                                                                               AND,
                                                                                                                             • Data definition and




                                                                                                         Custodian)
                                                                                                         (Data
                                                                                                         re Team
                                                                                                         Architectu
                                                                                                         IT
                        Functional BI org             Data Governance Program
                                                                                                                               standards for quality of
                                                   BI center of excellence
                                                                                                                               transactions
                        Functional Ops
                                       Transformation Office
                                                                                                                             • Processes are adequately
                        org                                                                                                    defined to serve




                                                                                                           Enforcers
                                                                                                           Policy Makers &
                                       (Advanced Value chain solutions - Process Excellence - TBD)
                        (unassigned)
                                                                                    Trustee                                    customers and partners
                                                                                    Data
                                                                         Stewards
                                                                         Metrics




                                                                                              Stewards
                                                                                              Data
                                                Trustees
                                                Metrics
                                                Executive


                                                             Trustee
                                                             Metrics




                        Functional BI
                        org (as driver)
                                                                                                                             • Data governance is


                                                                                                            Audience
                                                                                                            Policy
                                             Functional Groups                                                                 adopted: data quality,
                                             Information users, Data subscribers
                                                      (Voice of the Customer/Metrics)                                          ownership and
                                                                                                                               accountability

            • Analytics is ultimately concerned with insights: customers, partners,
              internal operations, human capital, regulatory compliance…
© Terry Jabali; tjabali@pmoiq.net
The Way Forward




© Terry Jabali; tjabali@pmoiq.net
imperatives for data analytics

            1.            Adopt a maturity model and assess
                          current state of processes and data        “Bad data stymie
            2.            Define processes: purpose, policy,         analytics and "big
                                                                     data." You simply can't
                          tasks…                                     trust the insights
                                                                     when you can't trust
            3.            Define the E2E success metrics for         the inputs. “
                          combined tasks of the process              Thomas C. Redman

            4.            Define data source from task to            Harvard Business Review Blog


                          process
            5.            Apply data quality standards: profile,
                          cleanse, standardize

© Terry Jabali; tjabali@pmoiq.net
                                    Set S.M.A.R.T. targets to evolve maturity
imperatives for program execution

                1.            Adopt a pragmatic approach by
                              focusing on one to two key business
                              problems
                2.            Build the business case and secure
                              cross-functional sponsors
                3.            Establish a governance framework and
                              manage adoption starting with a quick
                              win (socialize)
                4.            Ensure a balanced team make-up:
                              process SME, Data Architect, DBA,
                              Metrics SME…
                5.            Assign a dedicated PM to drive the
                              proof of concept
© Terry Jabali; tjabali@pmoiq.net
Thank you
                                    Your turn…




© Terry Jabali; tjabali@pmoiq.net                22
BIO


   About the presenter: Terry Jabali
    tjabali@pmoiq.net
    (408) 644-8565
    Terry has over 20 years in operational excellence and information leadership with emphasis on BI, MDM, CRM, and
    Analytics. He is the Chief Information Architect at Applied Enterprise Dynamics, Inc. (AED), a consulting and
    software firm retained at Cisco Systems and NetApp. He leads initiatives and advises on MDM, Six Sigma, data and
    quality governance, metrics and analytics as well as service delivery modeling. Prior to AED, he was the CRM Practice
    Head for North America at ClarifyCRM, Principal at Computer Sciences Corporation (CSC), CRM Practice Director
    at Cedars (Peoplesoft), and a Leadership Development Director at American Society for Training and Development
    (ASTD-RMC). Terry earned his B.A. degree in Applied Behavioral Sciences and completed graduate work in System
    Dynamics at Massachusetts Institute of Technology (MIT) and Organization leadership at Stanford. He holds several
    industry certifications including Six Sigma Master Black Belt, CM, CPC, among others.
    Terry speaks at industry conferences and recently served as a Technology Director at PMI, Program Management
    Office (PMO) SIG, a certification panelist for program management (PgMP) and risk management (RMP), impacting
    200,000 worldwide members. He is published in several trade journals:
    Data Governance: http://dqgassociation.blogspot.com/
    CRM leadership: Relationship Dynamics Feature: The Savior of CRM
    PMO best practices: http://blogs.ittoolbox.com/cio/pmo/
    Initiative Leadership: IntelligentCRM: Key Imperatives for Success
    IntelligentCRM | Feature | E-Intelligence and the Agile Enterprise
value-add mapping
use case   why data governance?
           New business opportunities                       Information Week

           State of the art customer service                ‘The information Challenge’

           Managing Risk and Compliance

           Meaningful decision guidance models                      47% of users don’t
                                                                     have confidence
           Reducing operating costs                                  in their information


              Effectiveness of the organization to drive

           Reliable, secure, accessible                             59% of managers don’t
           and usable data                                          use information
                                                                    they should have used
           Data fit for business purpose
           Ability to align interdependencies of

             People           Processes      Technologies
                                                                    42% of managers use
           Across the organization                                   wrong information
                                                                     at least once
                                                                     a week

           Effective Data Governance Program
BC slide



use case                           data governance structure (major manuf)
                                                      Enterprise Governance Councils
                                                                                                                 Governance body will
                                                               Enterprise DMO                                      enable following:
                                                     Business Intelligence Data Services                         •   Establish a common
                                                                                                                     business language and
                                                    BI Center of Excellence / BI Council                             quality processes
                                                      Data Management Office (DMO)
                                                                                                                 •   Resolve cross-functional
                                                                                                                     definition issues
                                                                                                                 •   Approve documentation
                                                                                                                     of standards
                                                                                                                 •   Approve targets for
                                                                                                                     quality measures
                                                                                                                 •   Facilitate culture change
       Policy Makers & Enforcers




                                                                                                                     for data quality and data
                                                                                                                     accountability
                                                                                              Executive Metric
                                     Data Steward /                                               Trustee
                                                               Data Trustee /                   (Dashboard)
                                    Data Custodian /           Metric Trustee
                                    Metrics Steward
                                                  Metrics Steering Committee
                                                                                                                 Quality of analytics
                                             Data Management Steering Committee
    Policy Audience




                                                              Transformation Office
                                            (Advanced Value chain solutions - Process Excellence - TBD)

                                                       Information users / Data Subscribers

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Competitive advantage through data management terry jabali v.01

  • 1. Data Management Planning & Analysis Summit San Francisco, The Palace Hotel, 8/15 & 16, 2011 Keynote: Competitive Advantage Through Data Management Terry Jabali, Chief Information Architect / Managing Director Applied Enterprise Dynamics, Inc. 889 Menker Ave, San Jose, CA, 95128 tjabali@pmoiq.net (408) 644-8565
  • 2. OBJECTIVES 1. Overview of key trends and practices 2. Use cases and discussion © Terry Jabali; tjabali@pmoiq.net
  • 3. INDUSTRY BENCHMARKS © Terry Jabali; tjabali@pmoiq.net
  • 4. data issues Area Benchmark People can't find the data they need Knowledge workers spend 30% of their time searching data they need, unsuccessfully half the time. Incorrect data 10-25% of data record contains inaccuracies. Poor data definition Data frequently misinterpreted, can't connect data from different departments. Data inconsistency across sources The norm when there are multiple databases. Too much data Half of all data never used for anything, uncontrolled redundancy. Organizational confusion Can't answer basic questions such as: How much created each day? Which are most important Source: CIO Zone © Terry Jabali; tjabali@pmoiq.net
  • 5. trends Benchmarks • Enterprise data will grow about 650% over the next five years • Employers will allow in workplace the use of Wikis, Twitter, or Facebook, to communicate for business • Companies are unifying as much of their communications as possible • More and more people are utilizing applications for mobile and wireless applications • Mashups created by users are also something that IT has to manage Source: Excerpt from the Top 10 Trends, CIO/Gartner, 2009 IMPACT: enterprise processes, data capture, measurement & analytics © Terry Jabali; tjabali@pmoiq.net
  • 6. cost of bad data? 85 percent of survey respondents For one-fifth of them, losses were in agreed that their organizations excess of an astounding $20 million "treat information as a strategic per year. asset More than four out of five (82 percent) While many IT and line-of-business of respondents agreed that "bad executives in the survey agreed that information leads to costly mistakes by information in their organizations has its business managers problems, they differ widely on where and why these data quality issues exist 79 percent of IT managers surveyed said fragmented data ownership" is the single data-quality responsibility was theirs biggest roadblock to a successful AND enterprise information management 74 percent of the finance, sales and program; this differing perspective puts IT marketing respondents said it their job to and business executives in conflicting ensure data quality. camps 51 percent of their companies were But just 25 percent of business engaged in data quality management executives reported that their companies work had similar projects Source: Gartner © Terry Jabali; tjabali@pmoiq.net 200 executives at companies with more than $500 million in revenues
  • 7. investments and competitive advantage “At a time when companies in many industries offer similar products and use comparable technology, high-performance business processes are among the last remaining points of differentiation.” Tom Davenport, “Competing on Analytics” Ten Most Important Visionary Plan Elements Interviewed CIOs could select as many as they wanted BI/Analytics Business Intelligence and Analytics 80% 86% #1 Virtualization 77% 76% investment to Risk Management and Compliance 70% 73% improve Mobility Solutions 66% 71% competitiven Customer and Partner Collaboration 64% 73% ess Self-Service Portals 63% 71% Low Application Harmonization 62% 67% growth 70% Business Process Management 61% High 68% growth SOA/Web Services 55% 63% Unified Communication 57% 7 Source: IBM Global CIO Study 2009; n = 2345 (slide contributed by Perficient)
  • 8. evolutions IMPACT: enterprise processes, data capture, measurement & analytics Source: © Terry Jabali; tjabali@pmoiq.net Technology services industry association
  • 9. PLANNING & EXECUTING use cases and discussion of underlying foundational elements © Terry Jabali; tjabali@pmoiq.net
  • 10. processes and inter-dependencies continue to evolve Follow the Customer: Phone  Ex. 1: Self-service and support social networks are in a state of convergence Self- service Social Media How can an organization plan and execute in an era of convergence? © Terry Jabali; tjabali@pmoiq.net
  • 11. foundation: process & data maturity PROCESS DATA Optimized Governed • Governance, monitoring, continuous improv. Quantitatively Managed Proactive • Data definition, Defined taxonomy , cleansing Reactive Managed • Sporadic data fixes Undefined Initial • Data is not defined Copyrights CMMi®) © Terry Jabali; tjabali@pmoiq.net Inventory of processes and data
  • 12. impetus for analytics Optimal Performance Point Defined and Measured Process (include customer touch-points) Optimized Quantitatively Managed Data Metrics Defined (& systems) How do organizations Validated and Proactively Profiled and Cleansed ensure metrics Reported accuracy? © Terry Jabali; tjabali@pmoiq.net BI, EDW, DM
  • 13. process+data+metrics+DQ in action Improves Improvement Loop Perfect Order (L1) 1.Process Transactions % orders not Order entry Sales order 3. Metrics touched Scheduling Shipments WHO: QTC OTS Mfg Ops Drives Data Quality and Governance Analytics 2. Data 1. Profile BDOs 2. Cleanse 3. Monitor Sales Order Inventory Org 4. Govern Product Time © Terry Jabali; tjabali@pmoiq.net
  • 14. actionable analytics (simplified view) Process and data scopes defined E2E Processes qualitatively & quantitatively measured (100%) Data governed and integrated Data standardized/ validated Actionable Analytics © Terry Jabali; tjabali@pmoiq.net
  • 15. 100%: data should provide the full picture •Analytics should Customer Cases by Category provide easy 400 350 300 80.8% 92.0% 96.5% 100.0% 90.0% 80.0% 70.0% information of “what to do”? 250 60.0% Total 186 46.5% 200 137 50.0% 150 40.0% 30.0% 100 50 45 18 14 20.0% 10.0% I need to improve: 0 0.0% 1. Performance and Quality (drilldown) 2. Application Intuitiveness Resolved Customer Cases for Q1/Q209 Source: DCT Alliance cases (drilldown) Source: Alliance customer support cases 3. Application Functionality (drilldown) © Terry Jabali; tjabali@pmoiq.net
  • 16. (use case: validation: Q-scorecard mapping) Weight Frequenc Source System Target System % Data Quality Data y of Expected (define SOR, Up/Down stream) (define SOR, Up/Down stream) Allocati Filters Metric Metric Data Standard Behavior INBIZ QMX Delta on Select appropriate Record (define filter category Field value Table Field Record Table value) Accurate Consistent Relevant Timely Valid 99%: PCA # of PCA created with # records created of goal value in - in Pact without target CPN MTL_SYSTEM_I QMx PCA 985.00 Complete 1a goal in QMx Weekly (Segment 1) 2653TEMS_B PCA Master 50.00% # of QMx - records not in 99%: (“ not in QMx PCA CPN MTL_SYSTE 987.00 Complete 2Pact Weekly source) Master 2812PCA (Segment 1) 2653M_ITEMS_B 50.00% Confidence Score 0.6389 If PCA item number is in PACT however not in +/- 2%=alert CONFIDENCE SCORE = 64% QMx, return an exception (also return an exception of missing count) DESIGN If QMX yield is set, however, PCA is not in EXPERIMENT PACT, return an exception (quality rule) Monitoring dash © Terry Jabali; tjabali@pmoiq.net
  • 17. (use case) governance & analytics “Direct the Business” Executive Metrics Metric / Reporting “Manage the • Performance Trustees Analytics Business” Analytical BI , Strategy Reports & Metrics and Data Governance “Run the Business” Operational Reports & Metrics Process Excellence Data Architecture Data Architecture & Metadata Data Quality (Trustees, IT / Data Data Sources Stewards) Custodians Data management spans the entire information delivery lifecycle, enabling a consistent, reliable source of truth for metrics, analysis and reporting
  • 18. (use case) mdm governance & analytics Enterprise Governing Councils Business Intelligence Data Services ) • MDM is concerned with Enterprise BI org Single Source of Truth DMSC Enterprise Data Management Office Enterprise Data Management Office (SSOT) and increasingly (EDMO) with data stewardship; AND, • Data definition and Custodian) (Data re Team Architectu IT Functional BI org Data Governance Program standards for quality of BI center of excellence transactions Functional Ops Transformation Office • Processes are adequately org defined to serve Enforcers Policy Makers & (Advanced Value chain solutions - Process Excellence - TBD) (unassigned) Trustee customers and partners Data Stewards Metrics Stewards Data Trustees Metrics Executive Trustee Metrics Functional BI org (as driver) • Data governance is Audience Policy Functional Groups adopted: data quality, Information users, Data subscribers (Voice of the Customer/Metrics) ownership and accountability • Analytics is ultimately concerned with insights: customers, partners, internal operations, human capital, regulatory compliance… © Terry Jabali; tjabali@pmoiq.net
  • 19. The Way Forward © Terry Jabali; tjabali@pmoiq.net
  • 20. imperatives for data analytics 1. Adopt a maturity model and assess current state of processes and data “Bad data stymie 2. Define processes: purpose, policy, analytics and "big data." You simply can't tasks… trust the insights when you can't trust 3. Define the E2E success metrics for the inputs. “ combined tasks of the process Thomas C. Redman 4. Define data source from task to Harvard Business Review Blog process 5. Apply data quality standards: profile, cleanse, standardize © Terry Jabali; tjabali@pmoiq.net Set S.M.A.R.T. targets to evolve maturity
  • 21. imperatives for program execution 1. Adopt a pragmatic approach by focusing on one to two key business problems 2. Build the business case and secure cross-functional sponsors 3. Establish a governance framework and manage adoption starting with a quick win (socialize) 4. Ensure a balanced team make-up: process SME, Data Architect, DBA, Metrics SME… 5. Assign a dedicated PM to drive the proof of concept © Terry Jabali; tjabali@pmoiq.net
  • 22. Thank you Your turn… © Terry Jabali; tjabali@pmoiq.net 22
  • 23. BIO  About the presenter: Terry Jabali tjabali@pmoiq.net (408) 644-8565 Terry has over 20 years in operational excellence and information leadership with emphasis on BI, MDM, CRM, and Analytics. He is the Chief Information Architect at Applied Enterprise Dynamics, Inc. (AED), a consulting and software firm retained at Cisco Systems and NetApp. He leads initiatives and advises on MDM, Six Sigma, data and quality governance, metrics and analytics as well as service delivery modeling. Prior to AED, he was the CRM Practice Head for North America at ClarifyCRM, Principal at Computer Sciences Corporation (CSC), CRM Practice Director at Cedars (Peoplesoft), and a Leadership Development Director at American Society for Training and Development (ASTD-RMC). Terry earned his B.A. degree in Applied Behavioral Sciences and completed graduate work in System Dynamics at Massachusetts Institute of Technology (MIT) and Organization leadership at Stanford. He holds several industry certifications including Six Sigma Master Black Belt, CM, CPC, among others. Terry speaks at industry conferences and recently served as a Technology Director at PMI, Program Management Office (PMO) SIG, a certification panelist for program management (PgMP) and risk management (RMP), impacting 200,000 worldwide members. He is published in several trade journals: Data Governance: http://dqgassociation.blogspot.com/ CRM leadership: Relationship Dynamics Feature: The Savior of CRM PMO best practices: http://blogs.ittoolbox.com/cio/pmo/ Initiative Leadership: IntelligentCRM: Key Imperatives for Success IntelligentCRM | Feature | E-Intelligence and the Agile Enterprise
  • 25. use case why data governance? New business opportunities Information Week State of the art customer service ‘The information Challenge’ Managing Risk and Compliance Meaningful decision guidance models 47% of users don’t have confidence Reducing operating costs in their information Effectiveness of the organization to drive Reliable, secure, accessible 59% of managers don’t and usable data use information they should have used Data fit for business purpose Ability to align interdependencies of People Processes Technologies 42% of managers use Across the organization wrong information at least once a week Effective Data Governance Program
  • 26. BC slide use case data governance structure (major manuf) Enterprise Governance Councils Governance body will Enterprise DMO enable following: Business Intelligence Data Services • Establish a common business language and BI Center of Excellence / BI Council quality processes Data Management Office (DMO) • Resolve cross-functional definition issues • Approve documentation of standards • Approve targets for quality measures • Facilitate culture change Policy Makers & Enforcers for data quality and data accountability Executive Metric Data Steward / Trustee Data Trustee / (Dashboard) Data Custodian / Metric Trustee Metrics Steward Metrics Steering Committee Quality of analytics Data Management Steering Committee Policy Audience Transformation Office (Advanced Value chain solutions - Process Excellence - TBD) Information users / Data Subscribers