BWU_BTA_22_508_RANJAN DAS(software_project_management).pptx

Software Management PPT

1. NAME – RANJAN DAS STUDENT CODE- BWU/BTA/22/508 SEC- I SEM- 6 th DEPT- B.TECH CSE(AIML) COURSE NAME- SOFTWARE PROJECT MANAGEMENT COURSE CODE- OEC-CSM601A TOPIC NAME- EFFORT ESTIMATION TECHNIQUES

2. INDEX Introduction to software project estimation. Objectives of accurate estimation. Factors influencing estimation accuracy. Estimation techniques overview. Expert judgement. Analogous and parametric estimation. Three- point estimation method. Conclusion.

3. Introduction to Software Project Estimation Definition:- Effort estimation is a crucial aspect of project management, playing a significant role in setting realistic timelines and allocating resources efficiently. It involves predicting the amount of time and effort required to complete a particular task or project. Why it is important:- Helps in planning & budgeting. Ensures resource allocation. Reduces project risks. Sets realistic deadlines. Challenges in estimation:- changing requirements Uncertainty in effort estimation. Developer productivity variations. Over-optimism leading to underestimation.

4. Objectives of Accurate Estimation Ensuring Project Feasibility – Confirms the project can be completed within constraints. Allocating Resources Effectively – Assigns budget, time, and workforce efficiently. Setting Realistic Timelines – Avoids delays by planning achievable deadlines. Minimizing Risks - – Identifies potential issues early to prevent failures . Improving Stakeholder Confidence – Builds trust with clients and investors through reliable estimates. Accurate Estimation refers to the precise prediction of project effort, cost, and time, ensuring minimal deviations from actual outcomes. It helps in better planning, resource allocation, and risk management, leading to successful project completion.

5. Factors Influencing Estimation Accuracy Project Size & Complexity – Larger and more intricate projects require more precise estimation due to increased risks and dependencies. Team Experience & Expertise – Skilled teams estimate better, while inexperienced teams may miscalculate effort and time. Technological Considerations – New or untested technologies can cause uncertainties, affecting accuracy. Requirement Clarity – Well-defined requirements lead to better estimates, while vague specifications increase uncertainty.

6. Estimation Techniques Overview Expert Judgment- – Relies on experienced professionals' insights for estimating effort, cost, and time. Analogous Estimation – Uses past similar projects as a reference to estimate the current project. Parametric Estimation – Applies mathematical models and historical data to predict effort and cost. Three-Point Estimation – Averages optimistic, pessimistic, and most likely estimates for better accuracy.

7. Expert Judgment Advantages of Expert Judgment:- Quick and efficient – Faster than data-driven estimation methods. Leverages experience – Uses insights from seasoned professionals . Useful for unique projects – Works well when no historical data is available. Flexible – Can adapt to changing project requirements. Combines multiple perspectives – Involves different experts for better accuracy. Potential Pitfalls of Expert Judgment:- Subjective and opinion-based – Estimates vary between individuals. Prone to bias- – Experts may be overly optimistic or conservative. Lack of consistency – Different experts may provide different estimates. Experience dependency – Accuracy depends on the expert’s knowledge . Not data-driven – Lacks statistical backing, making it harder to validate.

8. Analogous and Parametric Estimation

9. Three-Point Estimation Method The Three-Point Estimation Method is a technique used to improve accuracy in project estimation by considering three different scenarios: Optimistic Estimate (O) – Assumes the best-case scenario with minimal risks and delays. Most Likely Estimate (M) – Represents the most realistic scenario based on available information. Pessimistic Estimate (P) – Assumes the worst-case scenario, accounting for potential risks and uncertainties. This method reduces bias and provides a balanced estimate by averaging these three values using the formula: Expected Estimate (E) = (O + 4M + P) / 6 Example Calculation:- A software module is estimated as follows: Optimistic (O) = 10 days Most Likely (M) = 15 days Pessimistic (P) = 25 days Using the formula: E = (10 + 4(15) + 25) / 6 E = (10 + 60 + 25) / 6 = 15.83 days Thus, the estimated time for completion is approximately 15.8 days.

10. Conclusion Summary of Key Takeaways:- Accurate estimation is essential for project success, ensuring proper planning, resource allocation, and risk management. Various estimation techniques, such as Expert Judgment, Analogous, Parametric, and Three-Point Estimation, help improve accuracy. Factors like project complexity, team expertise, and technological considerations impact estimation reliability. Recommendations for Improving Estimation Accuracy:- Use a combination of estimation techniques for better precision. Rely on historical data and past project insights whenever possible. Involve experienced professionals and cross-functional teams in the estimation process. Continuously refine estimates as project requirements evolve. Factor in risks and uncertainties to avoid unrealistic expectations.

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