The building blocks of a data strategy for a CDO

The role of the Chief Data Officer (CDO)

An August 2019 MIT Sloan article begins with the premise “As the chief data officer (CDO) role evolves to focus on innovation and growth, job ambiguity and entrenched company cultures remain stumbling blocks.”  From our experience helping organizations with their Data Strategy, we know the challenges all too well.

Where does the CDO report into?

The CDO’s reporting line will depend on the role of data itself in the organization. Is it strategic, tactical, in transition?

  • STRATEGIC:  For an organization like LinkedIN data is the value chain as the raw material, the finished products, the sales, support and marketing. Data is the strategic asset, so the CDO should be sitting at the table with the CFO and COO. (read Getting LinkedIN to Data Science with Igor Perisic)
  • TACTICAL: Rio Tinto, a mining and metals company, generates huge volumes of data from mines, processing plants, geological studies, autonomous vehicles and all of the systems that manage HR, Procurement and Operations. Data is vital to the efficiency of the business, but it is in service of a value chain dedicated to processing ore into finished products. (read Using data to find solutions, one byte at a time)
  • IN TRANSITION: IKEA, a furniture retailer also generates data on products, supply chain, store operations and its customers. IKEA has made a major bet on SmartHome technology, which moves data from supporting the value chain activity to being very much part of it. (read IKEA goes all in on smart home tech)

If the current role of data is tactical, then the CDO should report into the executive team. If strategic, then the CDO would sit on the executive team. For an organization in transition, then the CDO would also sit on the executive team to ensure budgets and business support of the new initiatives.


Role Objectives

The purpose of Chief Data Officer (CDO) is to help the organization leverage data as a strategic asset. The variances in digital maturity would determine if: the CDO role is looking to catch up with respect to data governance and security; has the task of building infrastructure and organizational mindset for future where data is a strategic asset; or has the mandate to commercialize the data as new products or service offerings for internal and external customers.

  • CATCH-UP Fixing Legacy Problems to bring the organization’s data assets up to date in terms of compliance and access
  • BUILD INFRASTRUCTURE Resolving contemporary problems to provide a platform for growth that is dependent on data and artificial intelligence
  • COMMERCIALIZE Undertaking a digital transformation where products and service offerings leverage data and AI as core components

CDO Role Definition

Address Legacy Data Issues

  1. Identify and resolve legacy problems to bring the organization’s data assets up to date in terms of compliance and access
  2. Inventory the organization’s data asset
  3. Create the Data catalog , meta data, business glossary
  4. Establish basic Data Standards
  5. Audit Compliance with respect to any regulations, especially privacy / data protection
  6. Establish basic enterprise wide governance
  7. Ensure a robust and sustainable set of access controls
  8. Document the data life-cycle processes, identify and fill gaps
  9. Provide visibility to stakeholders of available data within the organization


Lay Foundations for a Digitally Enabled Organization

  1. Establish infrastructure, governance and mindset as a platform data and artificial intelligence driven growth
  2. Information asset management best practice (data management standardization, utilization, and quality of the Company’s information assets)
  3. Bridge between business and technology (both will lead, e.g. chief data id’s from data and chief digital id’s from business) moderate enterprise data requirements
  4. Governance framework and steering committee (make it a strategic concern)
  5. Define roles and responsibilities related to data management, train data stakeholders fostering a data protection culture
  6. Establish and lead Data Governance Steering Committee
  7. Collaborate with legal, biz ops, compliance, BI, and info sec cross-functional processes and correct ownership of data
  8. Leadership over GDPR, CCPA data governance compliance ongoing, with respect to our customer/user data
  9. Own and manage data validation processes, resolve weaknesses and manage risks


Digital Strategy Execution

  1. Undertaking a digital transformation where products and service offerings leverage data and AI as core components
  2. Sponsor and champion enterprise data strategies, data asset valuation and the data P&L(include data supply and demand chains)
  3. Define strategic priorities for development of information-based business capabilities
  4. Establish and govern an Enterprise Data Roadmap to include internal processes, commercialization and investment
  5. Implement a data quality framework to establish standards, controls and associated metrics for all dimensions of data quality (accuracy, completeness, consistency, integrity, reasonability, timeliness, uniqueness, and validity)
  6. Identify new business opportunities pertaining to the use of information assets
  7. Own the strategy for monetization of data across group properties and the development of data products
  8. Own the vision for and creation of both an internal admin view of consumer data, and consumer facing preference center
  9. Determine where to cut costs and increase revenue based on insights derived from data



  • Data roadmap program oversight
  • Executive data-driven strategies
  • Effectively communicate the status, value, and importance of data collection to executive members and staff
  • Driving change and providing consultation for senior business leadership and executives


Data Science

  • Experience building and leading data science organization or practices
  • High-level Data Science
  • Machine Learning
  • BI and Data Analytics
  • Building complex data pipelines (ETL)
  • Machine Learning Models,
  • Partnering with Data Scientist in SWE environment
  • Design, development, and validation of descriptive, predictive, prescriptive, and applied analytics.



  • Data governance and data governance process management
  • Data quality analytics monitoring and evaluation
  • Knowledge of relevant applications, big data solutions, and tools
  • Deep knowledge and expertise of US/EU privacy laws, including GDPR and CCPA (PIPEDA a plus, but not required)
  • Experience with internal controls and security audits, including SOX, PCI, ISO 27001 and SOC-II



  • Experience advocating for data analytics value across a business and to diverse audiences
  • Experience in conducting structured business analysis and generating well defined requirements.
  • Experience in the employment of contemporary data management and maturity assessment frameworks.
  • Proficiency in data classification for security, usage, protection, and enterprise communication.
Scroll Up