Data product projects can be challenging to execute as stakeholder requirements are often vague and undefined. In my experience, upfront design of data products can be difficult since the data team may not have the necessary context to create an appropriate solution.

Having numerous meetings to design the first version is often ineffective. However, creating a prototype can be a productive and efficient method of encouraging people to discuss their requirements. Through the creation of a prototype, stakeholders can see, touch and use a tangible representation of the product, and give feedback on its functionality.

Initially, stakeholders may say that the prototype is not what they need and provide further details on the desired functionality, which the data team can use to improve the prototype.

It is essential to inform the data team that some of the prototype materials may not be used, or may end up as appendices in a document. However, prototypes remain one of the most efficient ways of understanding what customers need in a data product.

While some may view this as an inefficient method of working, it is a crucial way to comprehend the true requirements of customers and design a data product that meets their needs.