Case context: A machine learning team has been working for weeks on improving a model, but progress has been slow. Team members have been splitting time across many small tasks, such as trying different hyperparameters, gathering additional data, and experimenting with new architectures, without a clear sense of which task matters most right now.

Question: Based on the source concept, what should this team consider changing, and why might this change have an outsized effect on their productivity?

Sample answer: The team should reconsider its prioritization and identify the one or few tasks that would have the greatest impact on their goal, rather than splitting effort across many small tasks. Since a few changes in prioritization can have a huge effect on productivity, focusing the team's limited time on the highest-impact task, instead of spreading it thin, is likely to produce much better progress than continuing to work broadly across many low-impact activities.

Key points:

• Team effort is currently spread across many small, possibly low-impact tasks
• The team lacks a clear sense of the highest-impact priority
• A few changes in prioritization can have a huge effect on productivity
• Focusing on the highest-impact task is likely to improve progress
• Recommendation should be grounded in the source claim from p. 7

Rubric: Full credit: response identifies the need to change prioritization/focus, explains that limited effort is being spread across low-impact tasks, and connects this to the source claim that a few prioritization changes can have a huge effect. Partial credit: response identifies a general problem without connecting it to prioritization. No credit: response is unrelated to the case or the source concept.