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💻Information Systems

Key IT Project Management Methodologies

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Why This Matters

When you're tested on IT project management methodologies, you're not just being asked to recall names and definitions—you're being evaluated on your understanding of when and why organizations choose specific approaches. The core tension in project management is between predictability and adaptability: some projects need rigid structure and upfront planning, while others thrive on flexibility and rapid iteration. Understanding this spectrum is essential for exam success.

These methodologies also demonstrate key Information Systems concepts: risk management, stakeholder alignment, resource optimization, and continuous improvement. Each approach represents a different philosophy about how to handle uncertainty, manage teams, and deliver value. Don't just memorize what each methodology does—know what problem it solves and when it's the right tool for the job.


Sequential and Structured Approaches

These methodologies prioritize upfront planning, documentation, and predictable phases—ideal when requirements are stable and changes are costly.

Waterfall

  • Linear, sequential phases—each stage (requirements → design → implementation → testing → deployment) must be completed before the next begins
  • Thorough documentation at every stage creates clear audit trails and reduces ambiguity for large teams
  • Best for low-uncertainty projects where requirements are well-defined upfront and changes are expensive or impractical

PRINCE2

  • Seven principles, themes, and processes provide a comprehensive framework emphasizing organization, control, and quality
  • Controlled environment focus with clearly defined roles, responsibilities, and decision-making authority at each level
  • Business case driven—requires regular assessment of project viability and alignment with organizational objectives

Critical Path Method (CPM)

  • Identifies the longest sequence of dependent tasks—the critical path determines minimum project duration
  • Float time calculation reveals which tasks have scheduling flexibility without delaying the overall project
  • Essential for complex, interdependent projects where resource allocation and timing directly impact delivery

Compare: Waterfall vs. PRINCE2—both emphasize structure and documentation, but PRINCE2 adds explicit governance principles and continuous business case validation. If an FRQ asks about government or enterprise projects, PRINCE2 is your go-to example.


Agile and Iterative Approaches

These methodologies embrace change, deliver value incrementally, and prioritize customer feedback over rigid plans—ideal when requirements evolve.

Agile

  • Iterative, incremental delivery breaks projects into short cycles that produce working functionality
  • Customer collaboration over contract negotiation—continuous feedback loops ensure the product meets actual user needs
  • Adaptive planning allows teams to respond to changing requirements rather than fighting against them

Scrum

  • Time-boxed sprints (typically 2-4 weeks) create predictable delivery rhythms with shippable increments
  • Three defined roles—Scrum Master (facilitator), Product Owner (requirements), and Development Team (execution)
  • Daily stand-ups and sprint retrospectives enforce transparency, inspection, and continuous adaptation

Extreme Programming (XP)

  • Technical excellence practices—pair programming, test-driven development, and continuous integration reduce defects
  • Frequent small releases with heavy customer involvement throughout the development process
  • Simplicity principle—build only what's needed now, refactor continuously, avoid over-engineering

Compare: Scrum vs. XP—both are Agile frameworks, but Scrum focuses on project management structure (roles, ceremonies, sprints) while XP emphasizes engineering practices (pair programming, TDD). Many teams combine both.


Flow-Based and Continuous Improvement Methods

These methodologies focus on optimizing ongoing work rather than managing discrete projects—ideal for maintenance, support, and process refinement.

Kanban

  • Visual workflow boards display work items moving through stages, making bottlenecks immediately visible
  • Work-in-progress (WIP) limits prevent overloading teams and improve flow efficiency
  • Continuous delivery model—no fixed iterations, work flows through the system as capacity allows

Lean

  • Maximize value, minimize waste—systematically eliminates non-value-adding activities from processes
  • Respect for people combined with continuous improvement (kaizen) creates sustainable efficiency gains
  • Cross-industry applicability—originated in manufacturing but widely adopted in software and service industries

Compare: Kanban vs. Scrum—Kanban has no fixed iterations or prescribed roles, focusing purely on flow optimization, while Scrum provides more structure with sprints and defined ceremonies. Kanban suits ongoing operations; Scrum suits discrete projects.


Quality and Data-Driven Methodologies

These approaches use measurement and statistical analysis to drive improvement—ideal when defect reduction and process consistency are primary goals.

Six Sigma

  • Statistical defect elimination—targets fewer than 3.4 defects per million opportunities through rigorous analysis
  • DMAIC framework (Define, Measure, Analyze, Improve, Control) provides a structured improvement cycle
  • Data-driven decision making—uses statistical tools to identify root causes rather than relying on intuition

Rational Unified Process (RUP)

  • Four phases—Inception, Elaboration, Construction, and Transition—each with specific goals and milestones
  • Risk-driven iteration addresses highest-risk elements early through iterative development within a structured framework
  • Hybrid approach—incorporates best practices from both Waterfall (phases) and Agile (iteration, feedback)

Compare: Six Sigma vs. Lean—both focus on efficiency, but Six Sigma targets defect reduction through statistical analysis while Lean targets waste elimination through process streamlining. Organizations often combine them as "Lean Six Sigma."


Quick Reference Table

ConceptBest Examples
Sequential/Predictive PlanningWaterfall, PRINCE2, CPM
Iterative/Adaptive DeliveryAgile, Scrum, XP, RUP
Flow-Based Continuous WorkKanban, Lean
Quality/Defect ReductionSix Sigma, XP
Heavy DocumentationWaterfall, PRINCE2, RUP
Customer Collaboration FocusAgile, Scrum, XP
Statistical/Data-DrivenSix Sigma, CPM
Hybrid ApproachesRUP, Lean Six Sigma

Self-Check Questions

  1. Which two methodologies would you recommend for a project with well-defined requirements that cannot change mid-development, and why do they share this characteristic?

  2. A software team needs to maintain a production system while handling unpredictable support requests. Which methodology best fits this scenario, and what specific feature makes it appropriate?

  3. Compare and contrast Scrum and Kanban: what do they share as Agile-influenced approaches, and what fundamental difference makes each suited to different contexts?

  4. If an FRQ asks you to recommend a methodology for a startup building a new app with unclear requirements and heavy user involvement, which approach would you choose and what three features would you cite?

  5. How do Six Sigma and Lean differ in their primary focus, and in what situation might an organization implement both simultaneously?