Data product management plays a crucial role in unlocking significant business opportunities. To achieve this, it is essential to prioritize problem exploration over immediate solution development. This involves adopting a continuous discovery approach, expanding the existing portfolio based on identified problems, and implementing a portfolio management perspective.

When evaluating business opportunities, it is important to understand the different types of data products and their potential contribution to unlocking these opportunities. These include:

• Platform products: technical products that provide the foundation for data and AI initiatives.
• Data products or data assets: curated data shared in a governed manner.
• Metric products and analytical products: dashboards, reports, and algorithms that provide insights and support decision-making.
• AI products: platforms, technologies, or hardware components embedded with AI capabilities.

The specific type of data product developed should be aligned with the specific business opportunity and its desired outcomes. Data product managers play a critical role in increasing the adoption of existing products and ensuring that new products deliver value.

This process requires continuous effort and adaptation, as data strategies, AI strategies, and product strategies evolve over time. The key to success is to avoid building the wrong products and focus on creating solutions that effectively address the identified problems.

By following these principles and emphasizing continuous discovery and portfolio management, data leaders can significantly increase the success rate of their data and AI initiatives and unlock substantial business opportunities.