A process for generating and prioritizing ideas

In this episode of Datadrivet, Joni Lindgren and Jasmin Yaya walk through how Jasmin’s team collects test ideas and decides which ones to run. The team gathers every idea, clusters them into tracks, votes, writes hypotheses and scores them with a modified ICE score. That makes the decision repeatable instead of leaving it to whoever speaks loudest in the room.

Everyone on the team brings every idea they have. Then the team clusters the ideas into themes, or tracks. The team votes on which tracks promise the most learning and the most value for the organization.

The team then writes each idea as a hypothesis in a fixed shape: by doing x, we will reach goal y. If you cannot name the action and the goal, the idea is not ready.

To rank the hypotheses, the team uses a modified ICE score with four parameters. Three are scored from 0 to 5: value, ease of doing it, and learning. The fourth, high risk, is scored as -1 or 0.

The parameters combine into a single score from 0 to 100 percent. The hosts start from the standard ICE model and a shared Google Sheets template the team works from. The scoring approach comes from Daniel Hansson at Signific.

Listen to the full episode of Datadrivet for the walkthrough of the template and the scoring.