Quantitative Software Management
36
0
0
Full text
(2) Outline • What is productivity? • Process overview – Static productivity categories – Dynamic productivity categories. • Team size and productivity • Questions?. © Quantitative Software Management, Inc. #2.
(3) What is Productivity? • Traditional Productivity: Ratio between cost/effort and units of size (lines of code per staff month, hours per function point) • Advantages – Relatively easy to calculate and understand – Effective way to compare similar projects or environments. • Disadvantages – Does not account for impact of different domains/application types – Does not account for schedule, team size, or quality constraints. © Quantitative Software Management, Inc. #3.
(4) Productivity Categories (Static) • Determine medians for technical productivity and schedule productivity from project history • Assign projects to one of four categories – Better than median both measures – Worse than median both measures – Better technical / worse schedule – Worse technical / better schedule. • Analyze variables (project size, staffing, quality, etc.) to uncover relationships. © Quantitative Software Management, Inc. #4.
(5) Productivity Categories. FP \ Duration. EDS SC Development + Projects 220 200 180 160 140 120 100 80 60 40 20 0. # Projects Projects. Median FP / Duration. Median FP / Person Month 0. 10. 20. 30. 40. 50. 60. 70. 80. 90. FP/Person Month. © Quantitative Software Management, Inc. #5.
(6) Process Overview (Dynamic Productivity Categories) • Analysis based on validated software projects completed since 2001 • All projects had effort and duration from the beginning of analysis until release into production • Projects parsed into four productivity groups – Better than average for effort and schedule – Worse than average for effort and schedule – Better than average for effort; worse for schedule – Better than average for schedule; worse for effort. © Quantitative Software Management, Inc. #6.
(7) Dynamic Productivity Categories A na lyz e t hro ug h Im p le m e nt Dura t io n vs Siz e. 100. Projects worse than average for schedule Average 10. Calendar Months. Average. 1. Projects better than average for schedule. 1. 100. 10. 0 .1 1 ,0 0 0. Siz e (th o u s a n d s ). © Quantitative Software Management, Inc. #7.
(8) Process Overview • Projects divided into quartiles based on size • Within each quartile, the % of each productivity group was calculated for different team sizes • Observations made for each quartile about the best team sizes for schedule optimization, cost containment, and risk avoidance. © Quantitative Software Management, Inc. #8.
(9) Quartile 1 Up to 4004 ESLOC Productivity: Quartile 1 70 60. Percentage. 50 Above Average. 40. Effort Optimized Schedule Optimized. 30. Below Average. 20 10 0 <= 1. 1-2. 2-3. 3-4. >4. Team Size. Team size 3 or less provides best chance of balancing both schedule and cost/effort. © Quantitative Software Management, Inc. #9.
(10) Quartile 1 Effort Productivity Effort Productivity Distribution: Quartile 1 120 100. Percentage. 80 Above Average. 60. Below Average. 40 20 0 <= 1. 1-2. 2-3. 3-4. >4. Team Size. Small teams (2 or less) have highest probability of optimizing cost/effort. © Quantitative Software Management, Inc. #10.
(11) Quartile 1 Schedule Productivity Schedule Productivity Distribution: Quartile 1 70 60. Percentage. 50 40. Above Average Below Average. 30 20 10 0 <= 1. 1-2. 2-3. 3-4. >4. Team Size. Team size between 2 and 4 best for schedule optimized projects. © Quantitative Software Management, Inc. #11.
(12) Quartile 1 Observations • % projects better than average for schedule increases with team size up to a staff of 3-4 • Effort optimized projects decrease with team size: dramatically when team size > 2 • % projects better than average for effort & schedule increases up to 3 then rapidly decreases • % high cost long schedule projects increases with team size: dramatically when team > 4. © Quantitative Software Management, Inc. #12.
(13) Quartile 1 Recommendations • Staff should be 2 or less if cost/effort is primary project driver • Staff should be 2 – 4 if schedule is primary project driver • Staff of 1 – 3 for best balanced probability of success • Avoid team size > 4: (> 60% chance of being worse than average for schedule and cost/effort). Large teams are counterproductive. © Quantitative Software Management, Inc. #13.
(14) Quartile 2 4005 – 8702 ESLOC Productivity Distribution: Quartile 2 90 80 70. Percentage. 60 Above Average. 50. Effort Optimized Schedule Optimized. 40. Below Average. 30 20 10 0 <= 1. 1-2. 2-3. 3-4. 4-5. 5-6. 6-8. >8. Team Size. Team size of 1 - 3 provides best chance of balancing both schedule and cost/effort. © Quantitative Software Management, Inc. #14.
(15) Quartile 2 Effort Productivity Effort Productivity Distribution: Quartile 2 120 100. Percentage. 80. Above Average. 60. Below Average. 40 20 0 <= 1. 1-2. 2-3. 3-4. 4-5. 5-6. 6-8. >8. Team Size. Effort optimized projects decrease steadily with team size. Few projects with teams > 4 are cost/effort optimized. © Quantitative Software Management, Inc. #15.
(16) Quartile 2 Schedule Productivity Schedule Productivity Distribution: Quartile 2 100 90 80. Percentage. 70 60. Above Average. 50. Below Average. 40 30 20 10 0 <= 1. 1-2. 2-3. 3-4. 4-5. 5-6. 6-8. >8. Team Size. Many different team sizes work with these projects. Large teams can be used effectively where schedule is paramount. © Quantitative Software Management, Inc. #16.
(17) Quartile 2 Observations • Wide latitude in staffing for better than average projects (for schedule) • Effort optimization decreases with size: few projects with staff > 4 are effort optimized • Staff 1 – 3 has best balanced probability of success • Effort optimized and balanced probabilities very similar to patterns for smaller (Quartile 1) projects. © Quantitative Software Management, Inc. #17.
(18) Quartile 2 Recommendations • Team size <= 3 best for producing better than average project for effort/cost • Team size 1 – 3 provides best balanced probability for better than average project for effort & schedule • Large teams (> 8) can be used effectively to optimize schedule. © Quantitative Software Management, Inc. #18.
(19) Quartile 3 8705 – 20647 ESLOC Productivity Distribution: Quartile 3 70 60. Percentage. 50 Above Average. 40. Effort Optimized Schedule Optimized. 30. Below Average. 20 10 0 <= 1. 1-2. 2-3. 3-4. 4-5. 5-6. 6-8. >8. Team Size. Team size of 4 or less provides best chance of balancing both schedule and cost/effort. Sharp drop-off with larger teams. © Quantitative Software Management, Inc. #19.
(20) Quartile 3 Effort Productivity Effort Productivity Distribution: Quartile 3 120 100. Percentage. 80 Above Average. 60. Below Average. 40 20 0 <= 1. 1-2. 2-3. 3-4. 4-5. 5-6. 6-8. >8. Team Size. Teams with 4 or less have highest probability of optimizing cost/effort. © Quantitative Software Management, Inc. #20.
(21) Quartile 3 Schedule Productivity Schedule Productivity Distribution: Quartile 3 70 60. Percentage. 50 40. Above Average Below Average. 30 20 10 0 <= 1. 1-2. 2-3. 3-4. 4-5. 5-6. 6-8. >8. Team Size. Teams with 4 or less have highest probability of optimizing schedule. © Quantitative Software Management, Inc. #21.
(22) Quartile 3 Observations • % projects with better than average effort drops significantly with teams > 4 • % projects with better than average schedule peaks with teams 3 – 4 then drops • Teams =< 4 have good balanced probability of success • Teams > 4 have increased chance of being worse than average for cost/effort and schedule. © Quantitative Software Management, Inc. #22.
(23) Quartile 3 Recommendations • Team size 3 – 4 a good fit for these projects • Smaller teams (< 3) a good fit if schedule pressure permits • Avoid teams > 4. © Quantitative Software Management, Inc. #23.
(24) Quartile 4 > 20647 ESLOC Productivity Distribution: Quartile 4 80 70. Percentage. 60 50. Above Average. Effort Optimized. 40. Schedule Optimized. Below Average. 30 20 10 0 <= 2. 2-3. 3-4. 4-5. 5-6. 6-8. 8 - 10. 10 - 15. > 15. Team Size. Balanced probability of success fairly consistent up to a team size of 8. © Quantitative Software Management, Inc. #24.
(25) Quartile 4 Effort Productivity Effort Productivity Distribution: Quartile 4 120 100. Percentage. 80. Above Average. 60. Below Average. 40 20 0 <= 2. 2-3. 3-4. 4-5. 5-6. 6-8. 8 - 10. 10 - 15. > 15. Team Size. Teams larger than 8 have little chance of optimizing cost/effort. © Quantitative Software Management, Inc. #25.
(26) Quartile 4 Schedule Productivity Schedule Productivity Distribution 80 70. Percentage. 60 50. Above Average. 40. Below Average. 30 20 10 0 <= 2. 2-3. 3-4. 4-5. 5-6. 6-8. 8 - 10. 10 - 15. > 15. Team Size. Little correlation between team size and schedule productivity. © Quantitative Software Management, Inc. #26.
(27) Quartile 4 Observations • Good chance to optimize effort if team size 6 or fewer • % projects better than average for schedule & effort fairly constant up to staff of 8 • Projects better than average for schedule peaks at staff of 4 – 5 • Significant increase in projects worse than average for schedule & cost/effort with staff > 8. © Quantitative Software Management, Inc. #27.
(28) Quartile 4 Recommendations • Team size of 5 – 6 provides best balanced probability of success • Projects with staff > 8 have a high chance of not being efficient in either cost/effort or schedule: keep teams small!. © Quantitative Software Management, Inc. #28.
(29) Optimal Team Sizes Quartile 1 - 4004 ESLOC 4005 - 8702 ESLOC 8703 - 20647 ESLOC 20647+ ESLOC Large Projects > 70000 ESLOC. Schedule Cost/Effort Balanced Optimized Optimized Performance 2-4. <2. 1-3. 2-6. 1-3. 1-3. 2-4. 1-4. 2-4. 4-6. 1-5. 2-6. 10 - 20. 10 - 20. 10 - 20 © Quantitative Software Management, Inc. #29.
(30) Overall Observations • Strong relationship between team size and effort efficiency: Small teams are more productive • Relationship between team size and schedule is more tenuous: Large teams not always associated with faster time to market • Smaller teams far less likely to be worse than average for both effort and schedule. © Quantitative Software Management, Inc. #30.
(31) Questions?. © Quantitative Software Management, Inc. #31.
(32) Backup Slides. © Quantitative Software Management, Inc. #32.
(33) Large Project > 70000 ESLOC Productivity Distribution: Large Projects > 70k 70.0% 60.0%. Percentage. 50.0%. Above Average 40.0%. Effort Optimized. Schedule Optimized. 30.0%. Below Average 20.0% 10.0% 0.0% <=5. >5<=10. >10<=20. >20. Team Size. Team size between 10 & 20 stands out as best choice for optimizing both schedule & cost/effort. © Quantitative Software Management, Inc. #33.
(34) Very Large Project Observations • Staffing between 10 & 20 is a sweet spot for both schedule and cost/effort • Projects with staff > 20 either optimize schedule or are high cost, slow to deliver. © Quantitative Software Management, Inc. #34.
(35) Very Large Project Recommendations • Use a staff between 10 – 20 for optimal performance • Projects with a staff > 20 are high cost and have a > 50% chance of being slow to deliver, too. © Quantitative Software Management, Inc. #35.
(36) Analyze through Implement Effort vs Size. 2nd. Quartile. 10,000. 1st Quartile 1,000. 100. Staff Months of Effort. 10. 1. 0.1. 3rd Quartile. 4th Quartile 100. 10. 1. 0.01 1,000. Size (thousands). Business Systems. Avg. Line Style. 1 Sigma Line Style © Quantitative Software Management, Inc. #36.
(37)
Related documents
Each of the important parameters in Figure 1 is estimated, including: the static performance difference between Internet-only start-ups and branching start-ups (i.e., the
autoethnographic case, the paper proposes several lines of action that can be considered in dialogue by the Church and the indigenous Christian communities: a Church-wide
plumbing systems; increase and upgrade electrical capacity for safety and access to technology; repair and renovate existing academic classrooms; add permanent academic classrooms
Andino Investment Holding ( “ AIH ” ) is a group of peruvian companies, leading the Logistic Services and Port Services and providing Infrastructure.. Group Sales run over
The purpose of this study was to examine the influences of intentional mentoring, structured debriefing sessions, and demographics (educational preparation, age, previous
[r]
Rotonda Circle 4 Plex Rotonda West, Florida Silver Cove Condominiums Punta Gorda Isles, Florida Park Beach Condominiums Punta Gorda Isles, FL Simmons Duplex Port
