Data Strategy Guidebook: What Every Executive Needs to Know

Don't forget: download the companion "Data Strategy Checklist" which outlines steps to create a data strategy.

In an information economy, every organization needs a data strategy. Today, digital upstarts are disrupting every industry, placing a premium on companies who know how to capitalize on data and analytics. Some need a data strategy to improve operational efficiency, others to grow revenues and profits, and most to achieve both simultaneously. The best data strategies are tailored to each organization’s unique circumstances, culture, and data maturity.

A data strategy is an enterprise-wide plan to harness data and analytics to achieve business goals. At a high level, it is a blueprint for creating a data-driven organization; at a low level it is a set of plans for building a data program and supply chain to acquire, transform, and deliver data to business users for analysis and decision making.

Some industry practitioners think a data strategy is synonymous with a data architecture; it is not. It is bigger than that. A data strategy paints a picture of how data will transform the organization and harmonize conflicting forces, such as governance and self-service, speed and standards. It defines a vision, goals, metrics, risks, and use cases along with detailed plans and a roadmap that specify the people, processes, technology, organization, and cultural change required to achieve the vision.

This report defines what a data strategy is, explains why organizations need them, and explains its core components and how to create one.

Key Takeaways

A data strategy is an enterprise-wide plan to harness data and analytics to achieve business goals.
A data strategy aligns with overall business objectives and helps organizations improve operational efficiency and strategic effectiveness.
A data strategy harmonizes internal conflicts, such as speed and standards, operations and innovation, freedom and control, corporate and business unit, business and IT.
Data strategies evolve from reactive to proactive use of data, but most organizations have difficulty making the leap from one to the other.
At a high level, a data strategy defies vision, goals, metrics, risks, use cases, plans, roadmap, and a program to execute the strategy. At a low level it consists of an organizational framework, change management strategy, and technology strategies for implementing data architecture, data infrastructure, data governance, data analytics, and data innovation.
Creating a data strategy requires lots of input. It should be led by a chief data officer (CDO) or cross-functional team (or both ideally) that solicits feedback from data advocates and consumers across the organization.
Selling a data strategy is the hardest part of creating a data strategy.

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