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Sheila Gobes-Ryan 1
Probability and Statistics are the Foundation
for Building Your Architectural Career
Introduction
As future architects, we all dream of creating iconic buildings that result in professional recognition
and financial success. Increases in ‘big data’ and the technologies to analyze these data sets more
effectively make it possible to improve the quality of our designs in significant ways during the
design process. However, to integrate these big-data benefits into our design solutions, we need to
become proficient in probability and statistics while in school.
To illustrate this to you, I will describe how probability and statistics are used in architectural
design and show that this skill will help start your career when you graduate. First, I will discuss the
uses of probability and statistics for improving the outcomes of several phases of architectural
projects. Then I will talk to you about the importance of having the skill to complete data analysis
when starting your career.
The Use of Probability and Statistics in Architecture
Design Phase Use of Probability and Statistics
Architects use probability and statistics during different phases of projects to improve and evaluate
the effectiveness of their built projects. In the following sections, I will present the use of
probability and statistics in four project phases:
1. Architects use probability and statistics during site selection to analyze relevant data.
2. In pre-design, they analyze client needs and evaluate their client's industry space use trends.
3. During design, they assess the layout and material options against existing performance data.
4. In post-occupancy, they evaluate the performance of the space against project goals,
comparable properties, and performance standards and requirements.
By integrating data-driven decisions into the design process, architects can be confident that they
will achieve the high client satisfaction needed for financial success.
Probability and Statistics in Site Selection
An organization’s selection of location impacts many aspects of business success. The decision
may be which city to locate in, what city section to move to, or what specific property to occupy.
However, for each decision, organizations must consider a wide range of business impacts that
location choices can have and if these will be positive or negative for their business. With statistical
and probabilistic analysis, architects can present the business impacts of many factors based on
current data and predicting how many factors are likely to develop in the future. These factors
include access to employees with the necessary skills, proximity to clients or customers, local cost
of living and expected wages, and commute time and transportation access for employees.
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Architects can use these analyses to combine client data, publicly available data, and mobile device
data to make data-driven site selection decisions (Intalytic, 2021). With this, architects provide
their clients with better business outcomes.
Probability and Statistics in Pre-Design
Architects collect and evaluate data statistically during the pre-design stage to determine building
space needs (Vangelatos, 2018) currently and into the future. Input from client interviews and
surveys, company growth projections, and industry benchmarks are all integrated into space needs
and acquisition decisions. Client organizations will rely on the dependability of this work as they
sign leases that extend for years or sometimes decades.
Probability and Statistics in the Design Phase
During the design phase, architects make decisions on materials and building systems so that
projects meet current regulations for things such as energy and water use (Yaglewad, 2020).
Additionally, we are often required to go beyond this to meet standards like the LEEDS
Sustainable Buildings Certification and Zero Net Energy (Carbonnier, 2020). Our ability to run
virtual simulations that statistically evaluate and present a wide range of design, material, and
construction options is critical to our success in this phase. These simulations integrate physics and
statistics to provide sophisticated examinations of building performance of various design choices.
Findings from these simulations allow architects to make changes to improve building performance
before anything is built (Goy, Maréchal, and Finn, 2020).
Post Occupancy Evaluations with Probability and Statistics
After clients move into buildings, sensors connected to the internet can measure and evaluate
actual building performance (Davis, 2015). Owners can assess building performance against
building code requirements and targeted certification programs, such as LEED (Davis, 2015).
With the decrease in the cost of monitoring systems, building owners and occupants are using
these systems to collect and evaluate data on building use and building systems performance in
increasingly complex ways. Vendors of building systems components are creating sophisticated
data visualizations to present this data in easy-to-understand formats.
Clients are using these analyses to move toward performance-based contracts with architects.
These contracts hold back part of the design fees until clients evaluate the buildings resulting from
an architect's design against required performance standards (Davis, 2015). To get the
compensation they are due, architects' pre-design systems of evaluation must match the post-
occupancy performance of the resulting buildings. As a result, architects now have a significant
financial stake in the accuracy of the probability and statistical analyses they complete.
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Probability and Statistics Literacy will Enhance Your Employability
You may be thinking that this is a skill set you can skip and allow others to bring to architectural
firms. However, recent data from the National Architectural Education Association (NAEA)
(2020) suggests you should think again about this.
Surveys completed across 2,456 participating architectural practices show that 93% of these firms
of all sizes use statistical data in multiple phases of their design work. For this reason, 85% of these
firms identified data literacy as a skill they consider significant for new employees. This skill
ranked higher in importance than traditional skills such as CAD proficiency. In follow-up
interviews with 200 firm leaders, 87% identified recent graduates' data literacy as inadequate for the
work demands of entry-level positions. This deficiency did not align with the finding that 70% of
architecture school faculty believed they were preparing their students for the data literacy
demands of the profession. Most challenging was that only 17% of architecture students identified
data literacy as a necessary professional skill (NAEA, 2020).
This data suggest that architecture programs are not preparing students for the data literacy
demands of their profession. Conversely, this preparation deficit provides a distinct advantage for
architecture students who become data literate and familiar with the uses of data analysis in their
professional lives.
Conclusion
This document discusses the many phases of architectural design work in which probability and
statistics play a role. They are first used to evaluate different options for siting a project. Then to
document building needs into the future. During the following phase of work, architects run many
design choices through simulations that evaluate and present various design choices in building
performance. Finally, owners use probability and statistics to collect data and analyze building
performance outcomes. Clients are frequently connecting these outcomes to completing payment
of architectural contracts. For this reason, as with many fields, using and evaluating data in a wide
range of probability and statistics applications is a skill that employers have indicated is critical.
When we prepare to graduate, we now know this is a skill we must have to start on a path of
financial and professional success
References
Carbonnier, E. (2020, April 5) Zero net energy design strategies: Creating a new normal. Retrieved
from https://hmcarchitects.com/news/zero-net-energy-design-strategies-creating-a-new-
normal-2020-04-03/
Chilton, J. J. & Baldry, D. (1997). The effects of integrated workplace strategies on commercial
office space. Facilities, 15(7/8), 187-194. doi: 10.1108/02632779710168227
Davis, D. (2015, April 23). How big data is transforming architecture.: The phenomenon presents
hug opportunities for the built environment and the firms that design it. Architect.
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Retrieved from https://www.architectmagazine.com/technology/how-big-data-is-
transforming-architecture_o
Goy, S., Maréchal, F. & Finn, D. (2020). Data for urban scale building energy modelling:
Assessing impacts and overcoming availability challenges. Energies 13. doi:
10.3390/en13164244
Intalytics, (2021). Precise recommendations back by sound science. Kalibrate Company.
https://intalytics.com/real-estate-solutions/
Vangelatos, G. (2018, October 12). How architects help increase patient satisfaction in healthcare
through building design.
Yaglewad, S. (2020, May 19). How is statistics used in architecture? What After College. Retrieved
from https://whataftercollege.com/data-science/statistics-used-in-
architecture/#:~:text=How%20is%20Statistics%20used%20in%20Architecture%3F&text=W
hen%20an%20architectural%20project%20is,use%20for%20the%20end%2Dusers.
- You may be thinking that this is a skill set you can skip and allow others to bring to architectural firms. However, recent data from the National Architectural Education Association (NAEA) (2020) suggests you should think again about this.
- Surveys completed across 2,456 participating architectural practices show that 93% of these firms of all sizes use statistical data in multiple phases of their design work. For this reason, 85% of these firms identified data literacy as a skill they c...
- This data suggest that architecture programs are not preparing students for the data literacy demands of their profession. Conversely, this preparation deficit provides a distinct advantage for architecture students who become data literate and famili...