Designing Step-Projects to Validate Product Ideas
A skill from the GIST Planning Framework: Goals, Ideas, Steps, Tasks method.
Design GIST step-projects as small, time-boxed experiments that test an idea's riskiest assumption and end in a clear continue, change or stop call.
Design GIST step-projects as small, time-boxed experiments that test an idea's riskiest assumption and end in a clear continue, change or stop call.
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At a Glance
| Field | Value |
|---|---|
| Difficulty | Intermediate |
| Time to Learn | A few hours to learn, several step-projects to get good at |
| Outcome | You turn a promising idea into a sequence of small step-projects, each with a question, a method, a success threshold and an end date, and you decide what to do next from the evidence each one produces. |
| Prerequisites | A goal with a measurable metric, a ranked idea bank, access to users or usage data |
| Part of | GIST Planning Framework |
Overview
Step-projects are the third layer of the GIST Planning Framework. Itamar Gilad introduced them to replace the long project that usually follows a promising idea. In his GIST article, turning an idea into a 9-18 month project is a common and costly mistake, because most ideas are not worth the investment. Instead, the bigger project behind the idea is broken into small step-projects, each no more than 10 weeks long, executed one at a time (GIST Framework).
Each step-project is an experiment. Gilad ties this directly to Lean Startup's Build-Measure-Learn principle, in which a team turns ideas into products, measures how customers respond, and learns whether to pivot or persevere (Lean Startup principles). His example sequence for one idea is mockup, then prototype, MVP, dogfood, beta and launch. In a successful progression, each step puts a somewhat more complete version of the idea in front of more users for a longer time.
The payoff is that ideas that do not work are dropped early and ideas that work get more investment, without pitching or politics. Because the steps are small, a team can test many more ideas in parallel for the same effort. That matters because most ideas fail: the Microsoft paper Gilad cites found that only about 1/3 of ideas improved the metrics they were designed to improve (Online Experimentation at Microsoft).
In his later work Gilad calls this layer Steps and defines a step broadly, as any type of assessment, fact finding or experimentation activity (GIST Scorecard). A step does not have to involve code. The output of this skill is a step-project brief: the idea, the assumption under test, the method, the success threshold, the time box, the owner and the decision each result would lead to.
How It Works
Every idea rests on assumptions: that users have the problem, that they will find the feature, that it changes their behavior, that the business can support it. A step-project tests the assumption that is both most uncertain and most damaging if wrong. Testing a safe assumption first produces evidence nobody needed.
Gilad sorts validation methods into levels, from quick internal checks to controlled experiments. In his validation article, Assessment covers quick internal checks such as goal alignment, ICE analysis, business modeling and assumption mapping. Fact Finding gathers existing evidence through data analysis, user interviews, surveys, field research and competitor analysis. Tests put something in front of users: usability tests, human-operated tests, smoke tests, dogfooding and early-adopter programs. Experiments use a control group, such as A/B tests and holdback experiments. In the book this becomes the AFTER model, adding Release-results as a fifth level (book resources).
How far up those levels an idea must go depends on what it costs and how risky it is. In How Much Product Discovery Is Enough?, Gilad says assessment alone can justify only very cheap, low-risk changes that are easy to reverse, supporting data can justify incremental features, and most ideas need tests or experiments. New products, major revisions and pricing changes need the most rigorous tests. His advice is to start with cheaper modes of validation and move to more expensive ones only if the idea still looks good.
A step-project needs a threshold set before it starts. The team writes down what result would lead it to continue to the next step, what would lead it to change the idea, and what would lead it to stop. Setting thresholds after seeing the data invites the team to explain away weak results.
Results flow back into the idea bank. On the GIST board, Gilad describes ICE scores being updated from experiment results on the spot, failed ideas removed with their steps, and new ideas added in their place (The GIST Board). A step that raises Confidence earns the idea its next, larger step. A step that lowers it frees the team for the next candidate.
Step-by-Step Guide
Step 1: Restate the idea as a testable hypothesis
Write the idea in one sentence: what you will do, which metric it will move, and why. Check its current ICE score and the evidence behind its Confidence. If the idea is too vague to state this way, send it back to the idea bank for more definition.
Step 2: List the assumptions
Write down everything that must be true for the idea to work: about the user's problem, their behavior, the solution's usability, the technology and the business case. Ask "what would have to be true for this to fail?" to surface assumptions nobody has said out loud. Include the ones everyone takes for granted.
Step 3: Pick the riskiest assumption
Rank the assumptions by how uncertain they are and how much damage a wrong one would do. The top one is what this step-project tests. Leave the rest for later steps, in order, so each step answers one clear question.
Step 4: Choose the cheapest method that can answer it
Start at the lowest validation level that could change your mind. A data check or a handful of customer interviews may be enough to kill an idea. Move to smoke tests, prototypes, dogfooding or betas only if the idea survives, and save controlled experiments for ideas close to launch. Match the method to the question: interviews explain why, experiments measure how much.
Step 5: Set the success threshold and the decisions
Choose the measure and write down, before starting, the result that means continue, the result that means change the idea, and the result that means stop. Base the threshold on what the next, larger step would need to be worth it. Agree it with the people who will act on the result.
Step 6: Time-box the step
Set an end date and keep the step within Gilad's limit of no more than 10 weeks (GIST Framework), and much shorter for early steps. If the step seems to need more time, split it into two steps that test different assumptions. Name one owner who is responsible for making the step happen.
Step 7: Write the brief and run the step
Put the hypothesis, the assumption, the method, the threshold, the time box and the owner on one page and share it. Add the step to the GIST board under its idea. Run it, break the work into tasks, and avoid changing the threshold or the method partway through without writing down why.
Step 8: Decide and update the bank
At the end, compare the result with the threshold and make the decision you committed to. Update the idea's Confidence and ICE score in the bank, record the evidence, and plan the next step if the idea continues. If it stops, park it with the result attached so the evidence is there when the idea returns.
Best Practices
- Test one assumption per step. A step that tries to answer everything usually answers nothing clearly.
- Start cheap. Gilad's discovery guidance is to move to expensive validation only when the idea still looks good after the cheaper checks.
- Set the threshold before you see the data. Deciding after the fact lets the team rationalize a weak result.
- Grow the audience step by step. Following Gilad's learning milestones, each step should show a more complete version to more users for longer.
- Keep a record of every step, including the ones that failed. Those results stop the team from re-testing the same assumption and raise or lower Confidence for related ideas.
- Treat a stopped idea as a good outcome. Ending an idea after a short test costs far less than building it in full.
Common Mistakes
- Building the whole feature and calling it a step: A step that takes most of a quarter and ships the full idea is a project with a new name. Cut it down to the smallest thing that tests the riskiest assumption.
- No success threshold: Without a threshold agreed in advance, any result can be read as success. Write it down before the step starts.
- Testing the easy assumption: Teams often test what is simplest to measure. Test what is most likely to sink the idea.
- Using an A/B test for everything: Controlled experiments are the most expensive level. Many ideas can be rejected with a data check, interviews or a smoke test first.
- Not acting on the result: If the team builds the original plan whatever the step shows, the step was theater. Make the decision the threshold called for, and record it.
References
- Examples: Worked examples and scenarios
- FAQ: Frequently asked questions
- Parent Method: GIST Planning Framework
Related Skills
- ICE Scoring: Prioritizing Product Ideas by Confidence
- Breaking Step-Projects into Daily Tasks
- Building a Product Idea Bank for the GIST Ideas Layer
Sources
- Itamar Gilad: GIST Framework
- Itamar Gilad: Idea Validation Using the AFTER Model
- Itamar Gilad: How Much Product Discovery Is Enough?
- Itamar Gilad: Building Your Project for Learning and Execution
- Itamar Gilad: The GIST Board and Other GIST Tools
- Itamar Gilad: GIST Scorecard
- Itamar Gilad: Evidence-Guided book resources
- The Lean Startup: Principles
- Kohavi et al.: Online Experimentation at Microsoft
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Other Skills in This Method
Breaking Step-Projects into Daily Tasks
Break a GIST step-project into small, sprint-ready tasks that each trace back to the experiment, the idea and the goal they serve.
Defining Measurable Product Goals in GIST
Define measurable product goals for GIST planning: outcome-based goals with a metric, baseline, target and date that anchor ideas, steps and tasks.
Building a Product Idea Bank for the GIST Ideas Layer
Run the GIST planning ideas layer with a product idea bank: collect ideas from anyone, link each to a goal, triage quickly and park instead of delete.
GIST Planning Cadence: Managing Multi-Cadence Cycles
Set the GIST planning cadence for each layer: yearly goals reviewed quarterly, an always-open idea bank, steps reprioritized each sprint, daily tasks.
Presenting GIST Plans to Stakeholders
Give a GIST planning framework presentation to executives, peers or interviewers: walk one goal down to ideas, steps and tasks, and show the evidence.
ICE Scoring: Prioritizing Product Ideas by Confidence
ICE scoring ranks product ideas by Impact, Confidence and Ease so a GIST team knows which ideas to test first, with Confidence set by real evidence.
Replacing Your Product Roadmap with GIST
A GIST framework implementation guide: replace a feature roadmap with GIST planning through a staged transition that keeps commitments and trust.
Related Methods and Skills
Designing Validated Learning Experiments
Design validated learning experiments: pick the test, from landing page to concierge MVP or Wizard of Oz test, and set pass marks before any data arrives.
Lean Startup Hypothesis Template: Testable Hypotheses
Use a lean startup hypothesis template to turn vague business assumptions into falsifiable statements with a metric and pass mark set before testing.
Types of MVP: How to Choose the Right Format
Compare the types of MVP, from landing page and concierge to Wizard of Oz, piecemeal and single-feature, and pick one that tests your riskiest assumption.
Running the Build-Measure-Learn Loop
Run the build-measure-learn loop as short, planned cycles that each end with a recorded lesson and a decision, so every iteration adds validated learning.
How to Build a Minimum Viable Product (MVP)
How to build a minimum viable product: scope the smallest version that tests your riskiest assumption, instrument it, launch it and decide what's next.
Designing Assumption Tests for OST Solutions
Design assumption tests for solutions on your opportunity solution tree: surface hidden assumptions, map the riskiest, and test them with set criteria.
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