Discovery-Driven Planning
Plan assumptions, not just activities
Discovery-Driven Planning (DDP) is a planning approach designed for ventures with high uncertainty. Instead of a traditional business plan built on assumptions treated as facts, DDP makes assumptions explicit, sets milestone "assumption tests" to validate them, and converts projections into "reverse income statements" that reveal what must be true for the plan to work.
Developed by Rita Gunther McGrath and Ian MacMillan, first published in the Harvard Business Review in 1995. Extended in McGrath's book "The Entrepreneurial Mindset" (2000).
Use Discovery-Driven Planning when
- ✓New product lines, market entries, or innovation projects where key assumptions are unproven
- ✓Internal ventures or growth initiatives that need structured milestone-based investment gates
- ✓Budget planning for high-uncertainty roadmap items that require staged funding
- ✓Teams communicating with finance or leadership who need an assumption-based forecast model
Avoid it when
- ✗Well-established products with known unit economics — traditional planning is more efficient
- ✗Short-horizon execution work where the assumptions are already validated
- ✗Teams without access to financial modelling capability
Key Concepts
Start from the required profit/ROI and work backwards to determine what the product must achieve in revenue, volume, and margin.
The operational requirements (headcount, COGS, marketing spend) needed to deliver the reverse income statement targets.
A plan that stages investment around assumption checkpoints rather than activity completion dates.
An explicit list of every assumption the plan depends on, ranked by impact and certainty. High-impact, uncertain assumptions get tested first.
In DDP, a deliverable is something that tests an assumption, not just completes a task. Success is learning, not output.
A go/no-go decision point where validated assumption tests determine whether to continue, redirect, or stop the initiative.
How it works
Frame the business opportunity and the required financial returns (reverse income statement).
Surface every assumption the plan depends on. Make the implicit explicit. Rank by impact and uncertainty.
For each high-impact assumption, design the cheapest test that would validate or invalidate it.
Run assumption tests. Update the plan based on results. Go/no-go at each checkpoint based on validated data.
Tools that support Discovery-Driven Planning
Industry standard for software development teams — most PMs will encounter Jira in their career
Exceptionally intuitive and visually clean interface — one of the lowest onboarding friction tools for non-technical teams
Highly visual and intuitive interface with color-coded boards — one of the easiest PM tools for non-technical teams to adopt
All-in-one platform replacing multiple tools — docs, whiteboards, goals, time tracking, chat, and project management in a single workspace
Unmatched flexibility as an all-in-one workspace — combines docs, wikis, databases, and project management in a single tool
Spreadsheet-familiar interface makes adoption easy for teams transitioning from Excel — minimal training needed for basic use
Extremely intuitive drag-and-drop Kanban interface — virtually zero learning curve, new users productive within minutes
Best-in-class infinite canvas experience — the gold standard for collaborative whiteboarding with real-time multiplayer editing
Frequently Asked Questions
A standard business plan projects future performance based on assumptions that are rarely made explicit. DDP explicitly identifies every assumption, ranks them by risk, and builds a plan around testing them. Progress is measured by learning validated, not activities completed.
Yes — they are complementary. DDP provides the financial and strategic framework (what assumptions must be true for this to work). Lean Startup provides the experimental methodology (how to test those assumptions quickly). Use DDP for the planning layer and Lean Startup for the execution layer.
Start with your required return (e.g. the profit needed to justify investment) and work backwards: how much revenue is needed? At what price? From how many customers? At what conversion rate? Each step surfaces the assumptions your plan depends on, making them testable.