the effect of level of effort evt
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The effect of Level of Effort EVT
1
introduction
• LoE – This PMT is best used when it is impossible to determine progress for a task.
• This only works in circumstances where the forecast dates are the same as the Baseline dates, and if you will never need to do work from a previous month which was not done
2
Earned Value Techniques
• The CAM must allocate an appropriate Earned Value technique to the work
being performed
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50 / 50
0/100
Physical % complete
Incremental Milestone
Equivalent Units
Level of Effort
50% is earned as soon as work starts & remaining 50% when work is complete
Nothing is earned until the work is complete.
A percentage method of assessment
Weighted budget values assigned to milestones within a work package
Places a given value on each unit completed
EV is equal to BCWS at all times
SOME EXAMPLE METHODS DESCRIPTION
50/50 – xx/yy
When the work package begins in one period and completes in the next. No way of gaining credit between start and completion. Start and completion valued at 50% (or XX/YY). Completion should have criteria defined. Ideal when the plan consists of several short operations/activities.
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30 70
P1 P2 P3 P4 P5
50 50
Total Budget 100
0-100
No credit can be gained before completion.
Strictly limited to work packages starting and completing in the same reporting period.
5
P1 P2 P3 P4 P5
0 100
Incremental Milestones
When work packages exceed 2 reporting periods. 1 milestone a month is ideal. Each milestone should have its own value defined discrete from others. This means that the milestones are not sequential.
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P1 P2 P3 P4 P5
Budget 10
Budget 25
Budget 45
Budget 20
Total Budget 100
Units Complete
For physical counts of product or outputs. Each element is given a value for completion and then the units calculated. This is ideal for measuring items like drawings.
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P1 P2 P3 P4 P5
10 15 15 5 Budget Units 45Total £450
£10/unit
£100 £150 £150 £50
Percent Complete
For long work packages > 3 periods – no quantities to count and no definable milestones. Forecast % complete at end of each period and apply to BAC.
Success criteria should be identified to justify the Percentage claimed. For example 25% can be claimed only when the first draft of a document has been completed.
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Total Budget 1000
10%100
40%400
80%800
100%1000
Apportioned EffortWhen activities are performed in support of other direct activities eg
Assembly work and the associated material. The effort is estimated and planned as a % of the production effort. There must be a method of determining this %.
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50%
50%
Assembly work
Material Draw down
£10,000
£500,000
Level of Effort•Level of Effort
When tasks are are difficult to quantify with respect to accomplishment. Supportive activities – no definable outputs – budget scheduled over the period of performance. EV based on passage of time – EV always equal to planned accomplishment. – There can be no schedule variance. Beware, where effort is not linear, may end up with cost variance if more hours booked than planned.
•LoE – This PMT is best used when it is difficult to track the progress of an activity.
•This only works in circumstances where the forecast dates are the same as the Baseline dates.
•Remember – Earned Value should be credited in the same way it is planned.
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Correctly profiled
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Time nowBAC = 800
ACC BCWS = 400
ACC BCWP = 400
ACC ACWP = 400
Acc BCWS = 400Acc BCWP = 400Acc ACWP = 400Acc SV = 0Acc CV = 0
Incorrectly profiled
• There may be circumstances where it may seem appropriate to re-forecast a LOE package before it starts.
• For example an activity was baselined to start month 1 and then forecasted to start now in month 5. The following slides explain the effect of this on the EV data.
12
Incorrectly profiled Month 1
13
Time now
ACC BCWS = 100
ACC BCWP = 0
ACC ACWP = 0Acc BCWS = 100Acc BCWP = 0Acc ACWP = 0Acc SV = -100Acc CV = 0BAC = 800EAC = 800
Re-forecast start date
Incorrectly profiled Month 2
14
Time now
ACC BCWS = 200
ACC BCWP = 0
ACC ACWP = 0Acc BCWS = 200Acc BCWP = 0Acc ACWP = 0Acc SV = -200Acc CV = 0BAC = 800EAC = 800
Incorrectly profiled Month 3
15
Time now
ACC BCWS = 300
ACC BCWP = 0
ACC ACWP = 0Acc BCWS = 300Acc BCWP = 0Acc ACWP = 0Acc SV = -300Acc CV = 0BAC = 800EAC = 800
Incorrectly profiled Month 4
16
Time now
ACC BCWS = 400
ACC BCWP = 0
ACC ACWP = 0Acc BCWS = 400Acc BCWP = 0Acc ACWP = 0Acc SV = -400Acc CV = 0BAC = 800EAC = 800
Incorrectly profiled Month 5
17
Time now
ACC BCWS = 500
ACC BCWP = 500
ACC ACWP = 120Acc BCWS = 500Acc BCWP = 500Acc ACWP = 120Acc SV = 0Acc CV = 380BAC = 800EAC = 800
WHY!
• This is a strange effect of Earned Value and the PMT of LOE. Although the actual performance has not been worth 500, LOE means that the total performance will equal the value of the Baseline (BCWS) at time now.
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Incorrectly profiled Month 6
19
Time now
ACC BCWS = 600
ACC BCWP = 600
ACC ACWP = 240Acc BCWS = 600Acc BCWP = 600Acc ACWP = 240Acc SV = 0Acc CV = 360BAC = 800EAC = 800
Incorrectly profiled Month 7
20
Time now
ACC BCWS = 700
ACC BCWP = 700
ACC ACWP = 360Acc BCWS = 700Acc BCWP = 700Acc ACWP = 360Acc SV = 0Acc CV = 340BAC = 800EAC = 800
What does these mean• Looking at the data as it stands now it tells us:
– We have only one month of work left to do – We are on target to complete with no schedule variance– We have been very efficient we have done £700 for only £360 (positive CV of
£340)– We should under spend on completion and therefore the EAC is to high
• How real are these conclusions:
– Because we know the work was started late, we know more than 1 months work is needed.
– We also know the work is behind schedule, but not from the EV data– As the CAM we would know that only £100 of performance is being achieved
for a cost of £120 per month so we are not efficient– This efficiency in fact means that the EAC is too low.
21
Incorrectly profiled Month 8
22
Time now
ACC BCWS = 800
ACC BCWP = 800
ACC ACWP = 480Acc BCWS = 800Acc BCWP = 800Acc ACWP = 4800Acc SV = 0Acc CV = 320BAC = 800EAC = 800
Graph data Cum Performance
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100
200
300
400
500
600
700
800
900
1,000
2004JAN
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS100BCWP 0ACWP 0
Graph data Cum Performance
24
100
200
300
400
500
600
700
800
900
1,000
2004JAN FEB
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS 200100BCWP 00ACWP 00
Graph data Cum Performance
25
100
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MAR
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS 300200100BCWP 000ACWP 000
Graph data Cum Performance
26
100
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MARAPR
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS 400300200100BCWP 0000ACWP 0000
Graph data Cum Performance
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100
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MARAPR MAY
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS 500400300200100BCWP 5000000ACWP 1200000
Graph data Cum Performance
28
100
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MARAPR MAY JUN
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS 600500400300200100BCWP 6005000000ACWP 2401200000
Graph data Cum Performance
29
100
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MARAPR MAY JUN JUL
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS 700600500400300200100BCWP 7006005000000ACWP 3602401200000
Graph data Cum Performance
30
100
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MARAPR MAY JUN JUL AUG
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS 800700600500400300200100BCWP 8007006005000000ACWP 4803602401200000
Graph data Cum Performance
31
100
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MARAPR MAY JUN JUL AUGSEP
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS 800800700600500400300200100BCWP 8008007006005000000ACWP 6004803602401200000
Graph data Cum Performance
32
100
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MARAPR MAY JUN JUL AUGSEP OCT
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS 800800800700600500400300200100BCWP 8008008007006005000000ACWP 7206004803602401200000
Graph data Cum Performance
33
100
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MARAPR MAY JUN JUL AUGSEP OCT NOV
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS 800800800800700600500400300200100BCWP 8008008008007006005000000ACWP 8407206004803602401200000
Graph data Cum Performance
34
100
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MARAPR MAY JUN JUL AUGSEP OCT NOVDEC
BMT Sigma Example 1 OC Element: 1 Name: LOECum Element Performance
Time N
ow
Dollars in Thousands
BCWS 800800800800800700600500400300200100BCWP 8008008008008007006005000000ACWP 9608407206004803602401200000
Questions
• At what month could you determine that an over spend was going to happen, and by how much did you expect it to be.
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Cumulative variances
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-350
-250
-150
-50
50
150
250
350
2004JAN
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST 0.0SCHED-100.0
Cumulative variances
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-350
-250
-150
-50
50
150
250
350
2004JAN FEB
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST 0.00.0SCHED -200.0-100.0
Cumulative variances
38
-350
-250
-150
-50
50
150
250
350
2004JAN FEB MAR
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST 0.00.00.0SCHED -300.0-200.0-100.0
Cumulative variances
39
-350
-250
-150
-50
50
150
250
350
2004JAN FEB MARAPR
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST 0.00.00.00.0SCHED -400.0-300.0-200.0-100.0
Cumulative variances
40
-350
-250
-150
-50
50
150
250
350
2004JAN FEB MARAPR MAY
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST 380.00.00.00.00.0SCHED 0.0-400.0-300.0-200.0-100.0
Cumulative variances
41
-350
-250
-150
-50
50
150
250
350
2004JAN FEB MARAPR MAY JUN
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST 360.0380.00.00.00.00.0SCHED 0.00.0-400.0-300.0-200.0-100.0
Cumulative variances
42
-350
-250
-150
-50
50
150
250
350
2004JAN FEB MARAPR MAY JUN JUL
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST 340.0360.0380.00.00.00.00.0SCHED 0.00.00.0-400.0-300.0-200.0-100.0
Cumulative variances
43
-350
-250
-150
-50
50
150
250
350
2004JAN FEB MARAPR MAY JUN JUL AUG
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST 320.0340.0360.0380.00.00.00.00.0SCHED 0.00.00.00.0-400.0-300.0-200.0-100.0
Cumulative variances
44
-350
-250
-150
-50
50
150
250
350
2004JAN FEB MARAPR MAY JUN JUL AUGSEP
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST 200.0320.0340.0360.0380.00.00.00.00.0SCHED 0.00.00.00.00.0-400.0-300.0-200.0-100.0
Cumulative variances
45
-350
-250
-150
-50
50
150
250
350
2004JAN FEB MARAPR MAY JUN JUL AUGSEP OCT
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST 80.0200.0320.0340.0360.0380.00.00.00.00.0SCHED 0.00.00.00.00.00.0-400.0-300.0-200.0-100.0
Cumulative variances
46
-350
-250
-150
-50
50
150
250
350
2004JAN FEB MARAPR MAY JUN JUL AUGSEP OCT NOV
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST -40.080.0200.0320.0340.0360.0380.00.00.00.00.0SCHED 0.00.00.00.00.00.00.0-400.0-300.0-200.0-100.0
Cumulative variances
47
-350
-250
-150
-50
50
150
250
350
2004JAN FEB MARAPR MAY JUN JUL AUGSEP OCT NOVDEC
BMT Sigma Example 1 OC Element: 1 Name: LOECumulative Variance
Dollars in Thousands
COST -160.0-40.080.0200.0320.0340.0360.0380.00.00.00.00.0SCHED 0.00.00.00.00.00.00.00.0-400.0-300.0-200.0-100.0
Other Effects• Where you are in a situation where more performance is being claimed
than the spend incurred a positive Cost Performance Index (CPI) is created, meaning you are efficient than expected. Where the performance is due to the incorrect LOE re-forecast, an artificial variance has been created. Some Independent Estimates at completion (IEAC) formulas use the CPI, and if this is artificial then the IEAC will not be correct.
48
IEAC based on Cur/Cum CPI
49
200
300
400
500
600
700
800
900
1,000
2004JAN
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum800IEAC_Curr800BAC 800
IEAC based on Cur/Cum CPI
50
200
300
400
500
600
700
800
900
1,000
2004JAN FEB
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum 800800IEAC_Curr 800800BAC 800800
IEAC based on Cur/Cum CPI
51
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MAR
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum 800800800IEAC_Curr 800800800BAC 800800800
IEAC based on Cur/Cum CPI
52
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MAR APR
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum 800800800800IEAC_Curr 800800800800BAC 800800800800
IEAC based on Cur/Cum CPI
53
BCWPCPI= ACWP
BCWP = 500ACWP = 120
CPI = 4.2
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MAR APR MAY
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum 192800800800800IEAC_Curr 192800800800800BAC 800800800800800
IEAC based on Cur/Cum CPI
54
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MAR APR MAY JUN
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum 320192800800800800IEAC_Curr 480192800800800800BAC 800800800800800800
IEAC based on Cur/Cum CPI
55
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MAR APR MAY JUN JUL
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum 411320192800800800800IEAC_Curr 480480192800800800800BAC 800800800800800800800
IEAC based on Cur/Cum CPI
56
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MAR APR MAY JUN JUL AUG
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum 480411320192800800800800IEAC_Curr 480480480192800800800800BAC 800800800800800800800800
IEAC based on Cur/Cum CPI
57
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MAR APR MAY JUN JUL AUG SEP
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum 600480411320192800800800800IEAC_Curr 800480480480192800800800800BAC 800800800800800800800800800
IEAC based on Cur/Cum CPI
58
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MAR APR MAY JUN JUL AUG SEP OCT
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum 720600480411320192800800800800IEAC_Curr 800800480480480192800800800800BAC 800800800800800800800800800800
IEAC based on Cur/Cum CPI
59
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum 840720600480411320192800800800800IEAC_Curr 840800800480480480192800800800800BAC 800800800800800800800800800800800
IEAC based on Cur/Cum CPI
60
200
300
400
500
600
700
800
900
1,000
2004JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
BMT Sigma Example 1 OC Element: 1 Name: LOEIEAC Based on CPI
Dollars in Thousands
IEAC_Cum 960840720600480411320192800800800800IEAC_Curr 960840800800480480480192800800800800BAC 800800800800800800800800800800800800
Questions?
• Presented by:– Russell Berkeley– Tel: 07515 685458
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