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Generalized Analysis of Value Behavior over Time as a Project Performance Predictor

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  • Strategic Program Management LLC

Abstract and Figures

As projects have grown more complex our performance analysis frameworks have remained largely unchanged even as newer more powerful tools have become available to manage and manipulate large volumes of data. Newer analytical tools provide deeper insights into existing data sets especially from a statistical point of view but we continue to use traditional project metrics to assess project performance on both a retrospective as well as prospective basis. Whether our measure of project achievement is cost, schedule, physical % complete, risk or manhours we look at a relatively common set of “achievement” metrics that include absolute values (datum); changes in those values (progress) and their rate of change (progress rate). In limited instances we consider changes in the rate of progress (ramp rate) but do not more broadly analyze this throughout the project. Higher order performance measures that look at disruption and overall efficiency of delivery are not typically considered.
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PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 1 of 17
Generalized Analysis of Value Behavior over Time
as a
Project Performance Predictor
By Bob Prieto
As projects have grown more complex our performance analysis frameworks have
remained largely unchanged even as newer more powerful tools have become available
to manage and manipulate large volumes of data. Newer analytical tools provide deeper
insights into existing data sets especially from a statistical point of view but we continue
to use traditional project metrics to assess project performance on both a retrospective
as well as prospective basis.
Whether our measure of project achievement is cost, schedule, physical % complete,
risk or manhours we look at a relatively common set of “achievement” metrics that
include absolute values (datum); changes in those values (progress) and their rate of
change (progress rate). In limited instances we consider changes in the rate of progress
(ramp rate) but do not more broadly analyze this throughout the project.
Higher order performance measures that look at disruption and overall efficiency of
delivery are not typically considered.
The analog for each of these achievement metrics can be seen in the following table.
Derivative Spatial Achievement
Point x Datum
0 Distance dx Progress ∆ datum (dd)
1 Velocity dx/dt Progress Rate ∆ progress (dp/dt)
2 Acceleration dv/dt Ramp Rate ∆ progress rate (dpr/dt)
3 Jerk da/dt Disruption ∆ ramp rate (drr/dt)
4 Snap dj/dt Efficiency ∆ disruption (ddis/dt)
Generalized Analysis of Value Behavior over Time
In this paper we will consider some potential index type metrics to help evaluate the
level of potential “disruption” that exist in a project plan or is subsequently realized. In
addition we will look at how the various “disruptions” combine to impact the overall
efficiency of the project. These indices correspond to third and fourth order derivatives,
jerk and snap, in a spatial context and are subjects of one or more patents pending.
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 2 of 17
Conceptual Framework
Complex construction projects are susceptible to potential disruption from many
different sources including site based safety events, late or incomplete information,
poorly conceived or executed work processes, out of sequence work, unrecognized
interferences and a host of external factors which lie outside a project team’s control.
Throwing up one’s hands in dismay is not an acceptable management strategy and thus
we must ensure that we have the best possible plan and approach when we start and
gain the insights necessary to control or limit many of these potential sources of project
disruption.
The conceptual framework envisioned, seeks to provide a tool to assess the potential
disruption or execution inefficiencies present in a project plan, allowing project teams to
identify particularly troubling time frames and take steps to improve activity transitions,
startup and completion in particular.
Within an ongoing project context the conceptual framework should provide insight into
disruption durations and severity, and while not addressed here, provide insights in
closely coupled, multi-project programs.
Comparable insights are not well developed today.
The conceptual framework for construction of these indices falls within the realm of
optimization theory. Optimization theory is the more modern term for operations
research. Optimization theory includes the calculus of variations, control theory, convex
optimization theory, decision theory, game theory, linear programming, Markov chains,
network analysis, optimization theory, queuing systems, etc. (1)
In the simplest terms it is about making a system or project as effective or functional as
possible.
Let’s look at one example where the use of third and fourth order derivatives comes into
play. Consider the skilled movement of a hand. It is smooth and graceful and can be
described as minimizing jerk, a third order derivative in a spatial context. This
minimization of jerk allows us to predict the qualitative and quantitative features of the
hand movement. (2)
In general, when considering higher order derivatives, relative values are better
portrayed by utilizing the minimum squared derivative (MSD) principles. This implies
that the higher order derivatives will have low absolute values. In the example of skilled
hand movement above the squared jerk actually provides a better measure of relative
smoothness of the trajectory of movement.
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 3 of 17
While one may consider MSD for any order derivative, it has been found that 3rd and 4th
order MSD principles performed better than other orders. These correspond to minimum
jerk and minimum snap (snap is the time derivative of jerk).
Consideration of Representative Achievement Curves
The development of project plans results in a planned set of achievement curves. These
may correspond to manhours worked in a given period; installation rates; expenditure
rates or earned value. Inherent in these achievement curves are assumptions around
the efficiency with which certain activities are carried out and importantly the efficiency
with which we can transition these activities (start:stop; ramp-up:ramp-down). Inefficient
transitions lead to disruptions that have broader ripple effects and impact overall project
outcome.
In order to evaluate the impacts of different achievement plans, three typical
achievement models were constructed. These corresponded to:
Straight line achievement
S-curve achievement
Sculpted or user defined achievement
Each resulted in 1000 units of achievement over 100 time periods. The achievement
parameter and time period were kept dimensionless but it is important that time periods
do not become so long as to lose a view on the variations in progress that would occur
in such a long time period.
The following figures illustrate both the periodic achievement as well as the cumulative
achievement under each model.
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 4 of 17
In the periodic value we can see the disruptive start and stop nature of achievement in
the sculpted model while the straight line shows a sudden start and stop with no
variation in periodic progress throughout. The S-curve model provides a gradual ramp
up (versus abrupt full out start) and gradual ramp down (versus sudden abrupt stop).
The cumulative value figure illustrates the classical S-curve shape as well as straight
line and highly sculpted cumulative achievements. An infinite variety of S-curves are
possible with the shapes being flatter or steeper; more or less developed earlier or later
in the time frame; or skewed sooner or later in the time range. The particular example
illustrated includes no skew.
Construction and Selection of Higher Order Indices
Various indices may be calculated on both an instantaneous and cumulative basis for
each achievement model. Specifically, the progress in each period was tabulated and
corresponds to the Periodic Value Figure above. Based on these a time series of
values corresponding to the “instantaneous” change in the rate of progress (first
derivative) were tabulated and a ramp up rate (the rate at which the rate of progress is
changing or second derivative) was comparably tabulated.
Disruption (third derivative or jerk) and efficiency (fourth derivative or snap) were
similarly tabulated.
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 5 of 17
For purposes of constructing meaningful indices the effects of disruption were
considered on a periodic basis utilizing both absolute values as well as MSD values
(squared jerk). A similar approach was utilized for efficiency (fourth derivative or snap)
with both absolute values as well as MSD values (squared snap) considered. Lower
values represented better performance, reflecting less variance from the trend.
Tables 1, 2, and 3 included at the end present the results of these calculations.
Attention should be paid to start up, ramp-up, and ramp-down transitions in particular.
The S-curve time period 1 value includes all prior activities reflecting the “infinite” tails
associated with such curves.
In evaluating different potential approaches a singular set of values related to disruption
and efficiency were deemed to be more useful than a time series. The selected values
corresponded to:
Cumulative disruption (sum of the absolute disruption values for all time periods)
Cumulative efficiency (sum of the absolute efficiency values for all time periods)
MSD Disruption Index (sum of the squares of the periodic disruption values for all
time periods)
MSD Efficiency Index (sum of the squares of the periodic efficiency values for all
time periods)
The calculated values for the three selected models are shown in the following table.
Cumulative
Disruption
Index
Cumulative
Efficiency
Index
MSD
Disruption
Index
MSD
Efficiency
Index
Straight 40 80 600 2000
S Curve 19 37 108 380
Sculpted 780 1360 19950 55300
Lower is Better
Third and Fourth Order Measures of Project Plan and Performance
Conclusion
Better understanding, measuring and quantifying the relative effects of disruption in
today’s more complex project environments is increasingly important. Third and fourth
order derivatives represent a tool for contrasting alternative execution models as well as
assessing the impacts of actual performance against plan.
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 6 of 17
Time series modeling of these higher order derivatives illustrate how the effects of
disruption are felt over an extended time frame and offer the potential to influence
workface planning as well as broader project planning.
Through use over time, determination of acceptable disruption levels will be defined for
different project execution strategies, allowing us to establish performance linked
ranges for each of the recommended indices. Sensitivity to selected time period (hourly,
daily, weekly, monthly) requires further research. Similarly the significance of start-up
“disruption” and prior period values incorporated into the first time period of the S-curve
model must be judged.
References
(1) Weisstein, Eric W. "Optimization Theory." From MathWorld--A Wolfram Web Resource.
http://mathworld.wolfram.com/OptimizationTheory.html
(2) Hogan N (1984a) Adaptive control of mechanical impedance by coactivation of
antagonist muscles. IEEE Trans.Automatic.Control AC-29: 681-690
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 7 of 17
Table 1 - S Curve
Time Progress Progress
Rate Ramp
Rate Disruption Efficiency
Absolute
Periodic
Disruption
Cumulative
Disruption
Index
Absolute
Periodic
Efficiency
Cumulative
Efficiency
Index MSD
Disruption MSD
Efficiency
0 0 0 0 0
1 2.48 2.48 2.48 2.48 -2.48 2.48 2.48 2.48 2.48 6.14 6.14
2 0.32 -2.16 -4.64 -7.12 9.60 7.12 9.60 9.60 12.08 50.66 92.09
3 0.36 0.04 2.20 6.84 -13.96 6.84 16.44 13.96 26.03 46.79 194.82
4 0.41 0.05 0.01 -2.20 9.04 2.20 18.63 9.04 35.07 4.82 81.65
5 0.46 0.05 0.01 0.00 -2.20 0.00 18.63 2.20 37.27 0.00 4.82
6 0.52 0.06 0.01 0.00 0.00 0.00 18.63 0.00 37.27 0.00 0.00
7 0.58 0.07 0.01 0.00 0.00 0.00 18.63 0.00 37.27 0.00 0.00
8 0.66 0.07 0.01 0.00 0.00 0.00 18.64 0.00 37.27 0.00 0.00
9 0.74 0.08 0.01 0.00 0.00 0.00 18.64 0.00 37.27 0.00 0.00
10 0.83 0.09 0.01 0.00 0.00 0.00 18.64 0.00 37.27 0.00 0.00
11 0.94 0.11 0.01 0.00 0.00 0.00 18.64 0.00 37.27 0.00 0.00
12 1.06 0.12 0.01 0.00 0.00 0.00 18.64 0.00 37.27 0.00 0.00
13 1.19 0.13 0.01 0.00 0.00 0.00 18.64 0.00 37.27 0.00 0.00
14 1.34 0.15 0.02 0.00 0.00 0.00 18.64 0.00 37.27 0.00 0.00
15 1.51 0.17 0.02 0.00 0.00 0.00 18.65 0.00 37.27 0.00 0.00
16 1.70 0.19 0.02 0.00 0.00 0.00 18.65 0.00 37.27 0.00 0.00
17 1.91 0.21 0.02 0.00 0.00 0.00 18.65 0.00 37.27 0.00 0.00
18 2.15 0.24 0.03 0.00 0.00 0.00 18.65 0.00 37.27 0.00 0.00
19 2.41 0.27 0.03 0.00 0.00 0.00 18.66 0.00 37.27 0.00 0.00
20 2.71 0.30 0.03 0.00 0.00 0.00 18.66 0.00 37.27 0.00 0.00
21 3.04 0.33 0.03 0.00 0.00 0.00 18.66 0.00 37.27 0.00 0.00
22 3.41 0.37 0.04 0.00 0.00 0.00 18.67 0.00 37.27 0.00 0.00
23 3.82 0.41 0.04 0.00 0.00 0.00 18.67 0.00 37.27 0.00 0.00
24 4.28 0.46 0.05 0.00 0.00 0.00 18.67 0.00 37.27 0.00 0.00
25 4.78 0.51 0.05 0.00 0.00 0.00 18.68 0.00 37.27 0.00 0.00
26 5.34 0.56 0.05 0.00 0.00 0.00 18.68 0.00 37.27 0.00 0.00
27 5.96 0.62 0.06 0.00 0.00 0.00 18.68 0.00 37.27 0.00 0.00
28 6.64 0.68 0.06 0.00 0.00 0.00 18.69 0.00 37.27 0.00 0.00
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 8 of 17
29 7.38 0.74 0.07 0.00 0.00 0.00 18.69 0.00 37.27 0.00 0.00
30 8.20 0.81 0.07 0.00 0.00 0.00 18.70 0.00 37.27 0.00 0.00
31 9.08 0.89 0.07 0.00 0.00 0.00 18.70 0.00 37.27 0.00 0.00
32 10.04 0.96 0.07 0.00 0.00 0.00 18.70 0.00 37.27 0.00 0.00
33 11.07 1.03 0.07 0.00 0.00 0.00 18.70 0.00 37.27 0.00 0.00
34 12.18 1.11 0.07 0.00 0.00 0.00 18.70 0.00 37.27 0.00 0.00
35 13.36 1.18 0.07 0.00 0.00 0.00 18.70 0.00 37.28 0.00 0.00
36 14.60 1.24 0.07 0.00 0.00 0.00 18.71 0.00 37.28 0.00 0.00
37 15.91 1.30 0.06 -0.01 0.00 0.01 18.72 0.00 37.28 0.00 0.00
38 17.26 1.35 0.05 -0.01 0.00 0.01 18.73 0.00 37.28 0.00 0.00
39 18.65 1.39 0.04 -0.01 0.00 0.01 18.74 0.00 37.29 0.00 0.00
40 20.06 1.41 0.02 -0.02 0.00 0.02 18.75 0.00 37.29 0.00 0.00
41 21.47 1.41 0.00 -0.02 0.00 0.02 18.77 0.00 37.29 0.00 0.00
42 22.87 1.39 -0.02 -0.02 0.00 0.02 18.79 0.00 37.29 0.00 0.00
43 24.22 1.35 -0.04 -0.02 0.00 0.02 18.82 0.00 37.30 0.00 0.00
44 25.50 1.28 -0.07 -0.03 0.00 0.03 18.85 0.00 37.30 0.00 0.00
45 26.69 1.18 -0.10 -0.03 0.00 0.03 18.87 0.00 37.30 0.00 0.00
46 27.74 1.06 -0.12 -0.03 0.00 0.03 18.90 0.00 37.30 0.00 0.00
47 28.65 0.91 -0.15 -0.03 0.00 0.03 18.93 0.00 37.30 0.00 0.00
48 29.39 0.73 -0.17 -0.02 0.00 0.02 18.95 0.00 37.30 0.00 0.00
49 29.93 0.54 -0.19 -0.02 0.00 0.02 18.97 0.00 37.31 0.00 0.00
50 30.26 0.33 -0.21 -0.02 0.00 0.02 18.99 0.00 37.31 0.00 0.00
51 30.37 0.11 -0.22 -0.01 -0.01 0.01 18.99 0.01 37.32 0.00 0.00
52 30.26 -0.11 -0.22 0.00 -0.01 0.00 19.00 0.01 37.32 0.00 0.00
53 29.93 -0.33 -0.22 0.00 -0.01 0.00 19.00 0.01 37.33 0.00 0.00
54 29.39 -0.54 -0.21 0.01 -0.01 0.01 19.01 0.01 37.34 0.00 0.00
55 28.65 -0.73 -0.19 0.02 -0.01 0.02 19.03 0.01 37.34 0.00 0.00
56 27.74 -0.91 -0.17 0.02 0.00 0.02 19.05 0.00 37.35 0.00 0.00
57 26.69 -1.06 -0.15 0.02 0.00 0.02 19.07 0.00 37.35 0.00 0.00
58 25.50 -1.18 -0.12 0.03 0.00 0.03 19.10 0.00 37.35 0.00 0.00
59 24.22 -1.28 -0.10 0.03 0.00 0.03 19.12 0.00 37.35 0.00 0.00
60 22.87 -1.35 -0.07 0.03 0.00 0.03 19.15 0.00 37.35 0.00 0.00
61 21.47 -1.39 -0.04 0.03 0.00 0.03 19.18 0.00 37.36 0.00 0.00
62 20.06 -1.41 -0.02 0.02 0.00 0.02 19.20 0.00 37.36 0.00 0.00
63 18.65 -1.41 0.00 0.02 0.00 0.02 19.22 0.00 37.36 0.00 0.00
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 9 of 17
64 17.26 -1.39 0.02 0.02 0.00 0.02 19.24 0.00 37.36 0.00 0.00
65 15.91 -1.35 0.04 0.02 0.00 0.02 19.26 0.00 37.37 0.00 0.00
66 14.60 -1.30 0.05 0.01 0.00 0.01 19.27 0.00 37.37 0.00 0.00
67 13.36 -1.24 0.06 0.01 0.00 0.01 19.28 0.00 37.37 0.00 0.00
68 12.18 -1.18 0.07 0.01 0.00 0.01 19.29 0.00 37.38 0.00 0.00
69 11.07 -1.11 0.07 0.00 0.00 0.00 19.29 0.00 37.38 0.00 0.00
70 10.04 -1.03 0.07 0.00 0.00 0.00 19.29 0.00 37.38 0.00 0.00
71 9.08 -0.96 0.07 0.00 0.00 0.00 19.29 0.00 37.38 0.00 0.00
72 8.20 -0.89 0.07 0.00 0.00 0.00 19.30 0.00 37.38 0.00 0.00
73 7.38 -0.81 0.07 0.00 0.00 0.00 19.30 0.00 37.38 0.00 0.00
74 6.64 -0.74 0.07 0.00 0.00 0.00 19.30 0.00 37.38 0.00 0.00
75 5.96 -0.68 0.07 0.00 0.00 0.00 19.30 0.00 37.39 0.00 0.00
76 5.34 -0.62 0.06 0.00 0.00 0.00 19.31 0.00 37.39 0.00 0.00
77 4.78 -0.56 0.06 0.00 0.00 0.00 19.31 0.00 37.39 0.00 0.00
78 4.28 -0.51 0.05 0.00 0.00 0.00 19.31 0.00 37.39 0.00 0.00
79 3.82 -0.46 0.05 0.00 0.00 0.00 19.32 0.00 37.39 0.00 0.00
80 3.41 -0.41 0.05 0.00 0.00 0.00 19.32 0.00 37.39 0.00 0.00
81 3.04 -0.37 0.04 0.00 0.00 0.00 19.33 0.00 37.39 0.00 0.00
82 2.71 -0.33 0.04 0.00 0.00 0.00 19.33 0.00 37.39 0.00 0.00
83 2.41 -0.30 0.03 0.00 0.00 0.00 19.33 0.00 37.39 0.00 0.00
84 2.15 -0.27 0.03 0.00 0.00 0.00 19.34 0.00 37.39 0.00 0.00
85 1.91 -0.24 0.03 0.00 0.00 0.00 19.34 0.00 37.39 0.00 0.00
86 1.70 -0.21 0.03 0.00 0.00 0.00 19.34 0.00 37.39 0.00 0.00
87 1.51 -0.19 0.02 0.00 0.00 0.00 19.35 0.00 37.39 0.00 0.00
88 1.34 -0.17 0.02 0.00 0.00 0.00 19.35 0.00 37.39 0.00 0.00
89 1.19 -0.15 0.02 0.00 0.00 0.00 19.35 0.00 37.39 0.00 0.00
90 1.06 -0.13 0.02 0.00 0.00 0.00 19.35 0.00 37.39 0.00 0.00
91 0.94 -0.12 0.01 0.00 0.00 0.00 19.35 0.00 37.39 0.00 0.00
92 0.83 -0.11 0.01 0.00 0.00 0.00 19.36 0.00 37.39 0.00 0.00
93 0.74 -0.09 0.01 0.00 0.00 0.00 19.36 0.00 37.39 0.00 0.00
94 0.66 -0.08 0.01 0.00 0.00 0.00 19.36 0.00 37.39 0.00 0.00
95 0.58 -0.07 0.01 0.00 0.00 0.00 19.36 0.00 37.39 0.00 0.00
96 0.52 -0.07 0.01 0.00 0.00 0.00 19.36 0.00 37.39 0.00 0.00
97 0.46 -0.06 0.01 0.00 0.00 0.00 19.36 0.00 37.39 0.00 0.00
98 0.41 -0.05 0.01 0.00 0.00 0.00 19.36 0.00 37.39 0.00 0.00
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 10 of 17
99 0.36 -0.05 0.01 0.00 0.00 0.00 19.36 0.00 37.39 0.00 0.00
100 0.32 -0.04 0.01 0.00 0.00 0.00 19.36 0.00 37.39 0.00 0.00
Table 2 - Straight Progress
Time Progress
Progress
Rate Ramp
Rate Disruption Efficiency
Absolute
Periodic
Disruption
Cumulative
Disruption
Index
Absolute
Periodic
Efficiency
Cumulative
Efficiency
Index MSD
Disruption MSD
Efficiency
0
0
0
0
0
1
10.00
10.00
10.00
10.00
10.00
10.00 10.00
10.00
10.00
100
100
2
10.00
0.00
-10.00
-20.00
-30.00
20.00 30.00
30.00
40.00
400
900
3
10.00
0.00
0.00
10.00
30.00
10.00 40.00
30.00
70.00
100
900
4
10.00
0.00
0.00
0.00
-10.00
0.00 40.00
10.00
80.00
0
100
5
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
6
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
7
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
8
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
9
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
10
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
11
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
12
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
13
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
14
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
15
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
16
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
17
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
18
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
19
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
20
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
21
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
22
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
23
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
24
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 11 of 17
25
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
26
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
27
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
28
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
29
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
30
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
31
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
32
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
33
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
34
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
35
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
36
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
37
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
38
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
39
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
40
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
41
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
42
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
43
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
44
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
45
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
46
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
47
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
48
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
49
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
50
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
51
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
52
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
53
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
54
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
55
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
56
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
57
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
58
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
59
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 12 of 17
60
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
61
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
62
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
63
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
64
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
65
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
66
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
67
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
68
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
69
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
70
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
71
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
72
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
73
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
74
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
75
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
76
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
77
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
78
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
79
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
80
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
81
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
82
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
83
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
84
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
85
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
86
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
87
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
88
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
89
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
90
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
91
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
92
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
93
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
94
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 13 of 17
95
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
96
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
97
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
98
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
99
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
100
10.00
0.00
0.00
0.00
0.00
0.00 40.00
0.00
80.00
0
0
Table 3 - Sculpted Progress
Time Progress
Progress
Rate Ramp
Rate Disruption Efficiency
Absolute
Periodic
Disruption
Cumulative
Disruption
Index
Absolute
Periodic
Efficiency
Cumulative
Efficiency
Index MSD
Disruption MSD
Efficiency
0
0
0 0 0
1
10.00
10.00 10.00 10.00 10.00
10.00 10
10
10 100
100
2
50.00
40.00 30.00 20.00 10.00
20.00 30
10
20 400
100
3
70.00
20.00 -20.00 -50.00 -70.00
50.00 80
70
90 2500
4900
4
50.00
-20.00 -40.00 -20.00 30.00
20.00 100
30
120
400
900
5
40.00
-10.00 10.00 50.00 70.00
50.00 150
70
190
2500
4900
6
30.00
-10.00 0.00 -10.00 -60.00
10.00 160
60
250
100
3600
7
20.00
-10.00 0.00 0.00 10.00
0.00 160
10
260
0 100
8
10.00
-10.00 0.00 0.00 0.00
0.00 160
0
260
0 0
9
10.00
0.00 10.00 10.00 10.00
10.00 170
10
270
100
100
10
10.00
0.00 0.00 -10.00 -20.00
10.00 180
20
290
100
400
11
0.00
-10.00 -10.00 -10.00 0.00
10.00 190
0
290
100
0
12
0.00
0.00 10.00 20.00 30.00
20.00 210
30
320
400
900
13
0.00
0.00 0.00 -10.00 -30.00
10.00 220
30
350
100
900
14
0.00
0.00 0.00 0.00 10.00
0.00 220
10
360
0 100
15
0.00
0.00 0.00 0.00 0.00
0.00 220
0
360
0 0
16
0.00
0.00 0.00 0.00 0.00
0.00 220
0
360
0 0
17
10.00
10.00 10.00 10.00 10.00
10.00 230
10
370
100
100
18
50.00
40.00 30.00 20.00 10.00
20.00 250
10
380
400
100
19
70.00
20.00 -20.00 -50.00 -70.00
50.00 300
70
450
2500
4900
20
50.00
-20.00 -40.00 -20.00 30.00
20.00 320
30
480
400
900
21
40.00
-10.00 10.00 50.00 70.00
50.00 370
70
550
2500
4900
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 14 of 17
22
30.00
-10.00 0.00 -10.00 -60.00
10.00 380
60
610
100
3600
23
20.00
-10.00 0.00 0.00 10.00
0.00 380
10
620
0 100
24
10.00
-10.00 0.00 0.00 0.00
0.00 380
0
620
0 0
25
0.00
-10.00 0.00 0.00 0.00
0.00 380
0
620
0 0
26
0.00
0.00 10.00 10.00 10.00
10.00 390
10
630
100
100
27
0.00
0.00 0.00 -10.00 -20.00
10.00 400
20
650
100
400
28
10.00
10.00 10.00 10.00 20.00
10.00 410
20
670
100
400
29
10.00
0.00 -10.00 -20.00 -30.00
20.00 430
30
700
400
900
30
30.00
20.00 20.00 30.00 50.00
30.00 460
50
750
900
2500
31
30.00
0.00 -20.00 -40.00 -70.00
40.00 500
70
820
1600
4900
32
20.00
-10.00 -10.00 10.00 50.00
10.00 510
50
870
100
2500
33
10.00
-10.00 0.00 10.00 0.00
10.00 520
0
870
100
0
34
10.00
0.00 10.00 10.00 0.00
10.00 530
0
870
100
0
35
0.00
-10.00 -10.00 -20.00 -30.00
20.00 550
30
900
400
900
36
0.00
0.00 10.00 20.00 40.00
20.00 570
40
940
400
1600
37
0.00
0.00 0.00 -10.00 -30.00
10.00 580
30
970
100
900
38
0.00
0.00 0.00 0.00 10.00
0.00 580
10
980
0 100
39
0.00
0.00 0.00 0.00 0.00
0.00 580
0
980
0 0
40
0.00
0.00 0.00 0.00 0.00
0.00 580
0
980
0 0
41
0.00
0.00 0.00 0.00 0.00
0.00 580
0
980
0 0
42
0.00
0.00 0.00 0.00 0.00
0.00 580
0
980
0 0
43
0.00
0.00 0.00 0.00 0.00
0.00 580
0
980
0 0
44
0.00
0.00 0.00 0.00 0.00
0.00 580
0
980
0 0
45
0.00
0.00 0.00 0.00 0.00
0.00 580
0
980
0 0
46
0.00
0.00 0.00 0.00 0.00
0.00 580
0
980
0 0
47
10.00
10.00 10.00 10.00 10.00
10.00 590
10
990
100
100
48
10.00
0.00 -10.00 -20.00 -30.00
20.00 610
30
1020
400
900
49
10.00
0.00 0.00 10.00 30.00
10.00 620
30
1050
100
900
50
10.00
0.00 0.00 0.00 -10.00
0.00 620
10
1060
0 100
51
10.00
0.00 0.00 0.00 0.00
0.00 620
0
1060
0 0
52
10.00
0.00 0.00 0.00 0.00
0.00 620
0
1060
0 0
53
10.00
0.00 0.00 0.00 0.00
0.00 620
0
1060
0 0
54
10.00
0.00 0.00 0.00 0.00
0.00 620
0
1060
0 0
55
10.00
0.00 0.00 0.00 0.00
0.00 620
0
1060
0 0
56
10.00
0.00 0.00 0.00 0.00
0.00 620
0
1060
0 0
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 15 of 17
57
10.00
0.00 0.00 0.00 0.00
0.00 620
0
1060
0 0
58
10.00
0.00 0.00 0.00 0.00
0.00 620
0
1060
0 0
59
0.00
-10.00 -10.00 -10.00 -10.00
10.00 630
10
1070
100
100
60
0.00
0.00 10.00 20.00 30.00
20.00 650
30
1100
400
900
61
0.00
0.00 0.00 -10.00 -30.00
10.00 660
30
1130
100
900
62
0.00
0.00 0.00 0.00 10.00
0.00 660
10
1140
0 100
63
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
64
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
65
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
66
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
67
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
68
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
69
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
70
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
71
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
72
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
73
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
74
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
75
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
76
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
77
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
78
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
79
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
80
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
81
0.00
0.00 0.00 0.00 0.00
0.00 660
0
1140
0 0
82
10.00
10.00 10.00 10.00 10.00
10.00 670
10
1150
100
100
83
20.00
10.00 0.00 -10.00 -20.00
10.00 680
20
1170
100
400
84
30.00
10.00 0.00 0.00 10.00
0.00 680
10
1180
0 100
85
20.00
-10.00 -20.00 -20.00 -20.00
20.00 700
20
1200
400
400
86
10.00
-10.00 0.00 20.00 40.00
20.00 720
40
1240
400
1600
87
10.00
0.00 10.00 10.00 -10.00
10.00 730
10
1250
100
100
88
10.00
0.00 0.00 -10.00 -20.00
10.00 740
20
1270
100
400
89
10.00
0.00 0.00 0.00 10.00
0.00 740
10
1280
0 100
90
10.00
0.00 0.00 0.00 0.00
0.00 740
0
1280
0 0
91
10.00
0.00 0.00 0.00 0.00
0.00 740
0
1280
0 0
PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 16 of 17
92
10.00
0.00 0.00 0.00 0.00
0.00 740
0
1280
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PM World Journal Generalized Analysis of Value Behavior over Time
Vol. I, Issue III – October 2012 as a Project Performance Predictor
www.pmworldjournal.net Featured Paper Bob Prieto
© 2012 Bob Prieto www.pmworldlibrary.net Page 17 of 17
About the Author
Bob Prieto
Author
Bob Prieto is a senior vice president of Fluor, one of the largest,
publicly traded engineering and construction companies in the world. He is responsible
for strategy for the firm’s Industrial & Infrastructure group which focuses on the
development and delivery of large, complex projects worldwide. The group
encompasses three major business lines including Infrastructure, with an emphasis on
Public Private Partnerships; Mining; and Manufacturing and Life Sciences. Bob
consults with owner’s of large engineering & construction capital construction programs
across all market sectors in the development of programmatic delivery strategies
encompassing planning, engineering, procurement, construction and financing. He is
author of “Strategic Program Management” and “The Giga Factor: Program
Management in the Engineering and Construction Industry” published by the
Construction Management Association of America (CMAA) and “Topics in Strategic
Program Management” as well as over 400 other papers and presentations.
Bob’s industry involvement includes recent and ongoing roles on the National
Infrastructure Advisory Council’s Critical Infrastructure Resiliency Workgroup and the
National Academy Committee “Toward Sustainable Critical Infrastructure Systems:
Framing the Challenges”. He is a member of the ASCE Industry Leaders Council,
National Academy of Construction and a Fellow of the Construction Management
Association of America. Bob served until 2006 as one of three U.S. presidential
appointees to the Asia Pacific Economic Cooperation (APEC) Business Advisory
Council (ABAC), working with U.S. and Asia-Pacific business leaders to shape the
framework for trade and economic growth and had previously served as both as
Chairman of the Engineering and Construction Governors of the World Economic
Forum and co-chair of the infrastructure task force formed after September 11th by the
New York City Chamber of Commerce.
Previously, as a senior industry executive, he established a 20-year record of building
and sustaining global revenue and earnings growth. As Chairman at Parsons
Brinckerhoff (PB), one of the world’s leading engineering companies, Bob shaped
business strategy and led its execution. Bob Prieto can be contacted at
Bob.Prieto@fluor.com.
Article
Full-text available
This Executive Insight looks at large complex programs from a systems perspective recognizing that such programs are not as well bounded as classical project management theory, as espoused by Taylor, Gantt and Fayol , would have us believe. Rather, they behave in both independent and interconnected ways in a dynamic systems environment. They demonstrate the evolutionary nature of all complex systems. They face uncertainty and emergence that comes with human actions and interactions. Large complex programs struggle from insufficient situational awareness, treating the program to be more well-bounded than reality would suggest and using simplified models to understand the complexity inherent in execution. Best practices from project management were typically not derived from such environments and, worse, have fallen short on other large complex programs. Large complex programs are characterized by boundaries that change in response to changing environments; emphasize coping with challenges and change; go beyond uncertainty and require a change in perspective; face a high level of unknown unknowns and unclear/incompatible stakeholder needs. Systems theory represents a different way of seeing, thinking and acting Systems are viewed as greater than the sum of their parts. A system’s holistic properties can never be completely known. Different perspectives will provide different views that may overlap and not be completely compatible.
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This paper examines the postulate that an important function of the activity of antagonist muscle groups is to modulate mechanical impedance. Some biomechanical modeling and analyses are presented leading to a prediction of simultaneous activation of antagonist muscles in the maintenance of upright posture of the forearm and hand. An experimental observation of antagonist coactivation in this situation is presented.