Overview
- Based on the 80/20 principle: roughly 20% of effort delivers 80% of value.
- Focus on achieving practical, usable outcomes rather than perfect solutions.
- Avoid analysis paralysis and unnecessary complexity.
Key Principles
- Time and effort tracking: balance marginal gains vs cost of complexity.
- Good enough: deliver usable results rather than perfect models.
- Iterative improvement: refine solutions based on feedback and operational realities.
Understand Project Goals
- Clearly define what success looks like before starting.
- Include measurable outcomes and customer agreement.
- Use a meeting with stakeholders to align on success criteria.
Understand Customer Needs
- Practical implementation of results is critical.
- Understand user skills and context (who will use the model, reports, or analysis).
- Deployment considerations: cloud, local, or hybrid environments.
Performance Considerations
- Performance Dimensions: time, cost, code quality, stakeholder satisfaction.
- Track time and effort, considering diminishing returns and model complexity.
- Focus on core, fundamental features for the MVP.
Minimum Viable Product (MVP)
- Identify the simplest solution that provides value.
- Helps with deployment, operational hurdles, and validating assumptions.
- Allows small wins and prevents scope creep.
- Iterative approach: test, gather feedback, and refine.
Common reasons DS projects fail:
- Fuzzy goals: unclear or unmeasurable success metrics.
- Poor project management: unrealistic timelines or milestones.
- Insufficient resources: software, skills, or expertise gaps.
- Lack of senior management support or incentives.
- Over-complexity: chasing marginal gains at high cost.
Also see: