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Why Becoming Data-Driven Is So Hard

Why Becoming Data-Driven Is So Hard

by Starling Insights

Starling Insights Editorial Board

Observations

ICYMI: In a Harvard Business Review article from early 2022, Author Randy Bean explains why so many organizations struggle to become "data-driven" and how they can overcome these obstacles.

While many leaders see this as primarily a technical challenge, reforming organizational culture is actually the most significant barrier to becoming data-driven. Large organizations that have been around for decades — or even centuries — may not be agile enough to transform overnight. Instead, it will take a concerted, long-term effort to make meaningful change.

Bean lays out three principles on which organizations hoping to become data-driven should focus:

  • Think different. Data leaders recognize that becoming data-driven requires a different mindset. 
  • Fail fast, learn faster. Data leaders understand that individuals and organizations learn through experience, which often entails trial and error. 
  • Focus on the long-term. Data leaders appreciate that the data journey is a transformation effort that unfolds over time. Becoming data-driven is a process.

"To compete in the increasingly data-driven world of the twenty-first century, business leaders must learn from the experience of their predecessors," Bean concludes. "They must actively work to avoid the pitfalls of the past, and benefit from the example of those companies that have pushed forward with success."

In Starling's 2022 Compendium, David Kiron, Editorial Director of the MIT Sloan Management Review, argues that it's no longer simply the case that what you measure determines what you manage. Instead, it is how you determine what to measure that shapes what you manage. AI plays an essential role in this regard, helping leaders to establish a 'predictive alignment' between strategy, operations, and analytics. [Read Here]

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