Project Control is one of the most difficult tasks of a project manager. To assess whether a project is still on track is very difficult because the team members often report overconfident status reports. Using functional size and specialized tooling, like QSM Control or SEER PPMC, helps the project manager to get a real good understanding of the status of the project. These tools produce accurate forecasts and offer the possibility to do what-if analysis in order to select the best way to get a project back on track. In this presentation, it is examined which method would produce the best results, NESMA or IFPUG FPA or COSMIC FPA.

1. Project control based on functional size
Which method to use?
Harold van Heeringen
UKSMA conference
(London, November 8, 2012)

2. Harold van Heeringen
• Short intro:
− Sogeti Nederland BV senior consultant software metrics
− ISBSG president
− NESMA board member
− NESMA working group chair COSMIC
− NESMA working group chair Benchmarking
− COSMIC IAC member
Harold van Heeringen
Sizing, Estimating & Control
harold.van.heeringen@sogeti.nl
@haroldveendam
@Sogeti_SEC
2

3. Agenda
• Parametric project control
• Product size ready
• Differences IFPUG vs. COSMIC relevant for
Project control
• Experiment: Project control with two methods
• Conclusions
3

4. Project Management
• Project Estimation
− Parametric estimates based on (COSMIC) FP
− Effort hours, duration, staff, defects
− Galorath SEER-SEM / QSM SLIM Estimate / other tools
 Productivity (PDR = hours/FP) that is expected
• Project Planning
− Transform the estimate into the plan
• Project Control
− Track the status based on FP FTE Staff
Staff & Effort Variance
8
Cum Effort Life Cycle
3.500
3.000
6
2.500
− Do we meet our expected PDR?
2.000
MHR
ppl
4
1.500
1.000
2
500
0 0
2 4 6 8 10 12 14 16 2 4 6 8 10 12 14 16
29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09 29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09
− Forecasting based on actuals
'10 '10
Date 14-8-2010 (11,57 weeks)
Plan Actual Diff
Avg Staff Life Cycle (ppl) 5,2 5,3 0,1
Cum Effort Life Cy cle (MHR) 1.787,8 1.812,0 24,2
PI 20,8 20,6 -0,2
MBI 5,3 5,3 0,0
Current Plan Actuals Green Control Bound Yellow Control Bound Project: Project XYZ
4

5. Project Control
• How do Project managers manage their software
realization project?
− Administration of effort hours (weekly)
− Compare effort hours against planned hours (weekly)
• Project status
− If more hours than planned have been spent, we must be
ahead of schedule, right?
− If less hours than planned have been spent, the project is
easier than expected, right?
• To measure hours is easy, but what about
'product delivered'?
5

6. Inaccurate project status
• Most used:
− How many hours do you need to finish ‘activity X’?
− Expert estimate/judgment is used to assess the status of
the ‘work done’
− PM collects the status of all people and aggregates this info
into a status report
• Problem:
− experts are usually optimistic, underestimating the work
that still needs to be done
◦ Documenting, bug fixing, 2nd round of testing, etcetera
• Result:
− Inaccurate status until very late in the project !
6

7. Parametric project control
• Control the project, using functional size for the
'product ready'
• Project status:
− Effort hours spent vs. effort hours planned
− Actual functional size ready vs. planned functional size
ready
− Forecasting based on the actuals
• Galorath SEER-SEM
− Parametric Project Monitoring & Control tool (PPMC)
• QSM SLIM Control
− Part of the QSM SLIM toolsuite
7

8. How the tools work
1. Put in the baseline plan
− Start and end date
− Milestone dates
− Effort hours planned
− Product size to be delivered in (C) FP
1. Record actuals (every week / 2 weeks)
− Effort hours
− Dates
− Defects
− Product size ready in (C) FP
1. Forecast project results
2. Calculate corrective actions 8

9. Project control
• Putting in the baseline plan is easy (project plan
of the PL)
• Collecting actual hours, milestone dates and
defects is also fairly easy
• Measuring the ‘product size ready’ is more
complicated
− When is an EI ready? When is an EIF ready?
− How can we objectively assess a function point being ready?
• Function point ready – after the programmer
reports it ready for systems testing
• Measuring the correct ‘product size ready’ is
crucial for Project Control
9

10. Product size ready
• Multiple methods to measure ‘product size
ready’
• Technical: SLOCs
− Easy to measure actuals, but hard to predict/estimate total
− Baseline plan slocs is inaccurate, but actuals are accurate
• Functional: (COSMIC) Function Points
− Harder to measure, based on quality of documentation
− Baseline plan and actuals can both be accurately measured
• Which functional size measurement method is
most accurate?
10

11. NESMA/IFPUG vs. COSMIC
Characteristic NESMA/IFPUG FPA COSMIC
Applicable on domain Business software Business / Real-time /
Infrastructure software
Data model required? Required Not required (but very
handy)
Measurement of Not possible Possible
separate components
Size limit per function Yes Size is not limited
Benchmarking data ISBSG (aug 12), n= 4316 ISBSG (aug 12),
n=446
Measurement of No No, but local extension
processing functionality is possible
Early sizing Based on data model Based on process
model
11

12. Functional complexity
• IFPUG/NESMA does not really measure
differences in functional complexity
− EI: 3,4 or 6 FP (never less than 3, never more than 6)
− EO: 4,5 or 7 FP (never less than 4, never more than 7)
• But: in real life functions can differ from very
low complexity
− e.g. drop down list ‘Client’ (EO: 1 FTR, 2 DET, 4 FP)
…to very complex
− e.g. to make a new insurance contract perhaps clicking
through 5 screens: (EI: 8 FTR, 121 DET, 6 FP)
• Difference in FP does not reflect difference in
effort needed.
12

13. COSMIC and Project control
• Theoretically, COSMIC should be the better
method to use for Project Control
• The data model does not explicitly get points.
− In project control, it’s difficult to assess status regarding the
realization of the data model (When is an EIF ready?).
• The functional processes are not restricted in
size
− E.g. drop down list Client: 3 CFP (EO: 4 FP)
− Make a new insurance contract: 38 CFP (EI: 6 FP)
• Difference in size reflects the difference in effort
needed more realistically 13

14. Some examples
User Function IFPUG IFPUG COSMIC COSMIC
type size type size
Functional 8 CFP
Add customer EI 3 FP Process
Change Functional 7 CFP
customer EI 4 FP Process
Delete Functional 4 CFP
customer EI 3 FP Process
Show revenue Functional 12 CFP
per customer Process
and region EO 7 FP
Customer ILF 7 FP - 0
14

15. Case: Government agency
• Project name: XYZ
• Programming language: Java
• Development method: waterfall
• Functional size:
− 371 FP (IFPUG)
− 494 CFP (COSMIC)
• Effort hours planned: 2.505 hours
• Planned start date: 26-05-2010
• Planned end date: 12-09-2010
CONST. & IFPUG COSMIC Hours
TEST FP FP planned Start date End date
Project XYZ 371 494 2505 26-5-2010 12-09-2010
15

16. The IFPUG plan
SEI Core Metrics
Schedule Size
500
400
300
Phases
FP
Construct & Test
200
100
0
2 4 6 8 10 12 14 16 2 4 6 8 10 12 14 16
29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09 29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09
'10 '10
Cum Effort Life Cycle
3.500
3.000
2.500
2.000
MHR
1.500
1.000
500
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
29-05 05-06 12-06 19-06 26-06 03-07 10-07 17-07 24-07 31-07 07-08 14-08 21-08 28-08 04-09 11-09 18-09
'10
Current Plan Actuals Current Forecast Green Control Bound Yellow Control Bound Project: Project XYZ
16

17. The COSMIC plan
SEI Core Metrics
Schedule Size
700
600
500
400
Phases
FP
Construct & Test 300
200
100
0
2 4 6 8 10 12 14 16 2 4 6 8 10 12 14 16
29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09 29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09
'10 '10
Cum Effort Life Cycle
3.500
3.000
2.500
2.000
MHR
1.500
1.000
500
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
29-05 05-06 12-06 19-06 26-06 03-07 10-07 17-07 24-07 31-07 07-08 14-08 21-08 28-08 04-09 11-09 18-09
'10
Current Plan Actuals Current Forecast Green Control Bound Yellow Control Bound Project: Project XYZ
17

18. After 4 weeks: forecast IFPUG
• First Actuals
Metric Plan Actual Difference
Hours spent 238 294 +56
IFPUG FP ready 99 80 -19
COSMIC FP ready 132 130 -2
SEI Core Metrics
Schedule Size
500
400
300
Phases
FP
Construct &...
200
100
0
2 4 6 8 10 12 14 16 18 2 4 6 8 10 12 14 16 18
29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09 02-10 29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09 02-10
'10 '10
Cum Effort Life Cycle
3.500
3.000
2.500
2.000
MHR
1.500
1.000
500
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
29-05 05-06 12-06 19-06 26-06 03-07 10-07 17-07 24-07 31-07 07-08 14-08 21-08 28-08 04-09 11-09 18-09 25-09 02-10
'10
18
Current Plan Actuals Current Forecast Green Control Bound Yellow Control Bound Project: Project XYZ

19. After 4 weeks: forecast COSMIC
• First Actuals
Metric Plan Actual Difference
Hours spent 238 294 +56
IFPUG FP ready 99 80 -19
COSMIC FP ready 132 130 -2
SEI Core Metrics
Schedule Size
700
600
500
400
Phases
FP
Construct & Test 300
200
100
0
2 4 6 8 10 12 14 16 2 4 6 8 10 12 14 16
29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09 29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09
'10 '10
Cum Effort Life Cycle
3.500
3.000
2.500
2.000
MHR
1.500
1.000
500
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
29-05 05-06 12-06 19-06 26-06 03-07 10-07 17-07 24-07 31-07 07-08 14-08 21-08 28-08 04-09 11-09 18-09
'10
19
Current Plan Actuals Current Forecast Green Control Bound Yellow Control Bound Project: Project XYZ

20. Forecast after 4 weeks
Metric Plan Forecast Overrun/underrun
Based on IFPUG FP
Hours 2.505 2.933 +428 hours (+17%)
Schedule 12-09-2010 26-09-2010 2 weeks
Based on COSMIC FP
Hours 2.505 2.601 +96 hours (+4%)
Schedule 12-09-2010 14-09-2010 2 days
• Project manager thinks everything is OK
• Team members agree
20

21. Actuals after week 8: Forecast IFPUG
Metric Plan Actual Difference
Hours spent 941 982 +41
FP ready 279 252 -27
COSMIC FP ready 371 366 -5
SEI Core Metrics
Schedule Size
500
400
300
Phases
FP
Construct & T...
200
100
0
2 4 6 8 10 12 14 16 2 4 6 8 10 12 14 16
29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09 29-05 12-06 26-06 10-07 24-07 07-08 21-08 04-09 18-09
'10 '10
Cum Effort Life Cycle
3.500
3.000
2.500
2.000
MHR
1.500
1.000
500
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
29-05 05-06 12-06 19-06 26-06 03-07 10-07 17-07 24-07 31-07 07-08 14-08 21-08 28-08 04-09 11-09 18-09 25-09
'10
21
Current Plan Actuals Current Forecast Green Control Bound Yellow Control Bound Project: Project XYZ

22. Forecast after 8 weeks
• PM still thinks everything is on track, but is
getting a little nervous
• Team members still agree
Metric Plan Forecast Overrun/underrun
Based on IFPUG FP
Hours 2.505 2.991 +486 hours (+19%)
Schedule 12-09-2010 24-09-2010 12 days
Based on COSMIC FP
Hours 2.505 2.690 +185 hours (+7%)
Schedule 12-09-2010 15-09-2010 3 days
22

23. After 12 weeks
Metric Plan Actual Difference
Hours spent 1.788 1.812 +24
FP ready 357 348 -9
COSMIC FP ready 471 470 -1
Metric Plan Forecast Overrun/under run
Based on IFPUG FP
Hours 2.505 3.009 +504 hours (+20%)
Schedule 12-09-2010 25-09-2010 13 days
Based on COSMIC FP
Hours 2.505 2.730 +225 hours (+9 %)
Schedule 12-09-2010 16-09-2010 4 days
23

24. Final results
• Small overrun in time and effort
Metric Plan Actual Difference
Hours spent 2.505 2.586 +81
Project end date 12 -09-2010 16-09-2010 +4 days
FP ready 371 371 0
COSMIC FP ready 494 494 0
24

25. The forecasts analyzed
• IFPUG forecasts show considerable overruns
until late in the project
• COSMIC forecasts more conservative
• COSMIC forecasts more in line with the feeling of
the team and the PM
Forecast IFPUG FP COSMIC FP
Hours overrun Schedule overrun Hours overrun Schedule overrun
4 weeks +428 + 2 weeks +96 +2 days
8 weeks +486 +12 days +185 +3 days
12 weeks +504 +13 days +225 + 4 days
Final +81 +4 days +81 +4 days
25

26. Conclusions
• In theory, COSMIC should be the better method
to use in parametric project control
− No size limit per function: more accurate product size ready
− No explicit points for the data model: Easier to measure
‘project size ready’
• This experiment confirms this theory
− COSMIC forecasts closer to reality than IFPUG forecasts
• More experiments are needed to support this
conclusion
26

27. Sogeti Sizing, Estimating & Control
Thanks for your attention !
Harold van Heeringen
Sizing, Estimating & Control
harold.van.heeringen@sogeti.nl
@haroldveendam
@Sogeti_SEC
Sogeti Sizing, Estimating & Control
NESMA – board member
NESMA – chair working group COSMIC
NESMA – chair working group Benchmarking
NESMA – working group Sizing Packages
NESMA – working group Estimation maturity
COSMIC – International Advisory Counsil
COSMIC – Benchmarking Committee
ISBSG – President
27