1.
0 Introduction
(1.5 pages, with in-text APA 7th edition citations)
Cost estimation plays a central role in construction economics and project management. It
involves forecasting the costs associated with materials, labor, plant, overheads, and risk,
typically at various project stages. Quantity surveyors and construction managers rely on cost
estimates to make informed decisions, control budgets, and negotiate contracts. Accuracy and
timeliness in these estimates determine the financial success of most projects (Ashworth &
Perera, 2018).
Historically, cost estimation was a manual, paper-based process that required extensive
calculations, documentation, and duplication. Errors and delays were frequent, especially on
large or complex projects. This often led to budget overruns and project disputes. Over the past
two decades, the increasing use of digital tools has transformed how estimates are produced. The
adoption of software has accelerated estimation speed and improved overall productivity for cost
professionals (Sanni & Hashim, 2017).
Today, specialized estimation software provides automation, integration with design models,
access to current market data, and templates for recurring tasks. These tools shorten the time
required to produce bills of quantities and pricing documents. They also minimize human error,
encourage transparency, and enable faster decision-making (Olatunji, 2011). In developing
economies such as Nigeria, where construction growth is tied to infrastructure demand, the
impact of estimation software is significant. Speed and productivity gains translate to better
resource management and reduced project delays.
The demand for faster project delivery, more competitive bidding, and increasing complexity of
building systems has made software adoption a necessity rather than a preference. Professionals
are shifting from general-purpose spreadsheets to dedicated software such as CostX, Candy, and
BIM-based solutions. These platforms integrate design, scheduling, and cost data, helping
estimators work efficiently under tight deadlines (Perera et al., 2020).
This seminar aims to explore in detail how software tools impact speed and productivity in cost
estimation. The analysis will define key concepts, review types of software in use, assess their
effect on time and output, and examine real-world adoption challenges. It will also propose
strategies to maximize these tools and review future trends including artificial intelligence and
automation in quantity surveying practice.
Through this discussion, the paper will demonstrate that software-based cost estimation is not
only faster but also more productive in the long term. This improvement is shaping the future
role of the quantity surveyor as a digital construction professional.
References
Ashworth, A., & Perera, S. (2018). Cost studies of buildings (6th ed.). Routledge.
Olatunji, O. A. (2011). The impact of BIM on construction projects in the UK. Journal of Civil
Engineering and Management, 17(1), 107–115. https://doi.org/10.3846/13923730.2011.555471
Perera, S., Nanayakkara, S., & Rodrigo, M. N. N. (2020). Adoption of cost estimation software
in construction: A review of critical success factors. Journal of Financial Management of
Property and Construction, 25(3), 309–328. https://doi.org/10.1108/JFMPC-01-2020-0005
Sanni, A., & Hashim, M. (2017). A review of the integration of building information modeling
and cost estimating in construction. International Journal of Built Environment and
Sustainability, 4(3), 148–156. https://doi.org/10.11113/ijbes.v4.n3.207
Let me continue with Section 2.0: Conceptual Framework?
