Connecting Data Products to Business Strategy #73
Description
Which problem is this feature request solving?
What if your data product specification could explain not just what a product is, but why it exists and how success is measured?
In most organizations, business strategy and data infrastructure live in separate worlds. Business leaders speak in terms of outcomes, objectives, and KPIs. Meanwhile, data teams manage pipelines, schemas, APIs, and access rules. Somewhere in between, the connection between the purpose of data and the implementation of data often gets lost.
Describe the solution you'd like
Introducing productStrategy: A New Block in ODPS
This is where the Open Data Product Specification (ODPS) steps in with a bold vision. With a new addition under consideration — a productStrategy block — ODPS aims to embed business intent directly into the specification of a data product. Not as documentation in a PowerPoint deck, but as structured, machine-readable, and version-controlled metadata. This means strategic goals can be written into the same YAML file that defines your pricing plans, SLAs, and data access.
Let’s look at a basic example. Imagine you’re managing a data product for real-time event detection in a smart city context. Here’s how the strategic intent and business goals might look embedded directly in the ODPS YAML:
This block captures the business case behind the data product. It clarifies why it exists, what outcomes it targets, and how success will be measured. These are no longer abstract strategy slides — they’re now part of the living, operational spec.
This allows product managers, data owners, and even AI copilots to understand not just what the product delivers — but who it’s meant to serve and what kind of value it’s expected to produce.
This approach boosts alignment, consistency, and auditability across teams. A national sustainability program, for example, could maintain a central KPI profile repository and ensure all participating data products link back to these metrics.
What makes this even more powerful is how naturally it supports automation and observability. With KPIs declared at the product level, performance dashboards can be generated automatically. Alerts can be triggered when targets are missed. Adoption and revenue can be tracked without building separate, disconnected systems — it all starts with the YAML.
Why This Changes the Game
ODPS is becoming more than just a spec. It’s evolving into a strategic operating system for the modern data economy. It transforms every data product into a traceable, explainable unit of value. CIOs and data governance leaders can finally trace business impact at scale, while AI agents can answer the question, “What strategic value does this product provide?” — because the answer is now encoded, explicitly, in the product’s spec.
Can you submit a pull request?
Yes.