Determining the cost of poor
quality and its impact on
productivity and profitability
University of Engineering and Technology, Taxila, Pakistan
Syed M. Ahmed and Kamalesh Panthi
Department of Construction Management, East Carolina University, Greenville,
North Carolina, USA, and
Nadeem Ishaque Kureshi
Center of Advance studies in Engineering, Islamabad, Pakistan
Purpose – The purpose of this paper is to examine how effectively the cost appraisal system
proposed measures the cost of poor quality (COPQ) in a construction project. The paper first
formulates how COPQ can be measured and later clarifies the relationship between COPQ, labor
productivity, and profitability.
Design/methodology/approach – In order to measure COPQ, the researchers prepared data entry
forms for recording COPQ items on a daily basis and formulated the cost contribution of lost material,
lost man-hours, lost machinery hours, and lost overhead on the overall COPQ for the project. The
proposed method was then applied in a case study.
Findings – The results showed that, for the 60-days study period, COPQ decreased by about
24 percent while labor productivity and profitability increased by about 17 and 11 percent,
respectively, after the implementation of COPQ measuring system. This study further supports the use
of the COPQ system in construction projects as a mechanism to facilitate continuous improvement.
Originality/value – COPQ is a major cost that is often ignored in construction projects due to the
difficulty of measuring it. This paper presents a COPQ measuring and recording system capable of
identifying COPQ. The implementation of the system is shown to increase productivity and
profitability as demonstrated by the project used for the case study.
Keywords Project management, Productivity, Labor productivity, Construction industry,
Profitability, Cost of poor quality, Construction project
Paper type Technical paper
A construction project is a one-time activity with a specified time period, budget and
defined scope. A project, irrespective of its size or magnitude, must be completed
under three constraints -cost, time, and scope. These constraints are often referred to
as the “Triple Constraints of Project Management” (Deming, 1982; PMBOK, 2008).
Completing construction projects within these specified triple constraints, while
maintaining quality, is a big challenge for project managers.
The cost of poor quality (COPQ) cannot be traced or identified using the existing
accounting reports and auditing system (Barbar
aet al., 2008; Evans and Lindsay, 2005;
Retnari et al., 2010). Rao et al. (2010) state that putting a cost figure on quality is a
difficult job and accounting is unable to capture the “true” cost of quality (COQ).
The top level management is mainly concerned with the overall cost. On the
other hand, mid-level managers work with both frontline workers and top level
managers, making both the management of workers and costs responsibilities placed
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on mid-level managers. Thus, COPQ remains hidden, unable to be extracted using the
traditional accounting system. This all means that the extent of adverse effect
attributable to COPQ is not realized entirely by many project managers.
COPQ quantifies and translates failure incidents into dollar terms, which are better
understood by upper management. The existing accounting systems are unable to
measure and record COPQ, leaving it a hidden cost for construction projects. COPQ
cannot be controlled until it is identified and measured.
The main purpose of this research is to determine the effectiveness of the COPQ
measuring system as it pertains to the reduction of internal failure costs and the
subsequent effect on productivity and profitability.
The objectives of the research are to:
(1) develop a method to measure the COPQ;
(2) apply the method on a construction project; and
(3) determine how effective such a method is at reducing internal failure costs.
2. Literature review
According to Harrington (1987), in the early 1950s, Feigenbaum developed a dollar-based
reporting system called “quality cost” while working for General Electric. Campanella
(1990) and Rao et al. (2010) state that it was Juran who gave rise to the concept of quality
costs in his first Quality Control Handbook, wherein he tells his famous analogy of “gold
in a mine.” Still, Barbar
aet al. (2008), and Evans and Lindsay (2005) contend that the
concept of “COQ” and “cost of non-quality” was developed by Frank Gryna in the 1950s,
with the objective of presenting to top executives the language of quality translated into
monetary value. However, it is largely accepted that the traditional COQ concept was
developed by W.J. Masser in his 1957 article, “The quality manager and quality costs,”
when he subdivided the quality costs into prevention, appraisal, and failure. Lending
further validity to the COQ concept, the American Society of Quality Control formed the
Quality Cost Committee in 1961 to make the business community aware of quality costs
so that businesses might improve their quality through the measurement of quality
costs (Campanella, 1990). Two years later, the US Department of Defense adopted the
quality cost program in 1963. Finally, Feigenbaum (1977) further developed the COQ
model in his classic book To ta l Qu a l it y Co nt r ol .
COQ is usually understood as the sum of conformance and non-conformance costs,
where cost of conformance is the price paid for prevention of poor quality (e.g. inspection
and quality appraisal) and cost of non-conformance is the COPQ caused by product and
service failure (e.g. rework and returns) (Schiffauerova and Thomson, 2006). Juran (1951)
has suggested that the COQ can be understood in terms of the economics of the
end-product quality or in terms of the economics of the conformance to standards.
In his book, Quality is Free, Crosby (1979) defined the COQ as having two main
components: the cost of good quality (or the cost of conformance – prevention and
appraisal costs) and the COPQ (or the cost of non-conformance – internal and external
failure costs). Furthermore, Crosby (1983/1987) stated that no subject has received
more attention from quality professionals over the past years than COQ.
Retnari et al. (2010) contend that working out the COQ in monetary terms allows an
organization to evaluate the extent to which its resources are being used in order to
cost of poor
mitigate the adverse effects of poor processes. Such information can help an organization
determine the potential savings that can be gained by improving its processes. From the
management accounting perspective, economic issues are predominant. As Dobbins and
Brown (1991) puts it, “The true language of management is accounting, and money is
only the accent.”
COQ analysis enables organizations to identify measures and control the
consequences of poor quality. The major goal of a COQ approach is to improve the
bottom-line by eliminating poor quality (Mohandas and Raman, 2008). Quality costs
are not able to be obtained with a basic mathematical function, but instead are
dependent on the support processes, like maintenance and human resources, which are
also major contributors to the total COPQ. The major quality costs are exacerbated by
incapable support processes. COQ, after its recognition, can be reduced through
structural approaches (Retnari et al., 2010).
COPQ is the cost associated with providing poor quality products or services, due to
failure to conform to the quality standards of customer requirements. Harrington
(1987) defines COPQ as all the costs incurred by the company and the customer
because the output did not meet specifications and/or customer expectations. Crosby
(1979) states that “Quality is free; it’s not a gift, but it is free. What costs money are the
un-quality things – all the actions that involve not doing jobs right the first time.”
According to Raddatz and Klemme (2006) failure costs are incurred when it becomes
necessary to rectify the variation/defects that crop up after execution of a job or rework
of an unsatisfactory job in order to achieve the required specifications. This cost can be
divided into internal and external failure costs.
2.3 Internal failure costs
Internal failure costs are those costs associated with product failure before its delivery to
the external customer. They include the net cost of scrap, spoilage, rework, material
wastage, labor wastage, overheads associated with production, failure analysis, supplier
rework, scrap, re-inspection, retest, down time due to quality problem, opportunity cost,
or other product downgrades (Harrington, 1987; Pyzdek, 2003; Rao et al.,2010).
2.4 External failure costs
External failure costs crop up after delivery of the project to the customer within the
warranty or “defects liability period.” Examples include deterioration of executed
work, complaints of malfunctioning devices, complaints associated with repair, and
replacement of non-conforming defective parts. Warranty charges, customer complaint
adjustments, returned merchandize, product recalls, allowances, and product liability
costs are also external failure costs. Furthermore external failure costs include direct
and indirect costs such as labor, travel associated with the investigation of customer
complaints, inspection of warranty, field-tests, and repairs (Harrington, 1987; Pyzdek,
2003; Rao et al., 2010).
2.5 The hidden factory
Campanella (1990) states that accounting systems were never designed to demonstrate
the impact of the quality of performance on overall operating costs. That is why many
of these costs have remained hidden for so long. Feigenbaum (1977) pointed out that,
“a certain ‘hidden’ and non-productive plant exists to rework and repair defects and
returns, and if quality is improved, this hidden plant would be available for increased
The hidden losses on account of COPQ estimated by various researchers are
summarized in Table I.
The population mean of 27.53 percent with a standard deviation of 6.46, as shown in
Table I, is a very high cost of failure; it is more than a quarter of a project amount.
According to Campanella (1990), total qualitycosts can be reduced to 2-4 percent of sales.
Crosby (1990) contends that it should not be more than 4-5 percent of the total project.
Morse and Poston (1987) state that quality costs can be reduced to 2.5 percent of sales.
Therefore, there is a big opportunity for cost reduction on account of COPQ.
2.6 Measurement of COQ
According to Deming (1982), the objective of “never ending improvement” in total quality
management (TQM) cannot be achieved without measurement. Speirs and Nash (1995)
contends that a business is not under control if measurements are not carried out, and
there is no basis on which to implement improvement. Osman and Abdel-Razek (1996)
have contended that “you won’t be able to manage what you cannot measure.” It is the
measurement which triggers the improvement processes. Rao et al. (2010) contend that
the COQ is at best an educated estimate of the cost and not a precise measure. However,
Deming (1982) stated that cost analysis for quality is not effective and that measuring
quality costs to seek optimum defect levels is evidence of a failure to understand the
problem. Quality costs need to be measured, not only for management control, but also
for the development of quality thinking within the organization.
According to Rao et al. (2010) many critics of the concept of measuring COQ
are concerned that hidden costs associated with external failure are not reported.
Low High Mean
Researchers 10 40 25
aet al. (2008) 33.33 33.33 33.33
Juran (1989) 20 40 30
Evans and Lindsay (2005) 20 30 25
Harry et al. 20 35 27.5
Crosby (1984) 25 25 25
Atkinson et al. (1991) 20 25 22.5
Raab (1987) 40 40 40
Harrington (1987) 10 20 15
Morse and Poston (1987) 24 40 32
Singhal (2006) 38 38 38
Moyer and Gilmore (1979) 30 30 30
Wheelright and Hayes (1985) 10 30 20
Berry and Parasuraman (1992) 5 25 15
Dale and Oakland (1994) 20 20 20
Besterfield (1998) 5 25 15
Williams et al. (1999) 5 30 17.5
Giakatis et al. (2001) 30 30 30
Superville et al. (2003) 5 25 15
Kent (2005) 2.5 5 3.75
Rodchua (2006) 22.23 32.83 27.53
Tabl e I.
according to various
cost of poor
Lost opportunities, customer dissatisfaction, and negative customer referrals are
certainly costs relating to poor quality. A customer also has to pay higher maintenance
costs due to premature failure of products delivered by the contractor. External failures
not only cause inconvenience and mental stress but also a loss of time and money.
External failure cost can be very high; it can even be more than the cost of the original
project (Shahid and Sajid, 2010).
The measurement of COQ quantifies the problem in a language understood by
upper level management, and it helps to identify major opportunities for cost reduction
and customer satisfaction (Raddatz and Klemme, 2006).
3. Research methodology
3.1 Research instrument
The methodology is based on calculating the cost incurred in a construction project
because of poor quality. The COPQ is comprised of the cost of all the losses that are a
result of unutilized equipment and labor time, lost material due to rework, and lost
days in overhead for activities in the critical path. The following mathematical
equation has been proposed for assessment of COPQ for all losses during construction:
COPQ ¼XRMT MQ þXRMH MHQ þXRMC MCQ þXRT TQ ð1Þ
RMT is the unit rate of material, MQ the quantity of lost material, RMH the rate of man
hours, MHQ the quantity of lost man hours, RMC the rate for machinery hours, MCQ
the quantity of lost machinery hours, RT the rates of overheads per day, and TQ the
number of days lost in any activity on critical path.
Data entry forms for measuring COPQ were developed based on the information
available in literature, including unstructured interviews with management accountants,
project managers, and cost accountants. It comprises of data entry forms created in Excel
spread sheet to enter the COPQ data on a daily basis and construct summarized reports.
4.1 Project description
The project used for the case study was a bridge on a storm water stream being
constructed as a public sector project in Pakistan at a budgeted cost of 600,000 US
dollars. The project commenced in May 2011 with a planned completion schedule of
four months. The scope of project included diversion of the rain water stream,
excavation for the foundation, securing the raft foundation, erecting abutment walls,
pre-stressed concrete girders, placing deck slabs, installing concrete railings, earth
filling along the approaches to the bridge, and construction of an approach road.
4.2 Data collection
Researchers identified and evaluated losses on account of internal failure costs or
COPQ, which were recorded by project professionals and reported to project
management for initiation of corrective actions. The purpose was to identify cost
centers for opportunities of improvement, in order to ensure optimum utilization of
resources and prevent losses on account of COPQ. The data entry forms for measuring
COPQ were distributed to site staff working at various activities to record the losses on
a daily basis. Training was given to the site and office staff for entering the data before
starting data collection. Four independent variables machinery, labor, material, and
project overheads, were assessed with “Total COPQ” being the dependent variable. The
components were recorded for machinery, labor and material being used at the project
and their cost was estimated on the basis of respective unit rates, whereas, the fixed
monthly cost of management was considered as project overheads and the time delay
(number of days) in completion of critical activity was assessed in monetary terms as
loss. The COPQ was recorded continuously for 60 days in the months of May and June
2011. Excel spread sheets were used to compile the COPQ data and construct
summarized reports. Separate sheets were used to enter cost data with the respective
dates and references for each cost category.
4.3 Data analysis
The 60 days study period was divided into four quarters consisting of 15 days each in
which the first quarter was considered to be benchmark period. The benchmark was
established with a summary report of the first 15 days. Measurements and results from
the benchmark period were not communicated to the project management. The
management were apprised of the recorded COPQ during the second 15 days on a
weekly basis. The data from the four quarters was analyzed using Excel and SPSS
software to compute mean, standard deviation, and variance. The software packages
were also used for plotting time series graphs, doing trend analyses, creating pie
charts, and correlation analysis to check whether the COPQ measurement system was
successful in reducing the COPQ in the case study.
The monsoon season started early in the first week of June which not only disrupted
the work but also damaged some of the completed work. Scarcity of allocated funds
was also a constraint. “Availability of required funds for the project” has been assessed
to be the most important success factor by Shahid et al. (2012). The COPQ data from
the study period of four quarters (15 days each) were analyzed and discussions are
presented in the ensuing sections.
4.5 The benchmark
The internal failure costs recorded for machinery, labor, overheads, and material in the
first quarter is considered as the benchmark for comparison with other time periods.
The measurements are plotted and shown in Figure 1 for the first 15 days, whereas the
COPQ measurement data of all 60 days is presented in a tabular format in Appendix 1.
It can be observed from Figure 1 that COPQ started reducing, even before
the management was apprised of the results, during the benchmark period. The
improvement in quality can be attributed to the realization by the workers of their
weaknesses, while measuring COPQ during the benchmark period. The COPQ of all
the study periods can be seen in Appendix 2.
It can be seen from Table II and Appendix 2 that there is a considerable loss,
averaging $2009 per day, on account of COPQ. There is a significant variation and
spread in mean, mode, and median, as well as the observed high and low values. The
mean values of the benchmark were compared with the mean values of the three
subsequent quarters studied. The overall losses on account of COPQ as percentage of
work value are 40.43 percent with a standard deviation of 23.92, much more than the
population mean of 27.53 percent with a standard deviation of 6.46 as identified in the
It can be observed from Figure 2 that the main contributor to COPQ is machinery
followed by labor, material, and overheads. The increase in overhead cost, due to delay
in completion of critical activities, is a big and often ignored problem.
cost of poor
The COPQ measured after the benchmark period, in the form of summary report, was
shared with the project management on a weekly basis for the duration of the study.
Problematic areas indicated by high COPQ alerted the management to take prompt
corrective action. For example, whenever an equipment was sitting idle, COPQ on the
account of machinery would be giving high values. This would then prompt corrective
Cost of Poor Quality
01 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Machinery labor Overheads Material Ave. Total COPQ
Cost of poor quality
recorded in the
Total cost of poor quality in the benchmark period USD 30,138
Value of work done during the benchmark period USD 74,538
COPQ as percentage of value of work executed 40.43%
Benchmark of losses
on account of COPQ
as a percentage of value
of executed work
of components of
action from the management after finding the reason for the contributing COPQ
factors. Setting priorities and initiating corrective actions to control the losses on
account of COPQ were the goals that were hoped to be obtained by the sharing the
COPQ data with project management. Wastages and losses started to reduce with
the identification of problem areas and monetary emphasis being placed on internal
failure incidents. The improvement observed in reduction of losses in the three study
quarters, in comparison to benchmark period, is shown in Figure 3.
COPQ has reduced through each successive quarter with the improvement in
quality. The mean Total COPQ reduced from $2009 per day to $1,054 per day,
constituting a very significant reduction of 47.53 percent. Compared to the benchmark,
machinery losses reduced by 48.14 percent, labor along with overheads reduced by
50 percent and material had a reduction of 38.75 percent in the fourth quarter.
A decline in COPQ can be seen, even in the benchmark period. The COPQ continued
to reduce in subsequent quarters, with a noticeable downward trend. There are
comparatively less spikes and smaller spikes in the last quarter, which indicates that
the system is stabilizing and moving toward a normal distribution curve.
4.6 Trend analysis
Equations of the trend lines shown in Figure 4 are represented as shown below:
Benchmark period COPQ ¼2;216 25:85 No:of days
2nd Fortnight COPQ ¼1;984 39:11 No:of days
3rd Fortnight COPQ ¼2;080 71:92 No:of days
4th Fortnight COPQ ¼1;278 27:95 No:of days
A low intercept, which represents the loss constantly being faced by the project due to
COPQ, is desirable. It is evident from the above equations that the intercept has
reduced considerably over the four quarters. It reduced by 10.04 percent in the second
quarter but increased by 4.83 percent in the third quarter and again reduced by
38.55 percent in the last quarter in route to a total reduction of 42 percent. The trend
Cost of Poor Quality
in US Dollars
0Machinery Labor Overheads Material Ave. Total
1,160 398 200 252 2,009
1,021 308 150 192 1,671
895 273 125 212 1,504
3rd Quarter 198 100 154 1,054
Comparison of mean
values of COPQ in
four quarters of the
cost of poor
line gradient is negative for all variables with the greatest gradient of the trend line
being found in the third quarter, followed by the second quarter, then the benchmark,
and finally the last quarter. Therefore, it can be predicted that the COPQ will continue
to reduce when the COPQ identification and measurement system is in place.
It can be observed from analysis of the COPQ data recorded for the four quarters
(Appendix 2) that the average values of all four independent variables, and one
dependent variable, have dropped continuously through each successive quarter.
The spread of all the variables has also reduced considerably in the third quarter, when
compared to the benchmark. The standard deviation and the mean have both reduced
as well. Also, the mode and the median have become more similar. These results
taken together signify that the system has moved toward a normal distribution after
the implementation of the quality program.
According to the results shown in Table III, there is a considerable reduction of
about 39 to 50 percent in losses for all the independent variables, and there is about a
48 percent reduction in the losses of the dependent variable (Total COPQ). The
percentage of Total COPQ to Work value has also been brought down from 40.43 to
16.65 percent with an improvement of about 59 percent.
As observed in Figure 5, there is a consistent reduction in the losses on account of
COPQ, to the value of work executed. There is a significant gain in value of work
COPQ (US Dollars)
Number of Days 15
Linear (Bench Mark)
Linear (1st Quarter)
Linear (2nd Quarter)
Linear (3rd Quarter)
Scatter plot of daily
total COPQ recorded
in four quarters
Cost in US Dollars
COPQ components Benchmark 4th quarter % reduction
Machinery 17,400 9,025 48.13
Labor 5,962.5 2,975 50.10
Overheads 3,000 1,500 50.00
Material 3,775 2,312.5 38.74
Total COPQ 30,138 15,813 47.53
% of work value 40.43 16.65 58.82
Details of reduction
achieved in COPQ at
the end of 60 days
executed at the end of the 60 days study period. The losses have been reduced from
40.43 to 16.65 percent with a standard deviation of 19.62 percentage points. The COPQ
percentage losses are much less than the population mean of 27.53 percent as identified
in the literature review.
4.7 Relationship between Total COPQ, labor productivity, and profitability
As evident from Table IV, labor productivity continued to improve in every quarter,
coinciding with the reduction of COPQ. The overall improvement in labor productivity
is 16.88 percent. Expenditure on labor also declined in successive quarters due to
Likewise, profitability continuously increased in the study period of 60 days, as seen
in Table V. The input expenditure was also reduced due to reduction in losses on
account of COPQ. The overall improvement in profitability is 10.45 percent, which is a
From Figure 6, it is observed that Total COPQ has a very high intercept value of
48.66 percent, when a lower value would be better. High intercept values are required
0% Bench Mark 2nd QTR
Different Time Periods
% of Total COPQ to Value
of Work Done
3rd QTR 4th QTR
Reduction in total
COPQ as a percentage
of work executed
Cost in US Dollars
1 Benchmark 20,647 74,538 27.70 361
2 2nd quarter 20,297 75,734 26.80 373 3.36
3 3rd quarter 21,329 86,003 24.80 403 8.06
4 4th quarter 22,512 94,988 23.70 422 4.64
Tabl e IV.
Cost in US Dollars
% of input
1 Benchmark 65,369 74,538 87.70 13,427 114
2 2nd quarter 64,071 75,734 84.60 17,106 118 3.66
3 3rd quarter 71,038 86,003 82.60 22,073 121 2.42
4 4th quarter 75,421 94,988 79.40 28,878 126 4.03
Tabl e V.
cost of poor
Coefficient of Correlation
All 3 Quarters
0.34 0.30 0.71 0.37 0.58 –0.29 0.19 0.38 0.33 0.63
0.33 0.95 0.37 0.33 0.41 0.51 0.12 0.41 –0.17
for the labor productivity and profitability, which are 336.6 and 110.15 percent,
respectively. Total COPQ has a negative slope of 7.82 percent for its trend line, which
means that it is decreasing with every quarter. Labor productivity and profitability
both have positive gradients in their trend lines, 21.29 and 3.86 percent, respectively.
A consistent, gradual, and linear improvement in the performance can be observed
from the trend lines shown in Figure 6.
COPQ started reducing right from the Benchmark period. This could be explained
using the concept of Hawthorn Effect. Hawthorn Effect states that because the workers
knew that they were being studied, they made fewer mistakes. The percentage of
COPQ to the executed work value reduced from 40.43 to 16.65 percent in the 60 days
study period. The mean total COPQ of 16.65 percent, achieved at the end of the study
period, is much less than the population mean of 27.53 percent as investigated in the
literature review section. Therefore, there is a significant improvement in the reduction
of project losses.
Analysis of the four quarters also shows a consistent trend of reduction of COPQ in
each successive quarter, for each of the variable studied. It has also been observed that
in the study period of 60 days the labor productivity improved by 16.88 percent and
profitability increased by 10.45 percent.
The COPQ measurement and recording system successfully achieved its objective
of reducing losses on account of COPQ in an experimental study of a construction
project. It has been established that internal failure incidents translated to monetary or
dollar terms draw the attention of management, thereby leading to corrective action.
Timely corrective actions and better management not only reduced overall losses on
account of COPQ, but also improved the labor productivity and profitability of the
company. The measurement and recording system of COPQ also identified the cost
centers and problem areas while pointing out the employees responsible for the poor
quality. With this accountability system, workers became more vigilant and careful to
conserve resources. This study has validated the COPQ measuring system and the
methodology adopted, therefore it can be used for other construction projects with
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(The Appendix follows overleaf.)
cost of poor
Number of days of study period
15 days study
periods Head of account 123456789101112131415
1 1 to 15 days
Machinery 1,362.5 1,262.5 1,250 1,225 1,087.5 1,000 1,025 1,050 1,300 1,250 1,137.5 1,187.5 1,087.5 1,125 1,050
Labor 687.5 500 462.5 400 437.5 387.5 337.5 375 350 350 325 325 337.5 350 337.5
Material 325 337.5 287.5 225 212.5 250 287.5 275 262.5 262.5 225 175 137.5 137.5 375
Ave. Total COPQ 2,375 2,100 2,000 1,850 2,112.5 1,637.5 2,400 2,075 2,287.5 1,862.5 2,437.5 2,062.5 1,562.5 1,612.5 1,762.5
Machinery 987.5 1,100 1,137.5 1,100 1,062.5 1,037.5 1,062.5 1,100 937.5 900 987.5 1,000 950 950 1,000
Labor 350 337.5 325 337.5 312.5 312.5 275 312.5 312.5 287.5 275 262.5 312.5 312.5 300
Overheads 0 0 375 0 750 750 0 375 0000000
Material 250 237.5 287.5 200 162.5 150 187.5 187.5 175 150 162.5 225 187.5 162.5 150
Ave. Total COPQ 1,587.5 1,675 2,125 1,637.5 2,287.5 2,250 1,525 1,975 1,425 1,337.5 1,425 1,487.5 1,450 1,425 1,450
Machinery 1,062.5 1,075 1,200 1,000 900 1,087.5 875 812.5 912.5 825 875 775 687.5 687.5 650
Labor 312.5 325 350 375 300 275 225 250 300 250 262.5 237.5 225 187.5 212.5
Overheads 375 0 750 375 0000375000000
Material 187.5 225 200 250 187.5 212.5 250 200 250 237.5 225 262.5 212.5 150 125
Ave. Total COPQ 1,937.5 1,625 2,500 2,000 1,387.5 1,575 1,350 1,262.5 1,837.5 1,312.5 1,362.5 1,275 1,125 1,025 987.5
Machinery 737.5 850 775 675 637.5 587.5 637.5 537.5 500 562.5 500 475 525 462.5 562.5
Labor 200 250 237.5 225 200 200 187.5 200 200 187.5 175 175 200 175 162.5
Overheads 0 375 0000375375000000375
Material 162.5 187.5 162.5 150 137.5 150 162.5 137.5 175 137.5 162.5 150 175 137.5 125
Ave. Total COPQ 1,100 1,662.5 1,175 1,050 975 937.5 1,362.5 1,250 875 887.5 837.5 800 900 775 1,225
Note: Cost in USD
Data set of COPQ
recorded on one project
in 60 days
Dr Kamalesh Panthi can be contacted at: email@example.com
Total Highest Lowest SD Mean Mode Median
Bench mark 17,400 1,362.5 1,000 111.02 1,160 1,250 1,137.5
1st quarter 15,312.5 1,137.5 900 71.13 1,020.83 1,100 1,000
2nd quarter 13,425 1,200 650 163.65 895.00 875 875
3rd quarter 9,025 850 462.5 115.71 601.67 637.5 562.5
Bench mark 477 55 26 7.68 31.80 27 28
1st quarter 370 28 21 1.99 24.67 25 25
2nd quarter 327 30 15 4.28 21.80 24 21
3rd quarter 238 20 13 1.92 15.87 16 16
Bench mark 240 60 0 22.30 16.00 0 0
1st quarter 180 60 0 22.68 12.86 0 0
2nd quarter 150 60 0 18.52 10.00 0 0
3rd quarter 120 30 0 13.73 8.00 0 0
Bench mark 302 30 11 5.51 20.13 23 20
1st quarter 230 23 12 3.31 15.33 13 15
2nd quarter 254 21 10 3.08 16.93 20 17
3rd quarter 185 15 10 1.40 12.33 13 12
Ave. Total COPQ
Bench mark 2,411 200 125 23.92 160.73 168 166
1st quarter 2,005 183 107 25.90 133.67 114 122
2nd quarter 1,805 200 79 33.13 120.33 #n/a 109
3rd quarter 1,265 133 62 19.62 84.33 #n/a 78
Note: Cost in US Dollars
Statistic of the
five variables for the
four study periods
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cost of poor