I've been deep in Tony Ulwick’s Outcome-Driven Innovation (the quantitative version, not Christensen’s) for the last few months and got tired of doing the manual heavy lifting every time.

So I built a Claude plugin that does most of the heavy work:

What it does:

• /run-synthetic-survey "cut wood in a straight line" → Mines real online feedback, creates realistic personas, runs a full synthetic ODI survey, and gives you opportunity scores + segmentation
• /createodicanvas → Generates the full ODI canvas
• /computescores + /runsegmentation → Real opportunity algorithm + outcome-based segments
• /generatevalueprop, /buildroadmap, /outcometospec → Turns insights into value props, roadmaps, and measurable engineering specs
• Plus job definition, outcome extraction, netting, competitive analysis, Growth Strategy Matrix, etc.

It produces all six final artifacts from Ulwick’s method in one flow.

Installation (super simple):

Bash

npx skills add shikhirsingh/jtbd-odi-plugin

Then restart Claude and try:

text

/odihelp

or jump straight in with:

text

/run-synthetic-survey "listen to music while on the go"

Repo: https://github.com/shikhirsingh/jtbd-odi-plugin

Who is this for?

• Founders doing early customer research
• PMs tired of feature soup and loudest-voice roadmaps
• Anyone who wants to run real Outcome-Driven Innovation faster

Note: The synthetic survey part is excellent for hypothesis generation and rapid iteration, but I still recommend real human surveys for final decisions (as Ulwick advises).

Would love feedback, bug reports, or ideas for new commands.