Falantes

Srujan Akula
CEO at the Modern Data Company
John Spens
Managing Director for North America Data & AI Service Line at ThoughtWorks

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Implementing A Culture To Create Data Products

May 2024

Summary

In this enlightening session, the conversation revolved around the complexities of developing data products, highlighting the human and procedural elements involved. Experts Richie, Srujan Akkola, and John Spence provided wisdom on how data products can be used to generate value for organizations. The discussion initiated with defining data products as organizational resources that provide insights beyond mere data sets, with attributes such as discoverability, security, and reusability. Examples like Customer 360 and the longitudinal health record showcased the practical applications and benefits of data products. The discussion further explored the roles central to building these products, specifically focusing on the essential role of the data product manager who connects technical and business domains. The experts discussed the significance of aligning data products with business strategies and the possible pitfalls such as scope creep and inadequate data quality. They highlighted the need for a cultural shift within organizations to treat data as a core resource, advocating for a decentralized approach to team structures. Ultimately, the session underscored the transformative potential of data products in enhancing business processes, improving customer experiences, and driving innovation.

Key Takeaways:

Data products should be viewed as organizational resources with attributes of discoverability and security.
Successful data products like Customer 360 combine data from multiple sources to provide comprehensive insights.
The role of data product manager is essential, requiring a mix of business knowledge, data comprehension, and management skills.
Aligning data products with business strategy is vital for demonstrating value and driving organizational change.
Common challenges include data quality problems, scope creep, and the need for a cultural shift in treating data as a resource.

Deep Dives

The Role of Data Product Manager

The data product manager is often character ...
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ized as a 'unicorn' role, requiring a unique combination of skills. They must possess a deep comprehension of the business domain, the capacity to engage with technical teams, and managerial skills to coordinate project delivery. As John Spence noted, "The data product manager acts as a coordinator, ensuring that the data is represented accurately and is aligned with organizational needs." This role connects the gap between business and technology, necessitating a strong grasp of data modeling and a strategic vision for how data products can drive business outcomes.

Developing Data Products Aligned with Business Strategy

Aligning data products with business strategy is a key step in ensuring their success. Srujan Akkola stressed starting with simple business problems to demonstrate quick wins and build momentum. "Pick a specific business problem and create a thin slice end to end," he advised, highlighting the significance of demonstrating value early on. The discussion highlighted the need for organizations to view data products as integral to their strategic goals, advocating for a cultural shift where data is treated as a core organizational resource.

Common Challenges in Data Product Development

Data quality and scope creep emerged as significant challenges in data product development. Poor data quality can undermine trust and hinder the utility of data products, while scope creep can lead to projects that are difficult to manage and deliver. As John Spence articulated, "You must constantly reinforce the value of your data products to prevent them from becoming just another cost of doing business." The discussion emphasized the importance of setting clear objectives and maintaining focus to mitigate these risks.

Organizational Culture and Structure

The discussion illuminated the significance of organizational culture in supporting successful data product initiatives. A decentralized approach was recommended, where data teams are closely aligned with business units to ensure responsiveness and relevance. Srujan Akkola pointed out the necessity of having leadership buy-in and treating data as a critical business resource. The experts stressed the need to build a culture that values data-driven decision-making, with an infrastructure that supports agile and iterative development of data products.