Why is a Data Strategy important?
Data Strategy is a "Must Have". Five Reasons Why You Need a Data Strategy:
- The role of data within a company has changed; data is now a strategic resource. A data strategy must clarify the future role of data in a company’s business model.
- Advances in data science and artificial intelligence give rise to many data initiatives in a company. A data strategy creates company-wide capabilities for the use of artificial intelligence and data science at scale. A data strategy helps to align the increasing number of (local) data initiatives with common goals and to build on the organization and infrastructure.
- Today, important data is often only available in “silos”. A data strategy ensures that businesses overcome the “silos” and data can be used enterprise-wide across systems and departments.
- Data defects and poor data quality hinder digitalization. A data strategy defines responsibilities for data and data quality and ensures that important groundwork is done.
- Legal and regulatory requirements for data are getting more widespread. A data strategy analyzes the relevant legal and regulatory requirements as well as customer expectations and provides guidelines for the collection, management and use of data.
What is a Data Strategy?
A company's data strategy answers questions around:
- how a company will use data to generate value – typically with data-driven insights and business processes, and data-enabled business models (=data monetization),
- how a company manages data to generate value, i.e. collecting, storing, processing and distributing data (=data foundation)
The data strategy defines the capabilities and needs to evolve reflecting the organization's current state of data maturity.
How to Build a Data Strategy
To help companies create their own data strategy, the member companies and researchers of the CC CDQ have developed a blueprint: the "Data Strategy Canvas". It is a visual design tool, defining the core elements and guiding questions to be addressed.
Get data strategy canvas now
Print it as a poster and use it in workshops with business experts, data managers, data scientists and other stakeholders to discuss and define the key elements of your data strategy.
The "Data Strategy Canvas"
The strategic layer defines the Need for Action, Vision, Mission & Scope and Business Value
- Need for action defines the motivation for a data strategy
Where do we stand? Why do we have to change? - Vision defines the aspiration for data
What is data's future role? - Mission and scope set the boundaries and defines the purpose for the data program/initiative and (federated) data organization
What is the purpose and scope of our data initiatives and organization? - Business value explains how data contributes to business success
What is the value contribution of data to the business?
The operational layer includes data "use cases" and capabilities
- Key capabilities define the capabilities that are needed to achieve the vision and realize data use cases.
Which organizational capabilities do we intend to build or improve? E.g. People, roles and responsibilities; Processes and methods; Performance and metrics
Which technical capabilities (and technology) do we intend to build or improve? E.g. Data life-cycle; Data architecture; Data applications
The implementation layer covers the Code of Conduct and Transformation.
- Code of conduct describes the future mindset and culture related to data, both internally (employees) and externally (customers and partners)
What are the values and guiding principles for data? - Transformation defines the implementation and execution roadmap for the data strategy.
What is the roadmap to implement the data strategy? How will the data strategy be executed?
Do you have questions on Data Strategy?
Do you need support or advice in developing your company-wide data strategy? Our data management experts are happy to help you and answer your questions.
