Engaging in vibrant discussions around data products, it's clear that many organizations are still in the fabrication phase. This means they spend about 80% of their time building infrastructure and laying the groundwork, with only 20% dedicated to actually creating data products. It's time to shift this balance. We need to move to the assembly phase, where 80% of the effort is spent assembling products and only 20% on fabrication.

Moving Towards an Assembly-Line Approach

The focus needs to change not just in terms of technology and data, but also in the way businesses operate. The challenge is that many business teams struggle to define and drive data product production effectively. Often, data teams complain that they don't get clear requirements from the business, while the business side can't frame their needs in a way that's actionable for the data team. This disconnect hampers progress.

Creating a Structured, Iterative Process

To address this, we need a structured yet flexible approach that allows data and business teams to define, shape, explore, and quickly build, test, and operate data products in collaboration. This is the essence of true Data Product Management. Here’s a high-level framework to guide this transformation:

1. Data Product Pyramid

Think of a hierarchy of reusable Data Products that come together to solve specific business problems. This pyramid structure helps prioritize and organize data products to build upon each other, creating comprehensive solutions that add real value.

2. Data Product Funnel

An iterative process for creating and refining data products, the Data Product Funnel supports an evolutionary business strategy. This approach ensures continuous improvement and alignment with changing business needs.

3. Implementation Framework

Combining fast experimentation with robust control over Data Product infrastructure, this framework balances innovation and reliability. It ensures that while new ideas are quickly tested, they are also governed appropriately to maintain consistency and compliance.

Overcoming the IT Mindset

A significant part of this transformation involves shifting away from the traditional IT mindset. In IT, success often means building a well-designed platform that the business can use. However, in the realm of data, success means continuously creating and optimizing value. This requires active partnership between the Chief Data Officer (CDO) and the business, focusing on co-creating solutions rather than just gathering requirements.

The Role of Business Value Specialists

To bridge the gap between business needs and data capabilities, organizations need business value specialists. These professionals can guide, challenge, and help the business frame the right questions, ensuring that the data products developed are truly valuable. This role should be part of a multidisciplinary team that can quickly produce, test, and iterate data products.

The Importance of an Operating Model

For data products to be effective, the right operating model is crucial. This includes people, processes, and technology harmonized behind a common goal. While the technology is essential, particularly for supporting agile assembly and rapid prototyping, the focus must first be on understanding business needs and how to deliver on them effectively.

Conclusion

The journey towards effective Data Product Management is just beginning. By shifting from a fabrication-focused approach to an assembly-line model, organizations can better align their data initiatives with business strategies. This requires a collaborative, iterative process that integrates business and data teams, guided by a clear understanding of the value creation process.

Ultimately, the goal is to move from asking "What are the requirements?" to "What decisions need to be made?" and "What questions need to be answered?" This shift in perspective will ensure that data products are not just outputs but outcomes that drive meaningful business impact.

Let's continue the conversation and explore how we can implement these changes in our organizations to realize the full potential of data products. Your feedback and insights are invaluable as we navigate this exciting transformation.