Data leadership
Investing for value
Choose the data and AI projects that bring measurable value for the business, and stop the ones that do not.
Investing for value means comparing data and AI projects by what they bring to the business (revenue, costs avoided, risks reduced) against what they cost, including the running costs after launch.
Budgets are limited and every project competes with others. Funding the most visible or most fashionable projects rather than the most useful ones erodes the credibility of the data team with management.
Useful habits: agree on the expected result and how it will be measured before starting, start small, review value regularly, and stop or reshape a project that does not deliver instead of letting it run.
In the reports of your games, every answer linked to this skill counts: the skill is shown as acquired from 80% of correct answers, and in progress from 50%.
Games that train this skill
Play them for free, without an account, then adapt them for your teams.
