The Data Product Canvas: Designing Data Products for Sustained Value From Enterprise Data

Abstract

Organisations are increasingly striving to become more data-driven by embedding data into decisions, interactions and processes and by leveraging advanced AI technologies to unlock innovative use-cases. However, many remain unprepared to meet the rising demands for data, analytics and AI. A data product mindset—combining, packaging and delivering data as a product—has emerged as a promising approach to meet the needs of an expanding user base. Despite their popularity, data products are often seen as a purely technical concept, with suitable methodologies and tools for designing them still underdeveloped. This paper introduces the data product canvas, a visual and versatile tool that helps cross-functional teams—comprising business, data, analytics and IT experts—collaboratively design new data products and assess existing ones. The canvas ensures that critical themes are addressed: desirability from the customer perspective, feasibility from the technical perspective and viability from the economic perspective. The practical application at SAP illustrates how the data product canvas supports its data democratisation initiative, showcases real-world examples and offers practical insights to guide future adopters: (a) tailoring designs to different data product types, (b) periodically refining data products to increase their value and (c) systematically assessing requests to build a cohesive data product portfolio.