Capture Data Requirements for Data Products

Rapid requirements gathering using the Information Product Canvas

The Information Product Canvas is a pattern template for capturing the data and information requirements for a single Information Product, in 30 minutes, in a language both stakeholders and data teams understand. In this hands-on, full-day workshop Shane Gibson, the creator of the canvas, teaches you the twelve areas of the canvas, how to complete it interactively with your stakeholders, and how to use it to prioritise what to build first. You spend half the day completing canvases in small groups on a realistic case study, and finish with a hands-on session on using an AI assistant alongside the canvas. You leave able to run the canvas pattern storming workshop with your own stakeholders the next working day.

Course description

Ask a data team what slows them down most and the answer is rarely the technology. It is the gap between what stakeholders ask for and what the team ends up building. Stakeholders and data teams speak very different languages. Requirements take weeks or months to gather, and nobody can say when they are done. They arrive full of ambiguity, describe a dashboard when the real need is a decision, and focus on a specification of what is wanted rather than why it is needed. The data team cannot work out what to build from the requirements, so they guess, build, and then hear the words every data professional dreads: “That’s not quite what I wanted.” Meanwhile the detailed requirements document nobody reads sits in a folder, and the data team is treated as an order taker rather than an enabler by stakeholders.

The Information Product Canvas closes that gap with one shared language and one conversation. It is a pattern template, twelve areas on a single canvas page, for defining a single Information Product: the business questions it must answer, the actions and outcomes those answers drive, who will use it and how, what data it needs, what is in and out of scope, and how big a job it is.
The stakeholder and the data team fill it in together, in one 30-minute session, so the requirements are validated in real time rather than weeks later. Because the canvas captures the why as well as the what, it also becomes the basis for prioritising across many Information Products and for feeding the rest of the Information Value Stream: the concept model, the transformation logic, the metric definitions, the acceptance tests and the build.
It is a pattern, not a framework: pick it up, use it, change what doesn’t fit, keep using it. Shane created the canvas and has iterated it with data and analytic teams for more than a decade. It is documented in his book “An Agile Data Guide to Information Product Canvas” and extended by more than ninety companion articles.
In this full-day workshop you learn the canvas by using it.

After an overview of the pattern template and the problems it solves, we work through the twelve canvas areas step by step with a worked example, explaining what is captured in each area and why, with Q&A after each one. Half the day is spent in small groups populating canvases based on a realistic case study organisation, so you practise the pattern rather than watch slides about it. You then learn how to facilitate the canvas live with stakeholders using the Pattern Storming workshop format, review real-world canvases from a range of industries, and see how completed canvases are used to prioritise and to drive delivery.
The day closes with a hands-on session on using an LLM assistant such as Claude or ChatGPT alongside the canvas, bring your laptop and your own LLM access to take part. No prior experience with the canvas, or with agile ways of working, is required.

Learning objectives

• Capture the requirements for one Information Product in 30 minutes: Deliver the data elephant one bite at a time, defining requirements in small, well-formed chunks the data team can deliver in days or weeks rather than months.
• Speak a shared language: Learn a data requirements language that both stakeholders and data teams understand, so one conversation produces requirements the stakeholders recognises and the team can build from.
• Collaborate visually with stakeholders: Fill in the canvas in front of stakeholders and get real-time validation, instead of writing a document and waiting weeks for feedback.
• Capture the what and the why: Elicit the actions stakeholders will take and the business outcomes they expect, turning the data team from order taker into business value enablers.
• Make scope and priority visible: Use Will / Won’t, T-shirt sizing and stack ranking so stakeholders can make trade-off decisions and see at a glance what gets built first.
• Facilitate the canvas and teach it to your team: Run the structured Pattern Storming workshop with your own stakeholders, avoid the common anti-patterns, and leave with a repeatable pattern your whole team can run the next working day.
• Use AI alongside the canvas: Apply practical techniques for using an LLM assistant to draft, challenge and refine canvases, while keeping the stakeholder conversation at the centre.
• Use the completed canvas downstream: See how a well-formed canvas feeds concept models, acceptance testing and prototyping, so the requirements keep paying off long after the workshop.

Who is it for?

This workshop is for anyone who gathers, defines, prioritises or builds from data and information requirements, on either side of the conversation. No prior experience with the canvas, or with agile ways of working, is required.

• Business Analysts who gather data requirements on behalf of a data team
• Data Product Managers and Product Owners who need to define and prioritise data work
• Data Analysts who want to agree outcomes with stakeholders before starting work
• Data Engineers who are frustrated with requirements they cannot build from
• Data Architects and Data Modellers who need well-formed requirements as input to their models
• Data Leaders looking for one repeatable requirements pattern for their team
• Agile Coaches and Scrum Masters who want to add a data-specific pattern to their toolkit
• Business stakeholders who commission Information Products and want to be understood the first time.