Slide Presentation for undergraduate Research

1. KYAMBOGO UNIVERSITY
FOURTH-YEAR PROJECT REPORT
TOPIC:
CONSTRUCTION-RELATED REWORK AND ITS IMPACT ON
COST AND SCHEDULE: A CASE STUDY, KAMPALA CAPITAL
CITY AUTHORITY
BY
KALEMA SOLOMON WASAJJA
REG NO: 17/U/8331/ECE/PE
SUPERVISOR
ACHIRE MICHAEL WEST (GMUIPE)
JULY, 2022

2. SUMMARY OF THE PRESENTATION
• Introduction
• Statement of the problem
• Objectives
• Conceptual framework
• Methodology used
• Result and Discussion
• Conclusions and Recommendations

3. INTRODUCTION
Globally, in Ukraine’s construction industry, there is a trend of rework being
accepted as an integral part of construction activities (Trach et al, 2019).
On the African continent, studies have shown that all the elements of the building
had a direct bearing on an increase in the final cost of the project because of
rework (Oyewobi 2010).
In Uganda, Rework has been known to contribute to waste and value losses in
building design and construction (Kakitahi et al. 2013), and it has been considered
one of the key factors responsible for the cost and schedule overruns in
construction projects.

4. INTRODUCTION CONT….
Rework has been linked to waste and value loss in building design and construction
in Uganda (Kakitahi et al. 2013), and it has been identified as one of the primary
causes of cost and schedule overruns in building projects.
Alinaitwe (2014) also demonstrated that design omissions, poor workmanship, and
insufficient contractor supervision could be blamed for construction-related rework,
with consequences ranging from project schedule creep to client directives that
altered the scope of the task, coupled with client payment delays and site handover
delays.
The aim of this study, therefore, is to identify and evaluate the critical factors that
bring about rework and how it affects construction Cost and Schedule based on the
KIIDP2 project in KCCA.

5. Many economies rely heavily on the building industry. In Uganda, the sector accounts for more
than 12% of the country's GDP and has grown steadily over the years (Alinaitwe, 2021). The
sector has made significant strides in terms of capacity development and performance
enhancement (Joseph et al, 2018).
Despite its positive potential, the sector confronts significant barriers in failing to properly
transform investment opportunities into employment creation and national productivity
(Ntungire, 2018).One of the pertinent issues causing this is 'rework.’
It has an impact on time, cost, quality, and practically every other project success criterion
(Rezahoseini, et al, 2019). Rework is linked with higher expenses, while being responsible for
Schedule overruns and delays.
However, little is known about the history, causality and consequently, its impact on
Construction Schedule and Cost. Accordingly, the study attempted to undertake a
comprehensive assessment of past studies by various authors in order to evaluate the primary
consequences of rework on construction cost and schedule on the KIIDP2 project in KCCA
STATEMENT OF PROBLEM

6. OBJECTIVES OF THE STUDY
• General Objective
To investigate the impact of construction-related Rework on cost and schedule.
• Specific objectives
(i) To identify the causes of Rework on construction projects.
(ii) To ascertain the effects of Rework on construction cost and schedule.
(iii)To propose strategies on how to minimize the impact of Rework on Cost and
schedule

7. CONCEPTUAL FRAMEWORK
Conceptual framework; by the researcher

8. Research Approach
A mixed method paradigm (quantitative and qualitative research approaches) in
examining the impact of Rework on Construction Cost and Schedule was adopted.
Research Design
A descriptive design was used to collect current data and establish the relationship
between variables.
Study Area
The study was carried out within Kampala Capital City Authority located in central
Uganda.
Study Population
From a study population of 47 and using Morgan’s tables, a sample size of 42
respondents was considered.
METHODOLOGY SLIDES

9. Study tools
Questionnaires- this was the main tool for the study, arranged on a 5-Linkert scale.
Questionnaires were administered to all participants.
Interview Guides- semi-structured guides was prepared and administered to the
respondents.
Data Tools Quality
The tools were tested for:
Validity-using Face Validity and Content Validity tests
Reliability-using SPSS to test for Cronbach’s Alpha values
These tools were considered valid and reliable with 0.7+ score.
• DATA COLLECTION INSTRUMENTS

10. DATA PROCESSING AND ANALYSIS
QUANTITATIVE
Raw data was entered into SPSS ver. 23 for analysis. Descriptive and Inferential
statistics tests were done. Hypotheses testing, correlations and regressions were used
to ascertain the relationship between variables. Results are presented in tables,
figures, and descriptive statements.
QUALITATIVE
Data from interviews were edited into meaningful opinions from participants. These
were categorized into leading themes. Content analysis was done and results were
presented in statements

11. RESULTS AND DISCUSSION
Response Rate of respondents
Out of 42 questionnaires distributed to the respondents, 39 responded, giving a response rate of 92%.
Background Information of the Respondents
This information was necessary to guarantee that the study's sample was representative had a similar
distribution of respondents by attributes to the population from which it was selected.

12. Background of respondents Cont..
15 (38.5%) respondents had a Master's degree, 21 (53.8 %) held a Bachelor's degree, and 3 (7.7 %) held a Diploma. This demonstrates that
the majority of research participants were appropriately informed
30 (76.9 %) had worked for a period of 5 – 10 years, 6 (15.4 %) had worked for a period of (11-16 years), leaving 3 (7.7 %) had worked for
a time of fewer than 5 years.
This means that the majority of respondents have been working within the industry and on this project long enough to contribute
meaningful information to the research.

13. DISCUSSION OF RESULTS.
Validation of questionnaires
Cronbach's alpha with the help of SPSS was deployed to assess the questionnaire's reliability from
the following equation;
where C = the average inter-item covariance, v = the average variance and N = the number of items
The obtained Cronbach’s Alpha value of 0.964 shows an excellent level of internal consistency in the questionnaire.
Cronbach's Alpha
Cronbach's Alpha Based on
Standardized Items
Number of Items
0.964 0.965 33

14. Objective No.1 Analysis of the causes of Rework on construction sites;
The scores were assigned for each factor as perceived by the respondents and were used for statistical
analysis, the factors were examined and ranked in terms of their impact using the Relative Importance
Index. S/N Causes of Rework on Construction Sites RII Rank
1 Insufficient briefing 0.744 12
2 Inadequate understanding of the construction process 0.754 10
3 Inadequate funds for site investigations 0.744 12
4 Changes because of change in officials 0.646 21
5 Lack of funding allocated for consultation 0.738 14
6 Communication breakdown with design consultants (architects/engineers) 0.795 4
7 Payment of low fees for preparing contract documentation 0.641 22
8 Mistakes in contract documents 0.779 7
9 Items missing from the contract documents 0.826 2
10 Poor coordination of design 0.774 9
11 Inadequate skill sets for completing the specified assignment 0.718 18
12 Inadequate time to produce bidding documents 0.687 20
13 Tender being incomplete at the time of bidding 0.785 6
14 Insufficient client briefing to produce comprehensive contract document 0.723 17
15 Workers being given unclear instructions. 0.779 7
16 Specification non-compliance 0.841 1
17 Having few trained supervisors on site 0.795 4
18 Scarcity of trained labour 0.728 16
19 Inadequate trained labourers 0.708 19
20 Insufficient supervisor-to-foreman-to-tradesmen ratios 0.733 15
21 Faulty construction 0.805 3
22 Carelessness resulting into damage to other works 0.754 10
Where:
W - is the weight given
to each factor by the
respondents and
ranges from 0 to 39,
X is the largest weight
(i.e., 39 in this case)
and; N - is the total
number of people that
responded.

15. Objective No.2: Effect of rework on project cost and schedule.
Based on the values of numerous independent variables (causes of rework), multiple
regression was used to estimate the value of the dependent variable (cost and/or
schedule).
Multiple regression allows for the determination of the model's overall fit (variance
explained) as well as the proportionate contribution of each predictor to the project
cost and schedule.
From multiple regression analysis, an equation of the form below was obtained
(Hanson, 2002);
where 𝑦 is the project cost or project schedule variable, 𝛽0 + 𝛽1𝑥1 + 𝛽2𝑥2 + ⋯ +
𝛽𝑛𝑥𝑛 is the deterministic portion of the model; in this case 𝑥𝑛 the causes of cost and
schedule overruns and 𝛽𝑛 the beta values, and 𝜀 is the random error.

16. Table: Showing Model Summary on the significance of Rework on Cost
Table: Showing Model Summary for the significance of Rework on schedule
• Rework accounted for an 8.95% variance in the construction cost increase.
• Rework accounted for an 8.0% variance in the construction Schedule increase.
Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson
1 0.946a 0.0895 0.0857 6.96698 1.516
a. Predictors: (Constant), Carelessness resulting into damage to other works, Tender being incomplete at the time of bidding, Workers being given unclear
instructions., Having few trained supervisors on site, Communication breakdown with design consultants (architects/engineers), Inadequate time to produce
bidding documents, Faulty construction, Items missing from the contract documents, Specification non-compliance, Mistakes in contract documents
b. Dependent Variable: Percentage Increase in Project Cost
Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson
1 0.900a 0.0809 0.0741 9.18350 1.966
a. Predictors: (Constant), Carelessness resulting into damage to other works, Tender being incomplete at the time of bidding, Workers being given unclear
instructions., Having few trained supervisors on site, Communication breakdown with design consultants (architects/engineers), Inadequate time to produce
bidding documents, Faulty construction, Items missing from the contract documents, Specification non-compliance, Mistakes in contract documents
b. Dependent Variable: Percentage Increase in project Schedule

17. Statistical Significance
The tables below show the ANOVA table from the regression analysis. The F-ratio was used to test whether the overall
regression model was a good fit for the data. The table shows that the causes of rework are statistically significant in
predicting the overall increase in project cost, F(10, 28) = 23.847, p < 0.001, and overall increase in the project schedule,
F(10, 28) = 11.881, p < 0.001 indicating that the regression model was a good fit for the data.
Table: Regression Model Fit for percentage cost increase with rework Table: Regression Model Fit for percentage Schedule increase with rework
ANOVAa
Model
Sum of
Squares
df
Mean
Square
F Sig.
1
Regression 11579.939 10 1157.994 23.857 0.000b
Residual 1359.086 28 48.539
Total 12939.025 38
a. Dependent Variable: Percentage Increase in Project Cost
b. Predictors: (Constant), Carelessness resulting into damage to other works, Tender being
incomplete at the time of bidding, Workers being given unclear instructions, Having few
trained supervisors on site, Communication breakdown with design consultants
(architects/engineers), Inadequate time to produce bidding documents, Faulty construction,
Items missing from the contract documents, Specification non-compliance, Mistakes in
contract documents.
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 10020.267 10 1002.027 11.881 0.000b
Residual 2361.425 28 84.337
Total 12381.692 38
a. Dependent Variable: Percentage Increase in project time
b. Predictors: (Constant), Carelessness resulting into damage to other works, Tender being
incomplete at the time of bidding, Workers being given unclear instructions., Having few
trained supervisors on site, Communication breakdown with design consultants
(architects/engineers), Inadequate time to produce bidding documents, Faulty construction,
Items missing from the contract documents, Specification non-compliance, Mistakes in contract
documents.

18. Objective 3: Strategies to minimize Rework on cost and schedule
The Relative Importance Index (RII) was calculated and the identified causes were ranked as per the responses in the
table below. The most notable solutions were identified to be;
S/N Measures taken to reduce rework on Cost and schedule RII Rank
1 Using sufficient and capable human resource 0.882 2
2 Sufficient supervision 0.887 1
3
Developing effective communication between project
participants
0.872 3
4
Continuous monitoring before and throughout work
implementation of work
0.867 4
5 Involving the client 0.815 8
6 Using effective planning and scheduling 0.867 4
7 Using qualified suppliers 0.764 11
8 Tracking and documenting rework incidents 0.810 10
9 Identifying the root cause of rework in detail 0.826 6
10 Developing options and actions to reduce reworking 0.821 7
11 Quantifying the cost and time effect of rework on project delivery 0.815 8
Where:
W - is the weight given to
each factor by the
respondents and ranges
from 0 to 39,
X is the largest weight
(i.e., 39 in this case) and;
N - is the total number of
people that responded.

19. The study also elicited independent suggestions from the respondents on how to mitigate the
cost and schedule impact of rework and these are as below.
➢Developing work programmes
➢getting an in-depth cause and solutions to the problem other than basing on assumptions
➢Proper Project conceptualization and adequate planning
➢Public projects should actively engage the stakeholders at the planning stage
➢Investing in Quality Control and Quality Assurance
➢Ensuring that work is done as per specifications, and drawings and also maintaining quality.
➢Proper planning of works
➢Adherence to documentation and permissions
➢Incorporating value engineering into all kinds of construction projects

20. CONCLUSIONS AND RECOMMENDATIONS
Conclusions
Close attention should be given to Contractor related rework causes as they were seen to be the heaviest
contributor to the negative effects.
There is a need for prior knowledge of rework during construction can help projects save money and time.
KCCA should know that the costs for building projects end up becoming very high because of the
complexities resulting from Rework.
Various methods can be deployed to help reduce the negative impacts of Rework on construction projects
and all project participants should be aware of these and know how to utilise them.
Recommendations
The project team should always have strategies for detecting Rework and be able to put in place mitigation
measures to mitigate rework.
Parties responsible for rework should bear the cost. This prevents unnecessary costs for the client and keeps
everyone on top of their game.
There is a need to allocate more supervisory resources like a “clerk of works” on projects to closely monitor
the implementation of the project.

21. REFERENCES
Trach, R., & Pawluk, K. (2019). CAUSES OF REWORK IN CONSTRUCTION PROJECTS IN UKRAINE. Pan
Polska, 63.
Kakitahi, Alinaitwe (2016) Impact of construction-related rework on selected Ugandan public projects, Journal of
Engineering Design and Technology.
Alinaitwe, H. (2014). A COMPARISON OF CONSTRUCTION-RELATED REWORK IN UGANDAAND
MOZAMBIQUE. Journal of Construction Project Management and Innovation, 775-776.
Ntungire, E. C. (2018, December). Construction and public procurement in Uganda. Boston: United Nations
University.
Rezahoseini, A., Noori, S., & Ghannadpour, S. F. (2019). Reducing rework and increasing the quality of the civil
project, through Total Quality Management (TQM), by using the concept of Building Information Modelling
(BIM). Journal of Industrial and Systems Engineering, 3.
Joseph Stables, G. O. (2018, November 18). Uganda Construction Capacity Preliminary Assessment: Key Findings
and Recommendations. Infrastructure for Cities and Economic Development, p.6.

22. END