Data vs. Business Strategy – A Plea for a Common Language
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    Data vs. Business Strategy – A Plea for a Common Language

    Data Strategy
    Playing to Win
    AI
    Analytics
    Digital Transformation

    Executives and strategy experts rely on well-established frameworks to design and implement business strategies. Yet, rather than applying these proven methodologies, many organizations attempt to redefine strategy in the context of data and AI as a foundation for becoming data-driven.

    The result? In the context of proven strategy frameworks, many data strategy definitions are fundamentally flawed.

    Why do we, as data professionals, reinvent the wheel when it comes to strategy instead of standing on the shoulders of giants?

    This is the topic of my latest article on towards data science: "Data vs. Business Strategy – Which is Responsible for What?". Below are its main takeaways:

    • ✔ As organizations strive to become data-driven, the term data strategy has gained significant attention.
    • ✖ However, there is no universal consensus on what a data strategy truly entails.
    • ✖ Most existing data strategy definitions do not align with fundamental business strategy principles.
    • ✖ A data strategy is NOT a separate entity that defines how an organization wins with data & AI—this is the core job of the business strategy.
    • ✔ If data, analytics, and AI contribute to your company's ability to win, the relevant choices are simply an integral part of your business strategy.

    Why Does This Matter?

    Becoming data-driven is a complex, organization-wide effort—one that requires a shared language and a joint strategic approach.

    Data and AI are enablers, but they are not the center of the universe justifying a separate approach to strategy. Here the links to my articles:

    What’s your perspective? Do you agree that data strategic choices must be embedded within business strategy? Let’s discuss!