Cash Flow Forecasting Model for General Contractors Using
Moving Weights of Cost Categories
Hyung K. Park1; Seung H. Han2; and Jeffrey S. Russell3
Abstract: This research introduces the development of a project-level cash ﬂow forecasting model from a general contractor’s viewpoint.
While most previous models have been proposed to assist contractors in forecasting cash ﬂow in the early stage of pretendering or the
planning phase, this paper aims to provide a tool that can be applicable during the construction phase based on the planned earned value
and the actual incurred cost on a jobsite level. The critical key to cash ﬂow forecasting at this level lies in how to build a realistic cash-out
model. Toward the end, this paper adopts moving weights of cost categories in a budget that are variable depending on the progress of
construction works. In addition, it addresses time lags in accordance with the contractual payment conditions and credit times given by
suppliers or vendors. As for the cash-in model, net planned monthly earned values are simply transferred to the cash-in forecast with a
consideration of billing time and retention money. Validation of the proposed model involves applying realistic data from four ongoing
projects. Based on the results of comparative analyses, the writers conclude that the proposed model is more accurate and reliable, yet
simpler to ﬁeld engineers who are generally not familiar with certain intricate ﬁnancial knowledge.
DOI: 10.1061/ ASCE 0742-597X 2005 21:4 164
CE Database subject headings: Financial management; Forecasting; Contractors; Cost control; Construction industry.
integrated schedule and cost items using a simulation model ap-
plied to the stochastic duration of the activities. However, it does
not consider the time lag’s impact on costs, which is essential in
cash ﬂow forecasting. The technique proposed by Sears 1981 is
Cash is the most important of a construction company’s re-
viewed accurately by manually integrating the schedule and cost
sources. More construction companies fail due to a lack of liquid-
items, but it requires considerable work and further, it does not
ity for supporting their daily activities than because of inadequate
consider the time lag between the expenditure and payment of a
management of other resources Singh and Lakanathan 1992;
related cost item. Navon’s model 1995, 1997 automatically in-
Navon 1994 . Russell 1991 pointed out that more than 60% of
tegrates the bill of quantity BOQ , cost estimate, and the sched-
construction contractor failures are due mainly to economic fac-
ule associated with a lower level of resources. However, if either
the BOQ or the schedule is altered due to various changes, inte-
tors. In an attempt to analyze the real business environment in the
gration is likely to be more complicated and time consuming.
construction industry, various forecasting methods have been ap-
Moreover, the main obstacle to automating the integration process
plied to cash ﬂow management.
is compatibility between cost items of the BOQ and activity ele-
Numerous techniques for cash ﬂow forecasting and manage-
ments of schedule.
ment differ in their levels of accuracy and detail, the degree of
In an attempt to improve the accuracy of a model for forecast-
automation in compiling them, and the method to integrate the
ing cash ﬂow, Ashley and Teicholz 1977 suggested a cash ﬂow
time and money elements. Some of the techniques are probabilis-
forecast based on detailed methods of cost ﬂow. They classiﬁed
tic, but most of them are deterministic Navon 1995 . Rein-
the direct cost by a number of cost categories such as labor, ma-
schmidt and Frank 1976 proposed a model for cash ﬂow fore-
terials, and equipment which are speciﬁed as percentages of total
casting in the early planning stage of a project. This model
cost. This approach is very realistic because it considers the na-
ture of the budget and cost. However, each of these cost elements
is assumed to be a ﬁxed percentage of total cost over the project’s
PhD, General Manager, G.K CM Team, Daewoo Engineering &
duration. Moreover, this model does not consider the effect of
Construction Co. Ltd., Seoul, Korea. E-mail: email@example.com
time lags on the costs. Also, Gates and Scarpa 1979 and Peer
Associate Professor, Dept. of Civil and Environmental Engineering,
1982 developed cash ﬂow models in the conceptual and plan-
ning stages using algebraic formulations and polynomial regres-
3Professor, Dept. of Civil and Environmental Engineering, Univ. of
sions. However, none of these models considered time lags to the
Wisconsin, Madison, WI. E-mail: firstname.lastname@example.org
costs and earned values.
Note. Discussion open until March 1, 2006. Separate discussions must
In reality, many factors exist during construction that may af-
be submitted for individual papers. To extend the closing date by one
fect the cash ﬂow including time delays, cost overruns, uncon-
month, a written request must be ﬁled with the ASCE Managing Editor.
ﬁrmed earned values, change orders, and changes of cost plan
The manuscript for this paper was submitted for review and possible
elements Bennett and Ormerod 1984 . The key points of cash
publication on November 2, 2004; approved on March 18, 2005. This
paper is part of the Journal of Management in Engineering, Vol. 21, No.
ﬂow forecasts lie in how accurate, ﬂexible, and comprehensive
4, October 1, 2005. ©ASCE, ISSN 0742-597X/2005/4-164–172/$25.00.
they are to be calculated and how effectively they consider uncer-
164 / JOURNAL OF MANAGEMENT IN ENGINEERING © ASCE / OCTOBER 2005
tain factors such as time delay, cost overrun, variation of cost, and
can be more accurate, ﬂexible, and simpler to typical ﬁeld engi-
earned value between plan and actual. Of course, it is impossible
neers on a job site.
to ensure that a project will deﬁnitely be as successful as initially
planned. Even though construction is in progress, cash ﬂow fore-
casts cannot be determined precisely. As a result, most models
Cash Flow to General Contractor
and techniques aforementioned are found to have the following
problems: 1 they are not based on the construction stage, but
Typical Project Cash Flow
rather only on the planning or preliminary stages in the project
delivery process; 2 they do not consider time lags for the costs
Most construction projects are individual proﬁt centers, each with
and earned values in forecasting cash ﬂow; and 3 with regard to
its own cash cycle based on the costs of activities related to the
integration of cost items and activities, they are not compatible
project and on payments from a client, both of which are pre-
with each item and are rather complicated depending on when
scribed by a contract. Typical cash ﬂow on a construction project
consists of: 1 cash out such as bid costs, preconstruction costs
change factors occur in the subsequent construction stage.
engineering, design, mobilization, etc. , materials and supplies,
Because cash ﬂow is a reality, a cash ﬂow forecast on a job site
equipment and equipment rentals, payments of subcontracts, labor
should be more precise than those during the preconstruction
and overhead; and 2 cash in such as billings less retentions ,
phases by addressing the uncertainties of the construction busi-
retentions, claims and change orders. The factors that affect cash
ness and jobsite procedures. The main objectives of this paper
ﬂows are the duration of the project, the retention conditions, the
are: 1 to quantitatively study construction project cash ﬂows; 2
times for receiving payments from the client, credit arrangement
to propose a forecasting cash ﬂow model for construction projects
with suppliers or vendors, equipment rentals, and times of pay-
with a consideration of both variable cost weights and a time lag;
ments to subcontractors, etc.
and 3 to validate the proposed model and suggest guidelines for
Cash ﬂow at the project level consists of a complete history of
implementing this cash ﬂow forecasting system. In addition, this
all cash disbursement and all earnings received as a result of
paper provides implications to management by focusing more on
project execution. Many construction projects have negative net
how project managers or ﬁeld engineers can beneﬁt by using the
cash ﬂows until the very end of construction when the ﬁnal pay-
ment is received or advanced payment is received before starting
the project. This is a typical situation when the ﬁnal payment
Research Scope and Methodology
consists of retention money and the retention percentage is greater
than the proﬁt percentage of the project.
Among a variety of types of construction projects, this research is
focused on bid projects. The proposed model is intended to be
Structure of Construction Budget
applicable to the construction stage in the project delivery process
from a general contractor’s viewpoint. Accordingly, the research
A budget structure in construction projects is constituted of cost
scope does not include investment projects such as Build–
accounts such as bills, sections, items, and resources. A budget
Operate–Transfer or Build–Operate–Own. Moreover, this re-
is a plan for allocating resources Meredith and Mantel 1995 .
search is relevant to the viewpoint of cash ﬂow management at
Hendrickson and Au 1989 identiﬁed the fact that allocation of a
the project level, and subsequently project evaluation is per-
cost to the budget may be used to develop the cost function of an
formed by allowing contractors to reﬂect the capital cost or so-
operation. The basic idea in this method is that each expenditure
called, interest cost whenever negative cash ﬂows occur.
item can be assigned to particular categories of operation. Ideally,
To achieve its end, methodology should possess several nec-
the allocation item of joint costs should be causally related to the
category of basic costs in an allocation process. Generally, a bud-
essary steps. As an initial step to meet the objectives, previous
get structure in construction projects is set up into labor, material,
research papers that deal with cash ﬂow management are re-
equipment, subcontract, and indirect expenses. If a general con-
viewed to investigate problems with existing cash ﬂow forecast-
tractor performs all the areas of job management on site, expenses
ing models. It should then suggest a new model of cash ﬂow
for management and overhead cost become a higher burden to the
forecasting for a jobsite using a new algorithm. A numerical ex-
general contractor. To mitigate these costs, general contractors
ample is prepared to demonstrate and verify the computational
prefer to distribute a role of management to other participants. As
aspects of the model. The next step is to perform a simulation
an example, if a portion of a subcontract is increased, the general
using experimental data and to compare the model results to ex-
contractor is able to decrease the indirect expenses used for hiring
isting models proposed by other researcher. The last step of this
project personnel: the workers, supervisory personnel, and engi-
research is to validate the model. Although the model is devel-
neers associated with the project. From the general contractor’s
oped to offer a practical guideline to improve forecasting quality
viewpoint, labor and equipment costs are uncertain because pro-
in evaluating the cash ﬂow on a job site, objectively assessing the
ductivity is extremely volatile and hard to measure. For this rea-
validity of the model in a real business scheme is quite difﬁcult.
son, general contractors attempt to hire subcontractors to reduce
Accordingly, a comparative case study methodology is chosen as
job-management costs and to maximize their proﬁt opportunity
a proper validation approach to the research features. Four
by concentrating their control ability on variable costs, uncertain
projects in progress, including one building project and three civil
time, and strict quality. Typically, the portions of subcontract cost
projects, with data compiled over a duration of 12 months are
range from 50 to 70%. Material, labor, equipment, and indirect
identiﬁed as the case study materials. Based on the results of
cost are arrayed between 25 and 35%, 5 and 15%, 10 and 25%,
comparative analyses, we measure to see if the proposed model
and 5 and 15%, respectively Oberlender 2000 .
JOURNAL OF MANAGEMENT IN ENGINEERING © ASCE / OCTOBER 2005 / 165
Jobsite Cash Flow Forecast Model
The critical key to cash ﬂow forecasting at the project level is
how to build a cash-out model. All resources to be incurred to
costs in a budget have different time lags. They are subject to
contracting procedures and a corporation’s payment policy to
other organizations. Accordingly, cash-out forecasts set the tone
for time lags. Cost categories are classiﬁed in order to compile
construction resources with similar time lags. Time lag, as used
here, is based on contracting payment conditions and credit times
given by suppliers or vendors.
Ahuja and Walsh 1983 also insist that there are delays be-
Fig. 1. Comparison of weights of costs during construction period
tween the dates of costs incurred and the dates of payment due.
These delays will vary depending on resource types and credit
arrangements as negotiated with subcontractors and suppliers.
For that reason, whenever costs are incurred in a periodic
This approach is maintained by a number of previous researchers
month, weights of cost categories relative to the remaining budget
Peterman 1973; Ashley and Teicholz 1977; McCaffer 1979;
are changed, even though neither the overall budget the forecast
Trimble 1982; Kenley and Wilson 1989; Navon 1995; Kaka
total cost nor the planning for execution is changed. Moreover, if
a change of project amount or project duration occurred due to a
Different cost categories are deﬁned for materials, labor,
change order or a change of contract conditions, weights of cost
equipment, subcontractors, indirect expenses site overhead , and
categories should also be adjusted Park 2001 .
depreciation items since these cost categories generally have dif-
Consequently, this implies that the next weight of a cost cat-
ferent time lags. If additional cost categories are needed, they can
egory to be applied will be set in accordance with the cumulative
be classiﬁed. As mentioned before, since payment conditions of
actual cost and the remaining budget. Thus, “the moving weights
subcontracts are controlled by general contractor policy, it can be
method” continuously changes over the project duration to pertain
noted that the general contractors entail 50–70% certainty in cash
to the remaining budget. Applying moving weights of cost cat-
ﬂow forecasting regarding time lags. The only remaining prob-
egories to the remaining budget in a month time series reduces
lems are how to determine time lags of other cost categories and
the uncertainty of forecasting cash out for the remaining duration
how to plan a budget for each period.
of the project. This characteristic of a budget during the construc-
Jepson 1969 suggested that net cash ﬂow for individual
tion period is illustrated in Fig. 2.
projects must be derived from “component” curves of inﬂow and
outﬂow proﬁles. Fondahl and Bacarreza 1972 claimed that total
costs can be broken down as to category since different cost re-
sources may have different cost curves or different time lags re-
lated to their payment.
Generally, earned values will be received on a monthly basis or
based on billing terms, but planning of earned values on a jobsite
Moving Weights of Cost Categories
is established by a monthly amount. Earned value planning is the
Ashley and Teicholz 1977 developed ﬁve cost curves for cost
basis for estimated cash-in values in actual cash ﬂow analysis.
categories in their highway construction project. Fondahl and
Net planned monthly earned values are simply transferred to the
Bacarreza 1972 also applied three cost curves to their school
cash-in forecast, to be applied there with appropriate time lags.
project Curves 1, 2, and 3 . Curve 1 is based on the assumption
The billing period, the time between the dates of bill submittal
that the rate of expenditure will be uniform over the project du-
and the progress payment receipt, is stipulated in the contract. If a
ration. Curve 2 assumes that only 25% of the total cost is incurred
payment delay occurs due to the owner’s circumstances, the bill-
during the ﬁrst half of the project duration and the remaining 75%
ing time of cash in can be adjusted in this model. In practice,
in the second half. Curve 3 assumes that 75% of the total cost is
billing terms in the contract should provide for a billing schedule
incurred in the ﬁrst half of project duration. In their research, only
for owner and contractor, but those terms can be applied variously
depending on the owner’s ﬁnancing situation.
ﬁeld overhead and home ofﬁce overhead costs were analogous to
Curve 1, which implies that only these costs were assumed to be
incurred at a uniform rate over the project duration.
In other words, all cost categories except ﬁeld overhead and
home ofﬁce overhead were not incurred at a uniform rate over the
project lifetime. Unless the curves of all cost categories are uni-
form, the relative weights of the different cost categories should
be changed whenever costs are incurred over the project duration.
If weights of cost categories are uniform over the project dura-
tion, curves of all categories should represent straight lines. The
concepts of the moving weights method and ﬁxed weights method
are illustrated in Fig. 1.
Fig. 2. Characteristic of budget during construction period
166 / JOURNAL OF MANAGEMENT IN ENGINEERING © ASCE / OCTOBER 2005
Cash-in planning should consider the effects of retention money
and the billing period on earned values. Retention money is based
on a percentage of retention stipulated in the contract. A cumula-
tive cash-in curve is obtained from the cumulative earned value
curve by applying a retention rate and billing period. Generally,
contractors can improve cash ﬂow by providing percent retention
schedules in contracts with subcontractors. Then, the retention
money is released when construction is completed and accepted.
If cash in is properly planned and manipulated by a model, it will
supply the funds necessary to meet the cash requirements of the
project without borrowing from other organizations.
Mathematical Algorithm of Model
The model algorithm for cash out can be represented by equa-
tions. In cash out, the cost categories in an initial budget can be
classiﬁed depending on the time lags of all resources in the bud-
get. After that, the following equation is applied:
initial weight wi = Ci ÷ TB
where i = cost categories; Ci= budget of individual cost categories;
and TB= initial total budget total costs .
Whenever deviation between actual and planned data occurs,
an adjustment of weight is calculated and applied to the next cash
Fig. 3. Process of model
planning. Since actual cost in accordance with initial weight of
each cost category in each month is not incurred, actual cost and
actual earned value should be reﬂected in the next weights of
TCt= actual cumulative total cost; and FCt+1,i= actual cash-out
individual categories. The weight is called the “moving weight”
in this research. Therefore, the next moving weight to be applied
Earned value is converted to cash in by deducting retention and
wi = Ci ÷ TB
applying billing time. This model considers that most contractors
Ci= remaining budget of individual cost category and
withhold retention from subcontractors at the same rate they are
TB= remaining total budget.
withheld by the owner. Therefore cash in should consider two
From Eqs. 1 and 2 , the constraints on weights of the indi-
kinds of retention money: contractors’ retention and subcontrac-
vidual cost categories can be represented by the following
tors’ retention. Hence, the cash in is calculated as follows:
CIt = Vt
1 − rc + rs
wi = 1
where CIt= cash in at the time t; Vt= earned value at the time t;
rc= contractual retention rate; rs= subcontractual retention rate;
and St= subcontract cost at the time t.
wi = 1
Depending on the contractual agreement, release of retention
where i = individual cost categories.
is prescribed in two ways: ﬁrst at the completion of the contract
As a result, equations for the moving weights cash-out model
and second, at the end of the maintenance period. The model is
are as follows. In terms of this model, the algorithm can be con-
simulated by entering the ﬁgures of release of retention by con-
tinuously updated to the weight to be applied in each month over
tractors whenever the subcontract ends.
the project duration
Ft+1,i = wt+1,i
Fig. 3 illustrates an integrated process of model to cash ﬂow
forecasting. It consists of three steps designed for general contrac-
Ct,i − ACt,i
tors on a job site level to evaluate cash ﬂow. The ﬁrst step re-
TBt − TCt
quires input data for evaluating each individual project, such as
planned earned values and budget cost to each month, cost cat-
egories, weights, and time lags. If more cost categories due to
different time lags are required, the users can classify separate
where Ft+1,i= forecast of individual cost categories of time series
in period t + 1; Ct+1= planned costs of time series in period t + 1;
The second step updates new weights to cost categories re-
wt+1,i= weights of cost categories of time series in period t + 1;
ﬂected on actual cost. Also, forecast cash ﬂow such as cash in,
AC,i= actual cumulative cost of individual cost categories;
cash out, cumulative cash ﬂow, and capital cost are automatically
JOURNAL OF MANAGEMENT IN ENGINEERING © ASCE / OCTOBER 2005 / 167
Table 1. Example of Cash Forecasting at Start of Projecta
Time lag days
Initial weight %
aUnit=1,000 US dollars.
calculated. This stage is based on moving weights of each classi-
model since that is not generally considered as a job or project
ﬁed cost category in each month. Moving weight is that weight to
cost. That is incurred at the company level and accordingly may
be applied to the next month that is adjusted and calculated by
be billed directly on a jobsite.
deducting the actual cost from the initial budget to the individual
classiﬁed cost category in each month. Therefore, a weight of
each budget of each individual cost category to the remaining
budget is to be changed every month.
To illustrate the new methodology proposed, we have conducted a
The ﬁnal step provides feedback to estimate the new planned
simple case study. The illustrative case is composed with the fol-
earned values and budget for each month. Whenever deviations
lowing ﬁgures: project duration is 12 months, contract amount is
between planned and actual costs and earned values occur, they
US$12,529,000, and budget is US$12,332,000. Input variables for
are automatically distributed over the remaining duration if
the case are: 1 planned earned values PE , planned budget
needed. If deviations between them are considerably more or less
PB , actual earned value AE , and actual cost AC at each
than expected, the project manager must modify the initial plan-
month; 2 cost categories classiﬁed based on contract procedure;
ning to forecast cash ﬂow.
3 weight percentage and credit time of each cost category; 4
As a basis for applying the proposed model, this paper sets up
billing time and percentage of retention to be stipulated in con-
basic assumptions: 1 in the initial time period, the planned
tract; and 5 percentage of interest to be applied by corporate
earned value to the contract amount and planned cost to the bud-
policy or decision. According to investigations by Singh and La-
get are not automatically generated each month. Instead they are
kanathan 1992 , the application of “S curves” for cash ﬂow pro-
made independently by engineers on the jobsite by their own
jections can achieve an accuracy of approximately 88–97%. Sub-
method of planning. 2 Time lags of cost categories are based on
sequently, input data at each month are based on S curves.
corporate historical data and company policy. 3 Cost categories
The basic assumptions applied to the case study are: 1
classiﬁed at the start of a project have to continuously be used in
changes of AC and AE against PE and PB at each month are
order to maintain the degree of accuracy in moving weight over
addressed, but overrun of budget and delay of duration are not
the project duration. 4 This model is used to forecast cash ﬂow
considered; 2 cost categories depending on time lags are simply
values at the close of each month last day of the month . 5
classiﬁed as labor 0 days , materials 150 days , rent equipment
Depreciation of company owned equipment is included in actual
0 days , depreciation of owned equipment 0 days , subcontract
cash transfer incurred cost in order to show cash ﬂow at the
150 days , and ﬁeld expense 0 days ; 3 billing time to earned
project level. 6 Home ofﬁce overhead is not considered in this
value is 120 days and percent of retainage is 0% of earned value
168 / JOURNAL OF MANAGEMENT IN ENGINEERING © ASCE / OCTOBER 2005
Table 2. Example of Updated Cash Forecasting after “1” Montha
Depreciation Equipment Main materials Sub-Con
Actual cost after 1 month
Actual weight %
New moving weight %
aUnit=1,000 US dollars.
each time; 4 in consideration of different time lags of cost cat-
actual cost US$729 is incurred, we can update new weights to
egories, cash ﬂow is calculated each 30 days; and 5 whenever
cost categories. The proposed model employs weights that are
negative cumulative cash ﬂow occurs, internal interest 10% is
updated based on weight percentage of cost categories to the re-
maining budget each month over the duration, while the tradi-
Table 1 represents the example of cash forecasting at the be-
tional approach is designed based only on weights to the initial
ginning of project “0” month made in accordance with the basic
total budget. For example, new moving weight of the material
conditions and aforementioned algorithm with considerations of
cost category 34.14% can be updated by dividing the remaining
time lags and moving weights. As an example, in time period of
budget of material US$3,960.82 to the remaining total budget
30 days, cash out US$83.03 is gaged only considering cost cat-
US$11,603 . Table 2 shows an example of the updated cash bal-
egories that have no time lags
ance negative US$3,025,000 in accordance with these revised
sum of initial weights of labor, equipment, and expenses
7.75% . It expects that the ﬁnal cash balance at completion will
be negative—around US$3,316,000. As the ﬁrst month passes and
Validation of Model
Model validation includes measuring the accuracy of a model in
Table 3. Project Overview
describing the actual conditions of a problem to solve and in
Project A: apartment
• 8–25 story seven building apartment
Table 4. Project Basic Dataa
• 490 unit
• Area: 279 ha
Project B: industrial complex
• Width: 20 M four lane
• Earth work: 19 million m3
Total budget dollars
• Joint venture project
Project C: railway
• Total length: 11.432 km
• Bridge: 12 4,867 m
• Tunnel: 1 545 m
• Stations: three stop
• Joint venture project
Project D: sewage treatment
• Treatment capacity: 80,830 t / day
aUnit=1,000 US dollars.
JOURNAL OF MANAGEMENT IN ENGINEERING © ASCE / OCTOBER 2005 / 169
Table 5. Time Lags for Each Cost Categorya
Table 6. Billing Time and Delay in Payment for Each Projecta
Delay in paymentb
bDelay payment is total delay time from the client.
bThe last day of the month when cost is incurred.
lations are performed on each project in order to compare the
cEquipment cost is charged to expense of cash out in accounting
accuracy of forecasting models. Subsequently, 48 simulations per
each project and a total of 192 simulations were performed for
four projects. In the comparative analysis the results of forecast-
evaluating the usefulness of the model in terms of its objectives to
ing are applied to cash ﬂow each month instead of the cumulative
a larger case with similar problem contexts. Stated earlier, a com-
cash ﬂow forecasting applied previously in experiments since pre-
parative case study methodology was used to validate whether the
vious cash ﬂow affects subsequent cash ﬂow.
model meets its development objective.
To compare the accuracy of two models, MWM and FWM, the
simulation is performed in accordance with the following two
types: 1 Type 1—planned data and actual data are identical to
each other. This type is used to determine the reliability of the
To verify the model, we performed simulation using empirical
model and compare the two methods under ideal conditions since
data from actual projects in progress. Simulation results based on
planned data are one of the most critical variables in this forecast-
the proposed model and existing model are compared. A simula-
ing cash ﬂow model, and 2 Type 2—planned data and actual
tion template is implemented in a common spreadsheet
data are different as reported by the jobsite for 12 months. In this
package—Microsoft Excel™—for the simulation experiments.
case, the uncertainty of the construction job site is involved and
Considering different time lags of cost categories, cash ﬂow is
the effect of planned data on the forecasting cash ﬂow is consid-
calculated in monthly increments. The ﬁxed weights method
ered. Finally, the following data are required for comparative
FWM —the current approach—applies ﬁxed weights to cost cat-
analysis of the four projects in progress:
egories over project duration, whereas the moving weights
Time lags of billing time and individual cost categories see
method MWM —the new proposed model—applies different
Tables 5 and 6 ;
weights each month using a new algorithm. The results of these
Total contract amount and total budget reﬂect contract
two models were then compared to show the accuracy and con-
amount and budget changed during the construction stage;
sistency of the model. The stepwise procedures for the validation
Monthly cost planning data and earned value planning data;
of the proposed model are as follows:
Weights of cost categories in the budget;
Four actual projects in progress including one building and
Retention rate and capital cost rate; and
three civil infrastructure projects, with data compiled over a
Actual cash ﬂow such as cash in and cash out for each
duration of 12 months see Tables 3 and 4 ;
To obtain forecast cash ﬂow data, MWM and FWM are ap-
plied to actual data through the simulation; and
To compare the accuracy of MWM to FWM, the results of
the simulation are analyzed.
To simulate the dynamic cash ﬂow forecasting, simulation ex-
Measurement of Accuracy
periments were conducted 12 times from the ﬁrst to the twelfth
Mean absolute deviation MAD was used to measure the error
month by each method for individual projects and compared by
for each month’s forecasted cash ﬂow by means of the two mod-
the two methods: MWM and FWM. In addition, 2 types of simu-
els: MWM and FWM. The MAD is a commonly used measure
Table 7. Example of Comparative Analysis for Project Aa
Actual cash ﬂow
Forecasting cash ﬂow
Mean absolute deviation
MWM moving weights method; and FWM ﬁxed weights method.
aSimulation 1—after 1 month, Type 1.
170 / JOURNAL OF MANAGEMENT IN ENGINEERING © ASCE / OCTOBER 2005
Table 8. Comparison of Mean Absolute Deviation MAD in Moving
Table 10. Reliability of Moving Weights Method Type 1 a
Weight Method MWM and Fixed Weights Method FWM
Type 1 a
A / B
amount B b
B − A
aUnit 1,000 US dollars.
bContract amount means total earned values for 12 months.
aUnit=1,000 US dollars.
bIt is calculated by Eq. 9 through the 12 times of simulations from
In the same way, the average MAD can be calculated through
the 1st month to the 12th month refer to Table 7 for the case of
the 12 times of simulations from the ﬁrst month to the twelfth
simulation 1 .
month. Based on the results of MAD for simulations, MWM is
MAPE= 26.803÷ 41.207= 65.04%.
more accurate than FWM. In the Type 1 simulation, the accuracy
is 0.28–65.04%, with an average of 32.30% higher than FWM in
that forecasts accuracy as the degree of variation by the following
the ideal condition, where planning is well established as reﬂected
equation. This measure is simply the measure of the absolute
on the construction jobsite, and continuously updated
deviations for all forecasts
Table 8 . In the case of Type 2, the accuracy is 1.14–4.54%, an
average of 2.13% higher see Table 9 . As a result, the degree of
accuracy of MWM is an average of 17.21% higher than FWM.
ti − Fcfti
ti = actual value of cash ﬂow, Fcfti = forecasting value of
cash ﬂow at t month by the ith simulations, respectively;
Kenley and Wilson 1986 and Kaka and Price 1991 suggested
t = 1 – 12; i = 1 – 12; and n = number of observations.
that the error range of forecasting in the construction industry is
In comparative analysis, the mean absolute percent error
within ±3% of the contract amount. This is considered an accept-
MAPE method was estimated for comparing errors. It can be
able limit and demonstrates the reliability of the proposed model.
achieved by dividing the difference between MAD of MWM and
The error range of the forecasting is 0.23–0.6%, with an average
FWM by MAD of MWM. This fraction represents how large the
of 0.38% for four projects in Type 1, and 0.82–2.78%, with an
error of FWM is as compared to MWM. All absolute deviation
average of 1.79% for four projects in Type 2 see Tables 10 and
data between MWM and FWM are summed and divided by the
11 . Despite unavoidable errors in the planning data, the result is
number of observations, by the following equations:
thought of as being reasonably attained by applying the model for
forecasting. Consequently, the reliability of the MWM model is
acceptable and well demonstrated based on simulation.
ti − fMADii
average MAPE =
Practical Implications to Industry
where mMADti= MAD value of MWM at t month by ith simula-
Financial management has long been recognized as an important
ti = MAD value of FWM at t month by ith simulation;
and n = number of observations.
management tool. A company can survive a transitional period
The cash ﬂow data consisted of four detailed real projects in
without a proﬁt, or even with a loss; however, it may fail due to
progress, together with their associated estimated monthly values.
lack of cash during the operation even if it has a good ﬁnancial
The data were obtained from “D” Construction and Engineering
statement. In the viewpoint of corporate, cash ﬂow forecasts
Company in Korea. During the data collecting, adjustment of
should be made at all stages of the project from the planning stage
budget and contract amount including inﬂation was applied to
to the operation and maintenance stage of a project. However,
speciﬁc projects. Table 7 shows the actual data to achieve the
cash ﬂow forecasting and management are a dynamic process.
MAD for the speciﬁc case of simulation 1, which are estimated
Deviations of all projects at the corporate level may signiﬁcantly
by Eq. 9 after the ﬁrst month passes from the start of the project.
affect the ﬁrm’s ﬁnancial status. Moreover, inadequate cash ﬂow
forecasts to a certain project may drive a corporate into a crisis of
Table 9. Comparison of Mean Absolute Deviation MAD in Moving
Weight Method MWM and Fixed Weights Method FWM
Table 11. Reliability of Moving Weights Method Type 2 a
A / B
amount B b
B − A
aUnit 1,000 US dollars.
bContract amount means total earned values for 12 months.
JOURNAL OF MANAGEMENT IN ENGINEERING © ASCE / OCTOBER 2005 / 171
Considering the real business world in construction industry,
actual data; 2 developing cash ﬂow forecasts at the planning
various forecasting methods may be applied to cash ﬂow. Some
stage using the relationship between cumulative earned value and
judgment on a jobsite is needed in the case of forecasting cash
cost categories; and ﬁnally 3 implementing a system at the
ﬂow with respect to complexity and unexpected situations in con-
corporate level to monitor cash ﬂow in a proactive and timely
struction industry. However, if jobsite engineers or project man-
agers rely only on judgment based on their experience without the
use of any mathematical forecasting techniques, they may not
make a good decision to forecast cash ﬂow. Essentially, a good
forecasting technique needs to include both a historical trend-
based data supported method and competent judgments based on
Ahuja, H. N., and Walsh, M. A.. 1983 . Successful methods in cost
engineering, Wiley, New York.
construction experience and knowledge.
Ashley, D. B., and Teicholz, P. M. 1977 . “Pre-estimate cash ﬂow analy-
In this respect, the proposed model suggest a practical and
sis.” J. Constr. Div., Am. Soc. Civ. Eng., 103 3 , 369–379.
easy approach for jobsite engineers and project managers who are
Bennett, J., and Ormerod, R. N. 1984 . “Simulation applied to construc-
generally not familiar with ﬁnance knowledge of forecasting cash
tion projects.” Constr. Manage. Econom., 2, 225–263.
ﬂow using the regular reports. This model can be applied as part
Fondahl, J. W., and Bacarreza, R. R. 1972 . “Construction contract
of a project evaluation process and continuously updated to show
markup related to forecasted cash ﬂow.” Technical Rep. Prepared for
deviations between plan and actual data through changes or infor-
Construction Industry Institute, Stanford Univ., Stanford, Calif.
mation from the jobsite. In addition, the fast and simple forecast-
Gates, M., and Scarpa, A. 1979 . “Preliminary cumulative cash ﬂow
ing cash ﬂow allows ﬁeld engineers or project managers to sup-
analysis.” Cost Eng., 21 6 , 243–249.
port and to save time for decision making of strategy of cash
Hendrickson, C., and Au, T. 1989 . Project management for construc-
management to the corporation and projects.
tion: Fundamental concepts for owner, engineer, architects, and build-
ers, Prentice Hall, Englewood Cliffs, N.J.
Jepson, W. B. 1969 . “Financial control of construction and reducing the
element of risk.” Contact. J., April, 862–864.
Kaka, A. P. 1996 . “Towards more ﬂexible and accurate cash ﬂow.”
Constr. Manage. Econom., 14, 35–44.
A simple cash ﬂow forecasting model MWM was developed to
Kaka, A. P., and Price, A. D. F. 1991 . “Net cash ﬂow models: Are they
assist general contractors on jobsites during the construction
reliable?” Constr. Manage. Econom., 9, 291–308.
phase. The model was based on the general procedure of con-
Kenley, R., and Wilson, O. D. 1986 . “A construction project cash ﬂow
model—An idiographic approach.” Constr. Manage. Econom., 4,
struction jobsites and the nature of a general contractor’s budget.
The model included new methodology that was not addressed by
Kenley, R., and Wilson, O. D. 1989 . “A construction project net cash
previous researchers. A comparative case study methodology was
ﬂow model.” Constr. Manage. Econom., 7, 3–18.
chosen as a proper validation approach to evaluate the beneﬁts of
McCaffer, R. 1979 . “Cash ﬂow forecasting.” Quantity Surveying, Au-
the proposed model. Four real projects were identiﬁed as the case
study materials and the validity of the model was tested by actual
Meredith, J. R., and Mantel, S. J., Jr. 1995 . Project management—A
data from these projects in progress. The overall validation pro-
management approach, 3rd Ed., J Wiley, New York.
cedures were derived from a series of simulations by comparing
Navon, R. 1994 . “Company-level cash-ﬂow management.” J. Constr.
the results of the proposed model with other models suggested by
Eng. Manage., 122 1 , 22–29.
previous researchers. Ultimately, the cash ﬂow forecasting model
Navon, R. 1995 . “Resource-based model for automatic cash-ﬂow fore-
was demonstrated to be a simple, accurate, and reliable forecast-
casting.” Constr. Manage. Econom., 13, 501–510.
ing tool for general contractors at the construction stage in com-
Navon, R. 1997 . “Cash-ﬂow forecasting and management.” Proc., Con-
parison with FWM.
struction Congress, ASCE, New York, 1056–1063.
During the case studies, two issues were recognized as requir-
Oberlender, G. D. 2000 . Project management for engineering and con-
struction, 2nd Ed., McGraw–Hill, New York.
ing more research. The ﬁrst is that the model is dependent on the
Park, H. K. 2001 . “Cash ﬂow forecasting model using moving weights
planning of cost and earned value. If planning of cost and earned
of cost categories for general contractors on jobsite.” PhD disserta-
value are not accurate, the forecasted cash ﬂow would not be
tion, Univ. of Wisconsin, Madison, Wis.
accurate. The second issue is, similar to the ﬁrst, how to obtain
Peer, S. 1982 . “Application of cost-ﬂow forecasting models.” J. Constr.
reliable variables at the jobsite level such as the release of reten-
Div., Am. Soc. Civ. Eng., 108 2 , 226–232.
tion money—because it can be applied depending on the duration
Peterman, G. G. 1973 . “A way to forecast cash ﬂow.” World Constr.,
of a subcontract.
Despite several limitations, the proposed model presents a
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practical and easy approach for jobsite engineers and project man-
management system.” J. Constr. Div., Am. Soc. Civ. Eng., 102 4 ,
agers who are not familiar with extensive ﬁnancial knowledge,
Russell, J. S. 1991 . “Contractor failure: Analysis.” J. Perform. Constr.
just using regular reports without separate information at the job-
Facil., 5 2 , 163–180.
site. In addition, this model can be applied as part of a project
Sears, G. A. 1981 . “CPM/COST: An integrated approach.” J. Constr.
evaluation process considering internal interest capital cost at
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the corporate level. The model can be continuously updated to
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1992 . “Computer-based cash ﬂow
show deviations between planned and actual data through infor-
model.” Proc., 36th Annual Trans., AM. Assoc. of Cost Engineers,
mation changes from the jobsite. Encouraged by the results of
current research, future procedural research will concentrate on:
Trimble, E. G. 1982 . “Micro computers in construction management.”
1 analyzing the impact on difference between planned data and
Building Technology Management, 2 2 , 11–13.
172 / JOURNAL OF MANAGEMENT IN ENGINEERING © ASCE / OCTOBER 2005