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Shift the Team Toward the Highest-Leverage Machine Learning Task
Case context: A product analytics group has spent several weeks trying to improve a recommendation model, but the pace of progress has been disappointing. People on the team keep dividing their time among many small efforts, including tuning model settings, collecting more examples, testing alternative feature sets, and trying a new network design. No one is sure which of these efforts should come first.
Question: What should this team change in how it works, and why could that single change make such a large difference to its output?
Sample answer: The team should stop treating every task as equally important and instead choose the one or small set of tasks most likely to move the project forward. Right now, the group’s time is being diluted across several modest activities, so little progress is being made on the work that matters most. Reordering the work so that the highest-value task gets attention first can produce a much bigger productivity gain than continuing to make many small efforts in parallel.
Key points:
- Time is currently fragmented across many separate activities
- The team has not identified the most valuable next task
- Reordering priorities can strongly change overall productivity
- Concentrating on the highest-value work should improve progress
- The answer should reflect the idea that priority changes can have a large effect on team output
Rubric: Full credit: response says the team should refocus priorities, explains that effort is spread over several low-impact tasks, and links this to the idea that changing priorities can greatly improve productivity. Partial credit: response notes the team is disorganized or inefficient without explaining the role of prioritization. No credit: response does not address the team’s work allocation or the productivity concept.
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Related
What effect can a change in prioritization have on a machine learning team?
True or False: A machine learning team's productivity is affected only by very large changes in what it is asked to prioritize.
Small changes in task priorities can strongly change a machine learning team's _____.
Match each project-planning term to its best description.
Order the reasoning steps for revising a team’s priorities
Why Reordering Work Can Greatly Improve ML Team Output
Shift the Team Toward the Highest-Leverage Machine Learning Task
How Prioritization Changes Affect Team Output
Which response best shows a useful change in priority?
True or False: Changing the order of project priorities has little impact on how fast a machine learning team can make progress.