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Building a Data Strategy: Key Steps for Aligning Data with Business Goals

May 2023
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Summary

In an extensive discussion on data strategy, the spotlight is on the essential elements required for organizations to use their data effectively. Key insights include the need for understanding business objectives, the role of proper data tracking, and the difficulties of communication and stakeholder management in data projects. The dialogue also underlines the need for a clear plan in executing a data strategy, with Libba Stanford, a data strategy consultant, sharing her experiences and lessons learned in the field, such as the necessity of aligning data initiatives with business goals and the complexities involved in educating teams on data specifics. The session outlines practical steps for developing a successful data strategy and emphasizes the value of subject matter experts in ensuring data accuracy and relevance. Various examples from Libba's career illustrate both successful and failed data strategy implementations, emphasizing the importance of a thorough understanding of data processes and the necessity of adapting to changing business environments.

Key Takeaways:

  • Successful data strategies begin with a clear understanding of business goals and problems to be solved.
  • Effective data usage requires proper tracking and metadata collection to understand and optimize processes.
  • Communication and stakeholder management are essential for aligning teams and ensuring project success.
  • Involving subject matter experts can help fill the gap between data science and practical business applications.
  • Incremental wins in data projects can encourage executive buy-in and facilitate larger strategic initiatives.

Deep Dives

Understanding Business Objectives

Libba Stanford emphasizes that a ...
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data strategy must begin with a clear understanding of what the business aims to achieve. This involves identifying specific problems the company wants to solve and aligning the data strategy to these objectives. As Libba notes, "What is the business trying to accomplish?" is the fundamental question that guides the development of a data strategy. This initial discovery phase is vital and often overlooked, yet it sets the foundation for all subsequent efforts. Ensuring that executives and teams are aligned on these goals helps prevent miscommunication and misaligned efforts down the line.

Challenges in Data Tracking and Management

Libba shares valuable insights into the importance of tracking data effectively, highlighting the potential pitfalls when this is not done correctly. She recounts a specific challenge where a lack of proper tracking led to inefficiencies and incorrect assumptions in a project. "If it can be measured, you probably want to record it and measure it," she advises, emphasizing the value of comprehensive data tracking in building strong processes. This approach not only supports better decision-making but also helps in setting realistic targets and measuring progress accurately.

Communication and Stakeholder Management

Effective communication is a recurring theme in the discussion, with Libba stressing its role in the success of data projects. She highlights the need to adapt communication to different stakeholders, ensuring that each group receives the information pertinent to their needs. "The way to start with it is understanding what each of the key stakeholders need from you as the leader," she explains, advocating for direct and concise communication. This approach helps maintain transparency and encourages trust among teams, which is essential for overcoming challenges and achieving project milestones.

The Role of Subject Matter Experts

Involving subject matter experts is essential in filling the gap between data science and practical applications, according to Libba. She shares an example where a lack of subject matter expertise led to significant errors in data analysis, illustrating the importance of having knowledgeable individuals who understand both the business context and the data intricacies. "Get your subject matter experts and engage them," she advises, pointing out that these experts can validate outcomes and ensure that data-driven decisions are grounded in reality.

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