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🌀 Retrospective: Milestone 1 - Problem Identification

"Regardless of what we discover, we understand and truly believe that everyone did the best job they could, given what they knew at the time, their skills and abilities, the resources available, and the situation at hand."
— Norm Kerth

This retrospective captures our reflections on Milestone 1: Problem Identification, highlighting what worked well, what didn’t, and how we can improve moving forward. Our objective is to continuously refine our collaborative process, learning from experience to enhance efficiency and impact.

Strategy vs. Board Reflection

  • What parts of our plan went as expected?

    • Our structured analysis of the syllabus clarified Milestone 1 expectations.
    • Dividing domain research tasks among team members enabled broad and efficient coverage.
    • Collaborative problem statement discussions were focused and constructive, leading to a coherent direction.

  • What parts of our plan did not work out?

    • We spent too much time in broad brainstorming, which delayed narrowing our focus.
    • Time estimates for domain research were optimistic, causing some last-minute rushes.

  • Did we need to add things that weren't in our strategy?

    • An early feasibility check on our research question helped ensure it was practical and data-answerable within the project scope.

  • Or remove extra steps?

    • We gradually streamlined internal communication, adopting more efficient tools and workflows for sharing progress and findings.

The Four Points

Stop Doing

  • Unbounded brainstorming: Introduce clearer time limits or criteria for early ideation to avoid scope drift.
  • Underestimating research depth: Acknowledge the iterative nature of research and plan time accordingly.
  • Delaying feasibility checks: Ensure potential research questions are grounded in data availability and practical constraints from the start.

Continue Doing

  • Targeted task assignment: Delegating research subtopics ensured comprehensive domain understanding.
  • Regular communication: Check-ins and open channels helped us resolve blockers early.
  • Leveraging diverse input: Multidisciplinary perspectives refined our framing of the problem.
  • Proactive documentation: Our living documentation (README.md, planning notes) was key for transparency and traceability.

Start Doing

  • Structured ideation frameworks: Use tools like “How Might We” or mind maps to balance creativity with focus.
  • Early scan for data sources: Identify data availability during problem ideation to prioritize feasible directions.
  • Dedicated synthesis time: Reserve sessions specifically for aligning individual insights into a shared understanding and deliverables.

Lessons Learned

  • Framing matters: A well-scoped, answerable problem is the cornerstone of a successful data project.
  • Research is iterative: Progress often requires looping back, adapting as new insights emerge.
  • Teamwork drives results: Collaboration, trust, and shared ownership are essential—especially in the ambiguous early stages.
  • Constraints empower clarity: Project limitations can sharpen focus, guiding us toward achievable, high-impact outcomes.

By reflecting on our process with honesty and openness, we aim to enter Milestone 2 more focused, aligned, and effective.