
Data-Driven Design and Construction
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Content
Foreword xiii
James Timberlake, FAIA, Partner, KieranTimberlake
Preface xv
Acknowledgments xxiii
Introduction: Measuring the Immeasurable, Validating the Ineffable 1
Not One More Thing 1
Strategies for Practice 2
Benefits of Gathering, Analyzing, and Applying Building Data 4
Challenges of Gathering, Analyzing, and Applying Building Data 13
Strategy No. 1: Hone in on Key Information 17
Strategy No. 2: Demonstrating Works, Explaining Doesn't 20
PART I Why Data, Why Now? 27
Chapter 1 The Data Turn 29
Five Factors Leading to the Leveraging of Data and Industry Change 29
Strategy No. 3: Look Outside the Industry 32
Case Study Interview with Robert Yori 37
Strategy No. 4: Not Big Data, Smart Data 54
Case Study Interview with Sean D. Burke 55
Data versus Documents 61
Case Study Interview with Jonatan Schumacher 63
Chapter 2 A Data -Driven Design Approach for Buildings 71
Five Trends Leading to the Rise of Data in the AECO Industry 71
Strategy No. 5: Eight Questions to Ask for Data Preparedness 73
Case Study Interview with Zigmund Rubel 75
Data-Centric Approaches 84
Case Study Interview with Andrew Heumann 86
Strategy No. 6: Four Steps toward Making the Change to Be More Data-Centric 87
Strategy No. 7: Ask Good Questions 88
Case Study Interview with Jonathon Broughton 96
Chapter 3 Learning from Data 107
Five Factors Ensuring Data Preparedness 107
Training, Learning, and Working with Data 110
Case Study Interview with Brian Ringley 113
Strategy No. 8: Play with Data 123
Case Study Interview with Toru Hasegawa 126
Case Study Interview with Aimee Buccellato 134
PART II Capturing, Analyzing, and Applying Building Data 141
Chapter 4 Capturing and Mining Project Data 143
Public Sources of Data 143
Case Study Interview with Ryan Mullenix 145
Private Data Sources 153
Case Study Interview with Sam Miller 157
Having a Data Collection Strategy 169
Strategy No. 9: Create a Data Collection Strategy 169
Case Study Interview with Gregory Janks 170
Strategy No. 10: First Steps to Becoming Data-Centric 174
Chapter 5 Analyzing Data 179
Analysis versus Analytics 179
Strategy No. 11: First Steps in Applying Data Analysis 180
Predictive Analytics 180
Case Study Interview with Mads Jensen 182
Strategy No. 12: Two Ways to Think about Energy Analysis 191
Strategy No. 13: Analysis for Sustainable Design 192
Case Study Interview with Chris Pyke, PhD 198
Strategy No. 14: How Analysis Informs Decision Making 201
Strategy No. 15: Start Simple, Technology Optional 202
Strategy No. 16: Leverage Data as Means to an End 203
Case Study Interview with Brendon Levitt 203
Dhour Case Study 209
Chapter 6 Applying Data 213
First Steps 213
Strategy No. 17: First Steps Before Applying Data 214
Strategy No. 18: Plan for the Data 215
Case Study Interview with Billie Faircloth 216
Data-Enabled Project Teams 222
Strategy No. 19: Should the Data Team Be Integrated or Stationed in the Corner? 225
Case Study Interview with Andrew Witt 226
Data-Intensive Roles 230
Strategy No. 20: Computer Scientist vs. Emerging Professional 231
Case Study Interview with Greig Paterson 235
Leadership in Data 238
PART III What Data Means for You, Your Firm, Profession, and Industry 241
Chapter 7 Data in Construction and Operations 243
Data in Construction 244
Strategy No. 21: Construction-Related Data Questions 245
Case Study Interview with Tyler Goss 246
Responding to Change 250
Case Study Interview with Mani Golparvar-Fard, PhD 250
Linking Design, Construction, and Operations 259
Strategy No. 22: Extract and Transfer What Matters 261
Case Study Interview with Bill East, PhD 262
Standards and Interoperability 266
Case Study Interview with Greg Schleusner 267
Chapter 8 Data for Building Owners and End Users 273
Benefits to the Owner 273
Case Study Interview with Sukanya Paciorek 274
Direction to Work with Data 277
Case Study Interview with Peter Pellerzi 279
Strategy No. 23: with Data, the Heart of the Issue Is Culture 280
AECO Firms as Data Intermediaries 281
Case Study Interview with Brian Skripac 282
Data Visualization Helps Owners Make Decisions 285
Case Study: Data Viz Using Revit 286
Case Study Interview with Evelyn Lee 293
Data-Driven Design Driven by Owners 296
Chapter 9 Building a Case for Leveraging Data 297
Business Intelligence (BI) and Current-State Assessment 297
Fee and Profitability Data Case Study 298
Case Study Interview with David Fano and Dr. Daniel Davis 300
Strategy No. 24: Big Data in Practice 301
Security and Privacy 310
Case Study Interview with Mark Frisch, FAIA, LEED AP BD+C 312
Sharing Data 324
Case Study Interview with David Sawdey 325
Strategy No. 25: Use Data to Provide Better Service 326
Epilogue
The Future Of Data In AEC 331
Our Data-Driven Future 331
The Future Is Already Here 333
Appendix 337
Experts, Innovators, and Thought Leaders Interviewed 337
Organizations and Universities Represented 338
The 25 Data-Driven Strategies 339
Software Mentioned 339
Recommended Reading 341
Index 343
PREFACE
Sherlock Holmes was highly intuitive, but only after he had collected sufficient data to eliminate the false positives.
-Jonathon Broughton, Data Wrangler
The impetus for this book goes back to my time as a university student. Upon graduation from architecture graduate school, as a graduation gift, my mentor-a professor-gave me a draft outline of a book he never got around to writing. "Here, you write this," he said, as though he was giving me a book to read. The book-had it been written-was on the topic of architectural justification, a subject that had at the time and long since interested me. I found the opportunity for design professionals to provide ultimate justifications for their architectural acts compelling. While that book so far has not been written (and this is not that book), a focus on process, decision making, and professional judgment prevail in my thinking, in my public speaking, and-informing my research on data in the AECO industry-in the pages that follow.
More recently, I served as the lead design architect on a team of talented designers and researchers on a prototype apartment building. Only this wasn't your typical housing project: This building would inconspicuously tap residents for their data. Data, in other words, would be extracted from the building's inhabitants in exchange for subsidizing their rent. My task, as the sole architect on the team, was partly to design attractive, functioning, buildable housing; but, as I soon discovered (and more importantly to the team in the success of the outcome), the charge was to assure that the 24/7 collecting of valuable data from the residents didn't feel like eavesdropping, wiretapping, or the intervention of Big Brother. In other words, the data gathering had to feel seamless and invisible. Most importantly, it couldn't feel creepy. It wasn't the first time an architect has been called upon to design something that needed to disappear, but it proved to be the most important. And the client's fascination with data goes a long way toward explaining why, as an architect, I am drawn to the topic of data-driven design. For the first time in my career, design and data met head to head. It wouldn't be the last.
The real revelation for me as a licensed architect, building designer, and professor was that the housing project-the building-was treated by all on the team as something almost incidental. Sure, it needed to be there: The residents needed to live somewhere. Something needed to keep rain and snow out of their bedrooms. But, to be sure, the focus of every meeting was on the data: how it would be gathered in such a way that people didn't feel like someone was watching their every move, however private. No one in the building, for example, could be aware of conspicuous data-gathering devices. How one went about tapping the building inhabitants for their data was the real design assignment. The goal was to make the data capturing innocuous, undetectable, and appear to be humane.
In my career as a building designer, I am continuously challenged by the need to persuade clients to go with-or as often dissuade them from going in-a particular design direction. There is only so much arm-waving an architect can do to recommend a preferred design direction. Early on, I realized that this process was a whole lot more successful-faster and less painful-when the decisions (our so-called preferences) were backed with reliable data.
To take one example, when approached by a client to expand their headquarters due to projected growth, there was some guesswork as to whether the completed project would accommodate the owner's needs at time of move-in and beyond. I watched as the addition, nearing completion, accommodated the company's anticipated expansion needs, but not their severely underestimated future needs. Data, and data analytics' ability to predict outcomes-as several individuals and cases in this book attest-would have prevented these stressful and unhappy outcomes.
In my parallel career as a university professor-whether teaching a comprehensive- or integrated-design studio, sequence of building construction courses, professional practice or mixed-reality construction management (virtual and real)-I have come to realize that the subject of data permeates the heart of the curriculum. Yet, just try getting a course approved on the topic of "buildings as data" over the long-used standbys: buildings as buildings, or buildings as documents. It is disheartening to recognize that what students need to know in order to thrive in the new work environment isn't always, if ever, taught. Something needs to change.
While writing my last book, BIM and Integrated Design: Strategies for Architectural Practice (John Wiley & Sons, 2011), I started paying more and more attention to the often cited "I" in BIM, which stands for "information." I noticed that, for most users, the BIM model was treated as a receptacle or place for safekeeping. People would say the model "holds" objects, the building code, specifications, and other types of information the way a shelf holds books. As analogies go, this wasn't a very sophisticated one.
While recognizing the value of BIM, most individuals and firms use BIM today as a document creation tool, when instead design and construction professionals need to recognize BIM's real value as a database, and start treating it like one. Additionally, it has become increasingly clear-through the ongoing research of Paul Teicholz and others at CIFE-that BIM alone won't improve labor productivity in the AEC industry, which, after more than 50 years of tracking, still lags other nonfarm industries. To improve productivity we will need something more. In BIM and Integrated Design, I suggested that we needed to collaborate and integrate while using BIM to see steeper and swifter gains. As of the writing of this book, those gains have yet to be realized.1 Something else-in combination with working on integrated teams-will need to do the heavy lifting if we are to see progress in our lifetimes. (See Figure P1)
Figure P1: BIM alone won't improve labor productivity in the AEC industry, which, after 50-plus years of tracking, still lags other nonfarm industries.
© Aditazz
Here, in this book, I am proposing that leveraging, capturing, analyzing, and applying of building data is the answer to our industry's collective productivity woes.
Asking the Right Questions
Starting with data, without first doing a lot of thinking, without having any structure, is a short road to simple questions and unsurprising results. Picking the right techniques has to be secondary to asking the right questions.
-Max Shron2
As conferences are where the questions of what matter most to a field are asked, as a member of Notre Dame University's Sustainable Data Community, I spoke recently at their Forum where I posed the following 12 questions:
- The AEC industry is the last to use data-why?
- What's driving data use in other industries?
- Why is this happening now?
- What forces are conspiring to come together to make the time ripe to leverage data in our practices and organizations, in our businesses, jobsites, habitations, and offices?
- What's the business case for incorporating data into our industry?
- How exactly will design professionals have a competitive advantage when working with data?
- Will architects have to adapt to working with quants? How will they do so?
- Will we need to modify the architectural curriculum to incorporate learning of the gathering, analysis, and use of data in design projects?
- Can data be crunched into a form that can be analyzed and communicated by nonexperts?
- Where do knowledge and judgment come in? And how, using data, does one arrive at insights?
- How can we ensure that our data is of high quality?
- Can we legally allow others to rely on the data in our models? Can we guarantee that data? Who is liable?
After conducting 40 in-depth interviews with design, construction, and operations professionals and educators around the globe for this book, I feel that all of these questions-except one-remain warranted. That would be the first: The AEC industry is the last to use data-why? It turns out that design professionals, at firms large and small, using sophisticated digital tools and hand tools, intelligence and intuition, have been using data to great effect and equally impressive results in their work. It is just that we, as a profession and industry, have not given voice to it-until now. In this book, I have sought to respond to each and every one of these questions, and many more.
The other week I found myself on a long road trip with a university facilities and operations director. The conversation got around to the topic of my research. I mentioned my book-the one that you are now holding, Data-Driven Design and Construction. He looked at me as though to ask, How will that help me? This book shows him-and now you-how. Using practice-based research and in-depth interviews with industry and academic leaders, this book seeks to answer these and...
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