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DataEd Slides: Data Strategy – Plans Are Useless but Planning Is Invaluable

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A data strategy document outlines Peter Aiken's perspective on developing an effective data strategy. Some key points include: - Effective data strategies require two phases - addressing prerequisites like organizational readiness and hiring qualified talent, and then ongoing iterations of planning. - Data is one of the most valuable yet underutilized assets in many organizations. A data strategy is needed to specify how data supports organizational goals. - Data governance provides guidance on managing data decisions and is necessary for an effective data strategy. The data strategy guides how data assets support the organizational strategy.

Data & Analytics
Related topics:
Data Management Insights • Data Strategy
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Data Strategy Copyright 2020 by Data Blueprint Slide # 1Peter Aiken, PhD Plans Are Useless but Planning is Invaluable
• DAMA International President 2009-2013 / 2018 • DAMA International Achievement Award 2001 (with Dr. E. F. "Ted" Codd • DAMA International Community Award 2005 • I've been doing this a long time • My work is recognized as useful • Associate Professor of IS (vcu.edu) • Founder, Data Blueprint (datablueprint.com) • DAMA International (dama.org) • CDO Society (iscdo.org) • 11 books and dozens of articles • Experienced w/ 500+ data management practices worldwide • Multi-year immersions – US DoD (DISA/Army/Marines/DLA) – Nokia – Deutsche Bank – Wells Fargo – Walmart … PETER AIKEN WITH JUANITA BILLINGS FOREWORD BY JOHN BOTTEGA MONETIZING DATA MANAGEMENT Unlocking the Value in Your Organization’s Most Important Asset. 2Copyright 2020 by Data Blueprint Slide # Peter Aiken, Ph.D.
• In spite of increasing (big data/AI) investments, % of firms self-identifying as data-driven is declining Source: Harvard Business Review, Feb 5, 2019 (Randy Bean and Thomas Davenport) • Survey of industry leading, large corporations • Firms must become much more serious and creative about addressing the human side of data if they truly expect to derive meaningful business benefits Source: 2018 Big Data & AI Executive Survey (NewVantage Partners) Companies Are Failing In Their Efforts To Become Data Driven 3Copyright 2020 by Data Blueprint Slide # 30% 32% 34% 36% 38% 2017 2018 2019 31% 32.4% 37.1% Forge a data culture Created a data-driven organization Treating data as a business asset Competing on data and analytics Identify people and process issues as the obstacle 0.00% 25.00% 50.00% 75.00% 100.00% Yes No
2019 Experian survey of industry leading, large corporations 4Copyright 2020 by Data Blueprint Slide # Have Big Data Projects underway "Data undermines key initiatives" Have under-invested in data quality Take to long to get insight from data Data enablement is 12 month key focus Currently have mature data quality initiatives 0.00% 25.00% 50.00% 75.00% 100.00% Yes No Data Quality Big Data Analytics Data Governance Data Literacy Machine Learning Artificial Intelligence 0% 25% 50% 75% 100% Currently undertaking Initiating within 12 months On the radar Not planned Data analyst Data engineer Chief Data Officer Data governance manager Data quality analyst Data scientist Data steward No specialized roles 0% 13% 25% 38% 50% Have Big Data Projects underway "Data undermines key initiatives" Have under-invested in data quality Take to long to get insight from data Data enablement is 12 month key focus Currently have mature data quality initiatives Data Quality Big Data Analytics Data Governance Data Literacy Machine Learning Artificial Intelligence
Data reports to Business 42% Data reports to IT 58% 5Copyright 2020 by Data Blueprint Slide # Enterprise-wide data efforts 31% Manage data within Departments 69% No data challenges 11% Experience data challenges 89% 2019 Experian survey of industry leading, large corporations • Many are not yet addressing the challenge correctly – Repeating the same behavior has not helped so far • 70% of focus is at the department level – More leverage is available at the enterprise level • Unresolved reporting structure – Leads to continued confusion and inhibits the profession's maturity
A Musical Analogy 6Copyright 2020 by Data Blueprint Slide # + = https://www.youtube.com/watch?v=4n1GT-VjjVs&frags=pl%2Cwn Please raise your hand when you recognize this song
Copyright 2020 by Data Blueprint Slide # Context • Strategy – Inherently a repetitive process that can be easily improved • Dependency – Data strategy exists to support organizational strategy • Evolution – At early maturity phases, the process is more important than the product! • Output – Plans are of limited value anyway and always discount obstacles • Technology – People and process challenges are 95% of the problem • Nirvana – How do I get to Carnegie Hall? – Practice Practice Practice 7
Copyright 2020 by Data Blueprint Slide # • A data strategy specifies how data assets are to be used to support the organizational strategy – What is strategy? – What is a data strategy? – How do they work together? • A data strategy is necessary for effective data governance – Improve your organization’s data – Improve the way people use their data – Improving how people use data to support their organizational strategy • Effective Data Strategy Prerequisites – Lack of organizational readiness – Failure to compensate for the lack of data competencies – Eliminating the barriers to leveraging data, the seven deadly data sins • Data Strategy Development Phase II–Iterations – Lather, rinse, repeat – A balanced approach is required • Q&A Data Strategy Plans Are Useless but Planning is Invaluable
What is a Strategy? 9Copyright 2020 by Data Blueprint Slide # • Current use derived from military • “a pattern in a stream of decisions” [Henry Mintzberg]
Former Walmart Business Strategy 10Copyright 2020 by Data Blueprint Slide # Every Day Low Price
Wayne Gretzky’s Definition of Strategy 11Copyright 2020 by Data Blueprint Slide # He skates to where he thinks the puck will be ...
Strategy in Action: Napoleon defeats a larger enemy • Question? – How do I defeat the competition when their forces are bigger than mine? • Answer: – Divide and conquer! – “a pattern in a stream of decisions” 12Copyright 2020 by Data Blueprint Slide #
Supply Line Metadata (as part of a divide and conquer strategy) 13Copyright 2020 by Data Blueprint Slide #
First Divide 14Copyright 2020 by Data Blueprint Slide #
Then Conquer 15Copyright 2020 by Data Blueprint Slide #
Complex Strategy 16Copyright 2020 by Data Blueprint Slide # W hile someone else is shooting at you! • First – Hit both armies hard at just the right spot • Then – Turn right and defeat the Prussians • Then – Turn left and defeat the British
General Dwight D. Eisenhower 17Copyright 2020 by Data Blueprint Slide # • “In preparing for battle I have always found that plans are useless, but planning is indispensable …” – https://quoteinvestigator.com/2017/11/18/planning/ • “In preparing for battle I have always found that plans are useless, but planning is indispensable …”
Strategy that winds up only on a shelf is not useful 18Copyright 2020 by Data Blueprint Slide # Data Strategy
Mike Tyson Quote 19Copyright 2020 by Data Blueprint Slide # “Everybody has a plan until they get punched in the mouth.” – https://www.sun-sentinel.com/sports/fl-xpm-2012-11-09-sfl-mike-tyson-explains-one-of- his-most-famous-quotes-20121109-story.html
Strategy Guides Workgroup Activities 20Copyright 2020 by Data Blueprint Slide # A pattern in a stream of decisions
Your Data Strategy • Highest level data guidance available ... • Focusing data activities on business- goal achievement ... • Providing guidance when faced with a stream of decisions or uncertainties 21Copyright 2020 by Data Blueprint Slide #
What is Data Governance? 22Copyright 2020 by Data Blueprint Slide # Managing Data with Guidance
Managing Data Decisions with Guidance What is Data Governance? 23Copyright 2020 by Data Blueprint Slide #
Managing Data with Guidance • How should data be used and in which business processes? • How is data shared among users, divisions, geographies and partners? • What processes and procedures allow for data to be changed? • Who manages approval processes? • What processes ensure compliance? • Most importantly, in what order should I approach the above list? 24Copyright 2020 by Data Blueprint Slide #
Data Strategy and Data Governance in Context 25Copyright 2020 by Data Blueprint Slide # Organizational Strategy Data Strategy IT Projects Organizational Operations Data Governance Data asset support for organizational strategy What the data assets do to support strategy How well the data strategy is working Operational feedback How data is delivered by IT How IT supports strategy Other aspects of organizational strategy
Data Strategy and Governance in Strategic Context 26Copyright 2020 by Data Blueprint Slide # Organizational Strategy Data Strategy Data Governance Data asset support for organizational strategy What the data assets do to support strategy How well the data strategy is working (Business Goals) (Metadata) IT Projects How data is delivered by IT
Data Strategy in Context 27Copyright 2020 by Data Blueprint Slide # Organizational Strategy IT Strategy Data Strategy
Organizational Strategy IT Strategy Data Strategy This is wrong! 28Copyright 2020 by Data Blueprint Slide # Organizational Strategy IT Strategy Data Strategy
Organizational Strategy IT Strategy This is correct … 29Copyright 2020 by Data Blueprint Slide # Data Strategy
Other recent data "strategies" • Big Data • Data Science • Analytics • SAP • Microsoft • Google • AWS • ... 30Copyright 2020 by Data Blueprint Slide #
Copyright 2020 by Data Blueprint Slide # • A data strategy specifies how data assets are to be used to support the organizational strategy – What is strategy? – What is a data strategy? – How do they work together? • A data strategy is necessary for effective data governance – Improve your organization’s data – Improve the way people use their data – Improving how people use data to support their organizational strategy • Effective Data Strategy Prerequisites – Lack of organizational readiness – Failure to compensate for the lack of data competencies – Eliminating the barriers to leveraging data, the seven deadly data sins • Data Strategy Development Phase II–Iterations – Lather, rinse, repeat – A balanced approach is required • Q&A Data Strategy Plans Are Useless but Planning is Invaluable
Organizational Assets • Cash & other financial instruments • Real property • Inventory • Intellectual Property • Human – Knowledge – Skills – Abilities • Financial • Organizational reputation • Good will • Brand name • Data!!! 32Copyright 2020 by Data Blueprint Slide #
33Copyright 2020 by Data Blueprint Slide # Separating the Wheat from the Chaff
Separating the Wheat from the Chaff • Data that is better organized increases in value • Poor data management practices are costing organizations money/time/effort • 80% of organizational data is ROT – Redundant – Obsolete – Trivial 34Copyright 2020 by Data Blueprint Slide # Incomplete
Data Assets Financial Assets Real Estate Assets Inventory Assets Non- depletable Available for subsequent use Can be used up Can be used up Non- degrading √ √ Can degrade over time Can degrade over time Durable Non-taxed √ √ Strategic Asset √ √ √ √ Data Assets Win!Data Assets Win! • Today, data is the most powerful, yet underutilized and poorly managed organizational asset • Data is your – Sole – Non-depletable – Non-degrading – Durable – Strategic • Asset – Data is the new oil! – Data is the new (s)oil! – Data is the new bacon! • As such, data deserves: – It's own strategy – Attention on par with similar organizational assets – Professional ministration to make up for past neglect 35Copyright 2020 by Data Blueprint Slide # Asset: A resource controlled by the organization as a result of past events or transactions and from which future economic benefits are expected to flow [Wikipedia]
Data Strategy and Data Governance in Context 36Copyright 2020 by Data Blueprint Slide # Organizational Strategy Data Strategy IT Projects Organizational Operations Data Governance Data asset support for organizational strategy What the data assets do to support strategy How well the data strategy is working Operational feedback How data is delivered by IT How IT supports strategy Other aspects of organizational strategy
Data Strategy & Data Governance 37Copyright 2020 by Data Blueprint Slide # Data Strategy Data Governance What the data assets do to support strategy How well the data strategy is working (Business Goals) (Metadata)
Data Strategy Motivation 38Copyright 2020 by Data Blueprint Slide # Improve your organization’s data Improve the way your people use its data Improve the way your data and your people support your organizational strategy • Because data points to where valuable things are located • Because data has intrinsic value by itself • Because data has inherent combinatorial value • Valuing Data – Use data to measure change – Use data to manage change – Use data to motivate change • Creating a competitive advantage with data
What did Rolls Royce Learn 39Copyright 2020 by Data Blueprint Slide # from Nascar? • Old model – Sell jet engines • New model – Sell hours of powered thrust – “Power-by-the-hour” – No payment for down time – Wing to wing – When was this new model invented? https://www.youtube.com/watch?v=RRy_73ivcms
Copyright 2020 by Data Blueprint Slide # • A data strategy specifies how data assets are to be used to support the organizational strategy – What is strategy? – What is a data strategy? – How do they work together? • A data strategy is necessary for effective data governance – Improve your organization’s data – Improve the way people use their data – Improving how people use data to support their organizational strategy • Effective Data Strategy Prerequisites – Lack of organizational readiness – Failure to compensate for the lack of data competencies – Eliminating the barriers to leveraging data, the seven deadly data sins • Data Strategy Development Phase II–Iterations – Lather, rinse, repeat – A balanced approach is required • Q&A Data Strategy Plans Are Useless but Planning is Invaluable
Data Strategy is Implemented in 2 Phases 41Copyright 2020 by Data Blueprint Slide # Data Strategy What the data assets do to support strategy Phase I-Prerequisites 1) Prepare for dramatic change and determine how to do the work 2) Recruit a qualified, knowledgeable enterprise data executive (and other qualified talent) 3) Eliminate the Seven Deadly Data Sins Phase II-Iterations (Lather, Rinse, Repeat)
Data Strategy is Implemented in 2 Phases 42Copyright 2020 by Data Blueprint Slide # Data Strategy What the data assets do to support strategy Phase I-Prerequisites 1) Prepare for dramatic change and determine how to do the work 2) Recruit a qualified, knowledgeable enterprise data executive (and other qualified talent) 3) Eliminate the Seven Deadly Data Sins Phase II-Iterations (Lather, Rinse, Repeat)
43Copyright 2020 by Data Blueprint Slide # Credit: Image credit: Matt Vickers
44Copyright 2020 by Data Blueprint Slide # CIOs aren't
45Copyright 2020 by Data Blueprint Slide #
Chief Data Officer Combat 46Copyright 2020 by Data Blueprint Slide # • Recasting the executive team. make full use of the most valuable assets
Change the status quo! 47Copyright 2020 by Data Blueprint Slide # • Keep in mind that the appointment of a CDO typically comes from a high-level decision. In practice, it can trigger an array of problematic reactions within the organization including: – Confusion, – Uncertainty, – Doubt, – Resentment and – Resistance. • CDOs need to rise to the challenge of changing the status quo if they expect to lead the business in making data a strategic asset. – from What Chief Data Officers Need to Do to Succeed by Mario Faria https://www.forbes.com/sites/gartnergroup/2016/04/11/what-chief-data-officers-need-to-do-to-succeed/#734d53a8434a
Change Management & Leadership Copyright 2020 by Data Blueprint Slide # 48
Diagnosing Organizational Readiness 49Copyright 2020 by Data Blueprint Slide # adapted from the Managing Complex Change model by Dr. Mary Lippitt, 1987 Culture is the biggest impediment to a shift in organizational thinking about data!
QR Code for PeterStudy • Free Case Study Download 50Copyright 2020 by Data Blueprint Slide # • Free Case Study Download – http://dl.acm.org/citation.cfm?doid=2888577.2893482 or http://tinyurl.com/PeterStudy or scan the QR Code at the right
Data Strategy is Implemented in 2 Phases 51Copyright 2020 by Data Blueprint Slide # Data Strategy What the data assets do to support strategy Phase I-Prerequisites 1) Prepare for dramatic change and determine how to do the work 2) Recruit a qualified, knowledgeable enterprise data executive (and other qualified talent) 3) Eliminate the Seven Deadly Data Sins Phase II-Iterations (Lather, Rinse, Repeat)
Data Strategy Framework (Part 1) 52Copyright 2020 by Data Blueprint Slide # • Benefits & Success Criteria • Capability Targets • Solution Architecture • Organizational Development Solution • Organization Mission • Strategy & Objectives • Organizational Structures • Performance Measures Business Needs • Organizational / Readiness • Business Processes • Data Management Practices • Data Assets • Technology Assets Current State • Business Value Targets • Capability Targets • Tactics • Data Strategy Vision Strategic Data Imperatives Business Needs Existing Capabilities Execution
What do we teach knowledge workers about data? 53Copyright 2020 by Data Blueprint Slide # What percentage of the deal with it daily?
What do we teach IT professionals about data? 54Copyright 2020 by Data Blueprint Slide # • 1 course – How to build a new database • What impressions do IT professionals get from this education? – Data is a technical skill that is needed when developing new databases • If we are migrating databases, we are not creating new databases and we don't need organizational data management knowledge, skills, and abilities (KSAs). • If we are implementing a new software package, we are not creating a new database and therefore we do not need data management KSAs. • If we are installing an enterprise resource package (ERP), we are not creating a new database and therefore we do not need data management KSAs.
Put simply, organizations: 55Copyright 2020 by Data Blueprint Slide # • Have little idea what data they have • Do not know where it is (and) • Do not know what their knowledge workers do with it
56Copyright 2020 by Data Blueprint Slide #
Bad Data Decisions Spiral 57Copyright 2020 by Data Blueprint Slide # Bad data decisions Technical deci- sion makers are not data knowledgable Business decision makers are not data knowledgable Poor organizational outcomes Poor treatment of organizational data assets Poor quality data
Hiring Panels Are Often Not Qualified to Help 58Copyright 2020 by Data Blueprint Slide #
The Enterprise Data Executive Takes One for the Team 59Copyright 2020 by Data Blueprint Slide #
Data Strategy is Implemented in 2 Phases 60Copyright 2020 by Data Blueprint Slide # Data Strategy What the data assets do to support strategy Phase I-Prerequisites 1) Prepare for dramatic change and determine how to do the work 2) Recruit a qualified, knowledgeable enterprise data executive (and other qualified talent) 3) Eliminate the Seven Deadly Data Sins Phase II-Iterations (Lather, Rinse, Repeat)
Exorcising the Seven Deadly Data Sins 61Copyright 2020 by Data Blueprint Slide # Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges ing to Implement a grammatic Way to Share Data Not Aligning the Data Program with IT Projects ata ation Not Addressing Cultural and Change Management Challenges 3 4 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 Data- g Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ling to Adequately anage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 5 6 7Data Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects t Sequencing Data tegy Implementation Not Addressing Cultural and Change Management Challenges 3 4 6 7 ent a y to Not Aligning the Data Program with IT Projects Addressing Cultural and Change agement Challenges 4 7 Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 king Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ely ons Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 6 7
Introducing The Data Doctrine 62Copyright 2020 by Data Blueprint Slide # http://www.thedatadoctrine.com
Copyright 2020 by Data Blueprint Slide # • A data strategy specifies how data assets are to be used to support the organizational strategy – What is strategy? – What is a data strategy? – How do they work together? • A data strategy is necessary for effective data governance – Improve your organization’s data – Improve the way people use their data – Improving how people use data to support their organizational strategy • Effective Data Strategy Prerequisites – Lack of organizational readiness – Failure to compensate for the lack of data competencies – Eliminating the barriers to leveraging data, the seven deadly data sins • Data Strategy Development Phase II–Iterations – Lather, rinse, repeat – A balanced approach is required • Q&A Data Strategy Plans Are Useless but Planning is Invaluable
Data Strategy is Implemented in 2 Phases 64Copyright 2020 by Data Blueprint Slide # Data Strategy Phase I-Prerequisites 1) Prepare for dramatic change and determined how to do the work 2) Recruit a qualified, knowledgeable enterprise data executive (and other qualified talent) 3) Eliminate the Seven Deadly Data Sins Phase II-Iterations (Lather, Rinse, Repeat) You are here 1) Identify the primary constraint keeping data from fully supporting strategy 2) Exploit organizational efforts to remove this constraint 3) Subordinate everything else to this exploitation decision 4) Elevate the data constraint 5) Repeat the above steps to address the new constraint
The Goal 65Copyright 2020 by Data Blueprint Slide #
66Copyright 2020 by Data Blueprint Slide # https://en.wikipedia.org/wiki/Theory_of_constraints (TOC) • A management paradigm that views any manageable system as being limited in achieving more of its goals by a small number of constraints(Eliyahu M. Goldratt) • There is always at least one constraint, and TOC uses a focusing process to identify the constraint and restructure the rest of the organization to address it • TOC adopts the common idiom "a chain is no stronger than its weakest link," processes, organizations, etc., are vulnerable because the weakest component can damage or break them or at least adversely affect the outcome
Theory of Constraints - Generic 67Copyright 2020 by Data Blueprint Slide # Identify the current constraints, the components of the system limiting goal realization Make quick improvements to the constraint using existing resources Review other activities in the process facilitate proper alignment and support of constraint If the constraint persists, identify other actions to eliminate the constraint Repeat until the constraint is eliminated Alleviate
Theory of Constraints at work improving your data 68Copyright 2020 by Data Blueprint Slide # In your analysis of how organization data can best support organizational strategy one thing is blocking you most - identify it! Try to fix it rapidly with out restructuring (correct it operationally) Improve existing data evolution activities to ensure singular focus on the current objective Restructure to address constraint Repeat until data better supports strategy Alleviate
Data Strategy Framework (Part 2) 69Copyright 2020 by Data Blueprint Slide # • Benefits & Success Criteria • Capability Targets • Solution Architecture • Organizational Development Solution • Leadership & Planning • Project Dev. & Execution • Cultural Readiness Road Map • Organization Mission • Strategy & Objectives • Organizational Structures • Performance Measures Business Needs • Organizational / Readiness • Business Processes • Data Management Practices • Data Assets • Technology Assets Current State • Business Value Targets • Capability Targets • Tactics • Data Strategy Vision Strategic Data Imperatives Business Needs Existing Capabilities ExecutionBusiness Value New Capabilities
Copyright 2020 by Data Blueprint Slide # Strategic Context • Strategy – Inherently a repetitive process that can be easily improved • Dependency – Data strategy exists to support organizational strategy • Evolution – At early maturity phases, the process is more important than the product! • Output – Plans are of limited value anyway and always discount obstacles • Technology – People and process challenges are 95% of the problem • Nirvana – How do I get to Carnegie Hall? – Practice Practice Practice 70
Data Strategy Plans Are Useless but Planning is Invaluable • A data strategy specifies how data assets are to be used to support the organizational strategy – What is strategy? – What is a data strategy? – How do they work together? • A data strategy is necessary for effective data governance – Improve your organization’s data – Improve the way people use their data – Improving how people use data to support their organizational strategy • Effective Data Strategy Prerequisites – Lack of organizational readiness – Failure to compensate for the lack of data competencies – Eliminating the barriers to leveraging data, the seven deadly data sins • Data Strategy Development Phase II–Iterations – Lather, rinse, repeat – A balanced approach is required • Q&A 71Copyright 2020 by Data Blueprint Slide #
Upcoming Events February Webinar: Data Architecture vs Data Modeling: Contrast and Compare Tuesday, February 11, 2020 @ 2:00 PM ET/11:00 AM PT (UTC-5) March Webinar: Unlock Business Value using Reference and Master Data Management Strategies Tuesday, March 10, 2020 @ 2:00 PM ET/11:00 AM PT (UTC-6) Enterprise Data World Developing Data Proficiencies to Improve Workforce Performance Sunday, 3/23/2020 @ 1:30 PM PT April Webinar: Leveraging Data Management Technologies Tuesday, April 14, 2020 @ 2:00 PM ET/11:00 AM PT (UTC-5) Sign up for webinars at: www.datablueprint.com/webinar-schedule or www.dataversity.net 72Copyright 2020 by Data Blueprint Slide # Brought to you by:
+ = Questions? 73Copyright 2020 by Data Blueprint Slide # It’s your turn! Use the chat feature or Twitter (#dataed) to submit your questions now!
10124 W. Broad Street, Suite C Glen Allen, Virginia 23060 804.521.4056 Copyright 2020 by Data Blueprint Slide # 74

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DataEd Slides: Data Strategy – Plans Are Useless but Planning Is Invaluable

  • 1. Data Strategy Copyright 2020 by Data Blueprint Slide # 1Peter Aiken, PhD Plans Are Useless but Planning is Invaluable
  • 2. • DAMA International President 2009-2013 / 2018 • DAMA International Achievement Award 2001 (with Dr. E. F. "Ted" Codd • DAMA International Community Award 2005 • I've been doing this a long time • My work is recognized as useful • Associate Professor of IS (vcu.edu) • Founder, Data Blueprint (datablueprint.com) • DAMA International (dama.org) • CDO Society (iscdo.org) • 11 books and dozens of articles • Experienced w/ 500+ data management practices worldwide • Multi-year immersions – US DoD (DISA/Army/Marines/DLA) – Nokia – Deutsche Bank – Wells Fargo – Walmart … PETER AIKEN WITH JUANITA BILLINGS FOREWORD BY JOHN BOTTEGA MONETIZING DATA MANAGEMENT Unlocking the Value in Your Organization’s Most Important Asset. 2Copyright 2020 by Data Blueprint Slide # Peter Aiken, Ph.D.
  • 3. • In spite of increasing (big data/AI) investments, % of firms self-identifying as data-driven is declining Source: Harvard Business Review, Feb 5, 2019 (Randy Bean and Thomas Davenport) • Survey of industry leading, large corporations • Firms must become much more serious and creative about addressing the human side of data if they truly expect to derive meaningful business benefits Source: 2018 Big Data & AI Executive Survey (NewVantage Partners) Companies Are Failing In Their Efforts To Become Data Driven 3Copyright 2020 by Data Blueprint Slide # 30% 32% 34% 36% 38% 2017 2018 2019 31% 32.4% 37.1% Forge a data culture Created a data-driven organization Treating data as a business asset Competing on data and analytics Identify people and process issues as the obstacle 0.00% 25.00% 50.00% 75.00% 100.00% Yes No
  • 4. 2019 Experian survey of industry leading, large corporations 4Copyright 2020 by Data Blueprint Slide # Have Big Data Projects underway "Data undermines key initiatives" Have under-invested in data quality Take to long to get insight from data Data enablement is 12 month key focus Currently have mature data quality initiatives 0.00% 25.00% 50.00% 75.00% 100.00% Yes No Data Quality Big Data Analytics Data Governance Data Literacy Machine Learning Artificial Intelligence 0% 25% 50% 75% 100% Currently undertaking Initiating within 12 months On the radar Not planned Data analyst Data engineer Chief Data Officer Data governance manager Data quality analyst Data scientist Data steward No specialized roles 0% 13% 25% 38% 50% Have Big Data Projects underway "Data undermines key initiatives" Have under-invested in data quality Take to long to get insight from data Data enablement is 12 month key focus Currently have mature data quality initiatives Data Quality Big Data Analytics Data Governance Data Literacy Machine Learning Artificial Intelligence
  • 5. Data reports to Business 42% Data reports to IT 58% 5Copyright 2020 by Data Blueprint Slide # Enterprise-wide data efforts 31% Manage data within Departments 69% No data challenges 11% Experience data challenges 89% 2019 Experian survey of industry leading, large corporations • Many are not yet addressing the challenge correctly – Repeating the same behavior has not helped so far • 70% of focus is at the department level – More leverage is available at the enterprise level • Unresolved reporting structure – Leads to continued confusion and inhibits the profession's maturity
  • 6. A Musical Analogy 6Copyright 2020 by Data Blueprint Slide # + = https://www.youtube.com/watch?v=4n1GT-VjjVs&frags=pl%2Cwn Please raise your hand when you recognize this song
  • 7. Copyright 2020 by Data Blueprint Slide # Context • Strategy – Inherently a repetitive process that can be easily improved • Dependency – Data strategy exists to support organizational strategy • Evolution – At early maturity phases, the process is more important than the product! • Output – Plans are of limited value anyway and always discount obstacles • Technology – People and process challenges are 95% of the problem • Nirvana – How do I get to Carnegie Hall? – Practice Practice Practice 7
  • 8. Copyright 2020 by Data Blueprint Slide # • A data strategy specifies how data assets are to be used to support the organizational strategy – What is strategy? – What is a data strategy? – How do they work together? • A data strategy is necessary for effective data governance – Improve your organization’s data – Improve the way people use their data – Improving how people use data to support their organizational strategy • Effective Data Strategy Prerequisites – Lack of organizational readiness – Failure to compensate for the lack of data competencies – Eliminating the barriers to leveraging data, the seven deadly data sins • Data Strategy Development Phase II–Iterations – Lather, rinse, repeat – A balanced approach is required • Q&A Data Strategy Plans Are Useless but Planning is Invaluable
  • 9. What is a Strategy? 9Copyright 2020 by Data Blueprint Slide # • Current use derived from military • “a pattern in a stream of decisions” [Henry Mintzberg]
  • 10. Former Walmart Business Strategy 10Copyright 2020 by Data Blueprint Slide # Every Day Low Price
  • 11. Wayne Gretzky’s Definition of Strategy 11Copyright 2020 by Data Blueprint Slide # He skates to where he thinks the puck will be ...
  • 12. Strategy in Action: Napoleon defeats a larger enemy • Question? – How do I defeat the competition when their forces are bigger than mine? • Answer: – Divide and conquer! – “a pattern in a stream of decisions” 12Copyright 2020 by Data Blueprint Slide #
  • 13. Supply Line Metadata (as part of a divide and conquer strategy) 13Copyright 2020 by Data Blueprint Slide #
  • 14. First Divide 14Copyright 2020 by Data Blueprint Slide #
  • 15. Then Conquer 15Copyright 2020 by Data Blueprint Slide #
  • 16. Complex Strategy 16Copyright 2020 by Data Blueprint Slide # W hile someone else is shooting at you! • First – Hit both armies hard at just the right spot • Then – Turn right and defeat the Prussians • Then – Turn left and defeat the British
  • 17. General Dwight D. Eisenhower 17Copyright 2020 by Data Blueprint Slide # • “In preparing for battle I have always found that plans are useless, but planning is indispensable …” – https://quoteinvestigator.com/2017/11/18/planning/ • “In preparing for battle I have always found that plans are useless, but planning is indispensable …”
  • 18. Strategy that winds up only on a shelf is not useful 18Copyright 2020 by Data Blueprint Slide # Data Strategy
  • 19. Mike Tyson Quote 19Copyright 2020 by Data Blueprint Slide # “Everybody has a plan until they get punched in the mouth.” – https://www.sun-sentinel.com/sports/fl-xpm-2012-11-09-sfl-mike-tyson-explains-one-of- his-most-famous-quotes-20121109-story.html
  • 20. Strategy Guides Workgroup Activities 20Copyright 2020 by Data Blueprint Slide # A pattern in a stream of decisions
  • 21. Your Data Strategy • Highest level data guidance available ... • Focusing data activities on business- goal achievement ... • Providing guidance when faced with a stream of decisions or uncertainties 21Copyright 2020 by Data Blueprint Slide #
  • 22. What is Data Governance? 22Copyright 2020 by Data Blueprint Slide # Managing Data with Guidance
  • 23. Managing Data Decisions with Guidance What is Data Governance? 23Copyright 2020 by Data Blueprint Slide #
  • 24. Managing Data with Guidance • How should data be used and in which business processes? • How is data shared among users, divisions, geographies and partners? • What processes and procedures allow for data to be changed? • Who manages approval processes? • What processes ensure compliance? • Most importantly, in what order should I approach the above list? 24Copyright 2020 by Data Blueprint Slide #
  • 25. Data Strategy and Data Governance in Context 25Copyright 2020 by Data Blueprint Slide # Organizational Strategy Data Strategy IT Projects Organizational Operations Data Governance Data asset support for organizational strategy What the data assets do to support strategy How well the data strategy is working Operational feedback How data is delivered by IT How IT supports strategy Other aspects of organizational strategy
  • 26. Data Strategy and Governance in Strategic Context 26Copyright 2020 by Data Blueprint Slide # Organizational Strategy Data Strategy Data Governance Data asset support for organizational strategy What the data assets do to support strategy How well the data strategy is working (Business Goals) (Metadata) IT Projects How data is delivered by IT
  • 27. Data Strategy in Context 27Copyright 2020 by Data Blueprint Slide # Organizational Strategy IT Strategy Data Strategy
  • 28. Organizational Strategy IT Strategy Data Strategy This is wrong! 28Copyright 2020 by Data Blueprint Slide # Organizational Strategy IT Strategy Data Strategy
  • 29. Organizational Strategy IT Strategy This is correct … 29Copyright 2020 by Data Blueprint Slide # Data Strategy
  • 30. Other recent data "strategies" • Big Data • Data Science • Analytics • SAP • Microsoft • Google • AWS • ... 30Copyright 2020 by Data Blueprint Slide #
  • 31. Copyright 2020 by Data Blueprint Slide # • A data strategy specifies how data assets are to be used to support the organizational strategy – What is strategy? – What is a data strategy? – How do they work together? • A data strategy is necessary for effective data governance – Improve your organization’s data – Improve the way people use their data – Improving how people use data to support their organizational strategy • Effective Data Strategy Prerequisites – Lack of organizational readiness – Failure to compensate for the lack of data competencies – Eliminating the barriers to leveraging data, the seven deadly data sins • Data Strategy Development Phase II–Iterations – Lather, rinse, repeat – A balanced approach is required • Q&A Data Strategy Plans Are Useless but Planning is Invaluable
  • 32. Organizational Assets • Cash & other financial instruments • Real property • Inventory • Intellectual Property • Human – Knowledge – Skills – Abilities • Financial • Organizational reputation • Good will • Brand name • Data!!! 32Copyright 2020 by Data Blueprint Slide #
  • 33. 33Copyright 2020 by Data Blueprint Slide # Separating the Wheat from the Chaff
  • 34. Separating the Wheat from the Chaff • Data that is better organized increases in value • Poor data management practices are costing organizations money/time/effort • 80% of organizational data is ROT – Redundant – Obsolete – Trivial 34Copyright 2020 by Data Blueprint Slide # Incomplete
  • 35. Data Assets Financial Assets Real Estate Assets Inventory Assets Non- depletable Available for subsequent use Can be used up Can be used up Non- degrading √ √ Can degrade over time Can degrade over time Durable Non-taxed √ √ Strategic Asset √ √ √ √ Data Assets Win!Data Assets Win! • Today, data is the most powerful, yet underutilized and poorly managed organizational asset • Data is your – Sole – Non-depletable – Non-degrading – Durable – Strategic • Asset – Data is the new oil! – Data is the new (s)oil! – Data is the new bacon! • As such, data deserves: – It's own strategy – Attention on par with similar organizational assets – Professional ministration to make up for past neglect 35Copyright 2020 by Data Blueprint Slide # Asset: A resource controlled by the organization as a result of past events or transactions and from which future economic benefits are expected to flow [Wikipedia]
  • 36. Data Strategy and Data Governance in Context 36Copyright 2020 by Data Blueprint Slide # Organizational Strategy Data Strategy IT Projects Organizational Operations Data Governance Data asset support for organizational strategy What the data assets do to support strategy How well the data strategy is working Operational feedback How data is delivered by IT How IT supports strategy Other aspects of organizational strategy
  • 37. Data Strategy & Data Governance 37Copyright 2020 by Data Blueprint Slide # Data Strategy Data Governance What the data assets do to support strategy How well the data strategy is working (Business Goals) (Metadata)
  • 38. Data Strategy Motivation 38Copyright 2020 by Data Blueprint Slide # Improve your organization’s data Improve the way your people use its data Improve the way your data and your people support your organizational strategy • Because data points to where valuable things are located • Because data has intrinsic value by itself • Because data has inherent combinatorial value • Valuing Data – Use data to measure change – Use data to manage change – Use data to motivate change • Creating a competitive advantage with data
  • 39. What did Rolls Royce Learn 39Copyright 2020 by Data Blueprint Slide # from Nascar? • Old model – Sell jet engines • New model – Sell hours of powered thrust – “Power-by-the-hour” – No payment for down time – Wing to wing – When was this new model invented? https://www.youtube.com/watch?v=RRy_73ivcms
  • 40. Copyright 2020 by Data Blueprint Slide # • A data strategy specifies how data assets are to be used to support the organizational strategy – What is strategy? – What is a data strategy? – How do they work together? • A data strategy is necessary for effective data governance – Improve your organization’s data – Improve the way people use their data – Improving how people use data to support their organizational strategy • Effective Data Strategy Prerequisites – Lack of organizational readiness – Failure to compensate for the lack of data competencies – Eliminating the barriers to leveraging data, the seven deadly data sins • Data Strategy Development Phase II–Iterations – Lather, rinse, repeat – A balanced approach is required • Q&A Data Strategy Plans Are Useless but Planning is Invaluable
  • 41. Data Strategy is Implemented in 2 Phases 41Copyright 2020 by Data Blueprint Slide # Data Strategy What the data assets do to support strategy Phase I-Prerequisites 1) Prepare for dramatic change and determine how to do the work 2) Recruit a qualified, knowledgeable enterprise data executive (and other qualified talent) 3) Eliminate the Seven Deadly Data Sins Phase II-Iterations (Lather, Rinse, Repeat)
  • 42. Data Strategy is Implemented in 2 Phases 42Copyright 2020 by Data Blueprint Slide # Data Strategy What the data assets do to support strategy Phase I-Prerequisites 1) Prepare for dramatic change and determine how to do the work 2) Recruit a qualified, knowledgeable enterprise data executive (and other qualified talent) 3) Eliminate the Seven Deadly Data Sins Phase II-Iterations (Lather, Rinse, Repeat)
  • 43. 43Copyright 2020 by Data Blueprint Slide # Credit: Image credit: Matt Vickers
  • 44. 44Copyright 2020 by Data Blueprint Slide # CIOs aren't
  • 45. 45Copyright 2020 by Data Blueprint Slide #
  • 46. Chief Data Officer Combat 46Copyright 2020 by Data Blueprint Slide # • Recasting the executive team. make full use of the most valuable assets
  • 47. Change the status quo! 47Copyright 2020 by Data Blueprint Slide # • Keep in mind that the appointment of a CDO typically comes from a high-level decision. In practice, it can trigger an array of problematic reactions within the organization including: – Confusion, – Uncertainty, – Doubt, – Resentment and – Resistance. • CDOs need to rise to the challenge of changing the status quo if they expect to lead the business in making data a strategic asset. – from What Chief Data Officers Need to Do to Succeed by Mario Faria https://www.forbes.com/sites/gartnergroup/2016/04/11/what-chief-data-officers-need-to-do-to-succeed/#734d53a8434a
  • 48. Change Management & Leadership Copyright 2020 by Data Blueprint Slide # 48
  • 49. Diagnosing Organizational Readiness 49Copyright 2020 by Data Blueprint Slide # adapted from the Managing Complex Change model by Dr. Mary Lippitt, 1987 Culture is the biggest impediment to a shift in organizational thinking about data!
  • 50. QR Code for PeterStudy • Free Case Study Download 50Copyright 2020 by Data Blueprint Slide # • Free Case Study Download – http://dl.acm.org/citation.cfm?doid=2888577.2893482 or http://tinyurl.com/PeterStudy or scan the QR Code at the right
  • 51. Data Strategy is Implemented in 2 Phases 51Copyright 2020 by Data Blueprint Slide # Data Strategy What the data assets do to support strategy Phase I-Prerequisites 1) Prepare for dramatic change and determine how to do the work 2) Recruit a qualified, knowledgeable enterprise data executive (and other qualified talent) 3) Eliminate the Seven Deadly Data Sins Phase II-Iterations (Lather, Rinse, Repeat)
  • 52. Data Strategy Framework (Part 1) 52Copyright 2020 by Data Blueprint Slide # • Benefits & Success Criteria • Capability Targets • Solution Architecture • Organizational Development Solution • Organization Mission • Strategy & Objectives • Organizational Structures • Performance Measures Business Needs • Organizational / Readiness • Business Processes • Data Management Practices • Data Assets • Technology Assets Current State • Business Value Targets • Capability Targets • Tactics • Data Strategy Vision Strategic Data Imperatives Business Needs Existing Capabilities Execution
  • 53. What do we teach knowledge workers about data? 53Copyright 2020 by Data Blueprint Slide # What percentage of the deal with it daily?
  • 54. What do we teach IT professionals about data? 54Copyright 2020 by Data Blueprint Slide # • 1 course – How to build a new database • What impressions do IT professionals get from this education? – Data is a technical skill that is needed when developing new databases • If we are migrating databases, we are not creating new databases and we don't need organizational data management knowledge, skills, and abilities (KSAs). • If we are implementing a new software package, we are not creating a new database and therefore we do not need data management KSAs. • If we are installing an enterprise resource package (ERP), we are not creating a new database and therefore we do not need data management KSAs.
  • 55. Put simply, organizations: 55Copyright 2020 by Data Blueprint Slide # • Have little idea what data they have • Do not know where it is (and) • Do not know what their knowledge workers do with it
  • 56. 56Copyright 2020 by Data Blueprint Slide #
  • 57. Bad Data Decisions Spiral 57Copyright 2020 by Data Blueprint Slide # Bad data decisions Technical deci- sion makers are not data knowledgable Business decision makers are not data knowledgable Poor organizational outcomes Poor treatment of organizational data assets Poor quality data
  • 58. Hiring Panels Are Often Not Qualified to Help 58Copyright 2020 by Data Blueprint Slide #
  • 59. The Enterprise Data Executive Takes One for the Team 59Copyright 2020 by Data Blueprint Slide #
  • 60. Data Strategy is Implemented in 2 Phases 60Copyright 2020 by Data Blueprint Slide # Data Strategy What the data assets do to support strategy Phase I-Prerequisites 1) Prepare for dramatic change and determine how to do the work 2) Recruit a qualified, knowledgeable enterprise data executive (and other qualified talent) 3) Eliminate the Seven Deadly Data Sins Phase II-Iterations (Lather, Rinse, Repeat)
  • 61. Exorcising the Seven Deadly Data Sins 61Copyright 2020 by Data Blueprint Slide # Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges ing to Implement a grammatic Way to Share Data Not Aligning the Data Program with IT Projects ata ation Not Addressing Cultural and Change Management Challenges 3 4 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 Data- g Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ling to Adequately anage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 5 6 7Data Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects t Sequencing Data tegy Implementation Not Addressing Cultural and Change Management Challenges 3 4 6 7 ent a y to Not Aligning the Data Program with IT Projects Addressing Cultural and Change agement Challenges 4 7 Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 king Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ely ons Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 6 7
  • 62. Introducing The Data Doctrine 62Copyright 2020 by Data Blueprint Slide # http://www.thedatadoctrine.com
  • 63. Copyright 2020 by Data Blueprint Slide # • A data strategy specifies how data assets are to be used to support the organizational strategy – What is strategy? – What is a data strategy? – How do they work together? • A data strategy is necessary for effective data governance – Improve your organization’s data – Improve the way people use their data – Improving how people use data to support their organizational strategy • Effective Data Strategy Prerequisites – Lack of organizational readiness – Failure to compensate for the lack of data competencies – Eliminating the barriers to leveraging data, the seven deadly data sins • Data Strategy Development Phase II–Iterations – Lather, rinse, repeat – A balanced approach is required • Q&A Data Strategy Plans Are Useless but Planning is Invaluable
  • 64. Data Strategy is Implemented in 2 Phases 64Copyright 2020 by Data Blueprint Slide # Data Strategy Phase I-Prerequisites 1) Prepare for dramatic change and determined how to do the work 2) Recruit a qualified, knowledgeable enterprise data executive (and other qualified talent) 3) Eliminate the Seven Deadly Data Sins Phase II-Iterations (Lather, Rinse, Repeat) You are here 1) Identify the primary constraint keeping data from fully supporting strategy 2) Exploit organizational efforts to remove this constraint 3) Subordinate everything else to this exploitation decision 4) Elevate the data constraint 5) Repeat the above steps to address the new constraint
  • 65. The Goal 65Copyright 2020 by Data Blueprint Slide #
  • 66. 66Copyright 2020 by Data Blueprint Slide # https://en.wikipedia.org/wiki/Theory_of_constraints (TOC) • A management paradigm that views any manageable system as being limited in achieving more of its goals by a small number of constraints(Eliyahu M. Goldratt) • There is always at least one constraint, and TOC uses a focusing process to identify the constraint and restructure the rest of the organization to address it • TOC adopts the common idiom "a chain is no stronger than its weakest link," processes, organizations, etc., are vulnerable because the weakest component can damage or break them or at least adversely affect the outcome
  • 67. Theory of Constraints - Generic 67Copyright 2020 by Data Blueprint Slide # Identify the current constraints, the components of the system limiting goal realization Make quick improvements to the constraint using existing resources Review other activities in the process facilitate proper alignment and support of constraint If the constraint persists, identify other actions to eliminate the constraint Repeat until the constraint is eliminated Alleviate
  • 68. Theory of Constraints at work improving your data 68Copyright 2020 by Data Blueprint Slide # In your analysis of how organization data can best support organizational strategy one thing is blocking you most - identify it! Try to fix it rapidly with out restructuring (correct it operationally) Improve existing data evolution activities to ensure singular focus on the current objective Restructure to address constraint Repeat until data better supports strategy Alleviate
  • 69. Data Strategy Framework (Part 2) 69Copyright 2020 by Data Blueprint Slide # • Benefits & Success Criteria • Capability Targets • Solution Architecture • Organizational Development Solution • Leadership & Planning • Project Dev. & Execution • Cultural Readiness Road Map • Organization Mission • Strategy & Objectives • Organizational Structures • Performance Measures Business Needs • Organizational / Readiness • Business Processes • Data Management Practices • Data Assets • Technology Assets Current State • Business Value Targets • Capability Targets • Tactics • Data Strategy Vision Strategic Data Imperatives Business Needs Existing Capabilities ExecutionBusiness Value New Capabilities
  • 70. Copyright 2020 by Data Blueprint Slide # Strategic Context • Strategy – Inherently a repetitive process that can be easily improved • Dependency – Data strategy exists to support organizational strategy • Evolution – At early maturity phases, the process is more important than the product! • Output – Plans are of limited value anyway and always discount obstacles • Technology – People and process challenges are 95% of the problem • Nirvana – How do I get to Carnegie Hall? – Practice Practice Practice 70
  • 71. Data Strategy Plans Are Useless but Planning is Invaluable • A data strategy specifies how data assets are to be used to support the organizational strategy – What is strategy? – What is a data strategy? – How do they work together? • A data strategy is necessary for effective data governance – Improve your organization’s data – Improve the way people use their data – Improving how people use data to support their organizational strategy • Effective Data Strategy Prerequisites – Lack of organizational readiness – Failure to compensate for the lack of data competencies – Eliminating the barriers to leveraging data, the seven deadly data sins • Data Strategy Development Phase II–Iterations – Lather, rinse, repeat – A balanced approach is required • Q&A 71Copyright 2020 by Data Blueprint Slide #
  • 72. Upcoming Events February Webinar: Data Architecture vs Data Modeling: Contrast and Compare Tuesday, February 11, 2020 @ 2:00 PM ET/11:00 AM PT (UTC-5) March Webinar: Unlock Business Value using Reference and Master Data Management Strategies Tuesday, March 10, 2020 @ 2:00 PM ET/11:00 AM PT (UTC-6) Enterprise Data World Developing Data Proficiencies to Improve Workforce Performance Sunday, 3/23/2020 @ 1:30 PM PT April Webinar: Leveraging Data Management Technologies Tuesday, April 14, 2020 @ 2:00 PM ET/11:00 AM PT (UTC-5) Sign up for webinars at: www.datablueprint.com/webinar-schedule or www.dataversity.net 72Copyright 2020 by Data Blueprint Slide # Brought to you by:
  • 73. + = Questions? 73Copyright 2020 by Data Blueprint Slide # It’s your turn! Use the chat feature or Twitter (#dataed) to submit your questions now!
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