For this assignment IDL 1 Final you will develop a handout for first-year students in your field. The purpose of this handout? is to persuade them that the competencies they will g

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.

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.

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