The current digitization tendencies in AECO are dangerously confusing. While digitization invites us to interpret and even experience the world as information, AECO is still entrenched in analogue practices that keep information implicit. This means that we miss the opportunity to develop new conceptual models of reality, which are a prerequisite to digitization and information processing by machines. Instead, we use the old and arguably outdated analogue practices as the domain of discourse (the stuff that should be digitized).
Equally limiting is that digitization in AECO still calls for human interpretation, which runs contrary to the general tendency to remove ourselves from the centre of the information world. As a result, the explosively increasing amounts of digital information become a burden rather than an opportunity: we still focus on the availability of information for human consumption instead of on the information-processing capacities of machines that can support us in reliable, meaningful ways.
Even worse, the very availability of information may be underplayed. While digitization in general makes increasingly difficult to claim ignorance of anything, in AECO a project can be an isolated microworld that fails to acknowledge what exists beyond its scope. Learning and generalizing from precedents remains unsupported by AECO information technologies but even within a project many silos persist. The brief and budget, for example, are practically never integrated in the setup of a model in BIM, thereby leaving powerful options for design guidance and automation severely underutilized.
Such limitations do not merely affect IM; they also undermine decision making. As we shall see in the chapter on decisions and information, there is strong evidence that human thinking comprises two kinds of processes. The first kind (Type 1) is fast, automatic, effortless and nonconscious, while the second (Type 2) is slow, effortful, conscious and controlled. Type 1 thinking dominates daily life and allows us to be quite efficient in many common tasks but it also regularly leads to errors, especially in complex tasks. Regrettably, we tend to rely too much on the economical Type 1 processes and accept their products, even in situations that clearly call for Type 2 thinking. For example, we tend to make judgements on the basis of the limited information available in our memory at a given moment (e.g. news stories of the past few weeks), instead of taking the trouble to collect all relevant data and analyse them properly before reaching a decision.
This type of thinking occurs only too frequently with respect to the built environment: we become concerned about fire safety only after a publicized disaster and then go into a frenzy of activity that nevertheless soon subsides, especially if there is no similar disaster to rekindle our interest or if a disaster of a different kind occurs, even though the probability and risks of building fires remain the same. Moreover, we do not exhibit the same concern about stair safety, despite the fact that annually there are more victims of stair falls than of building fires, probably because each stair fall usually involves only one person, while a single building fire can have tens of victims.
That such problems are not restricted to AECO is not a consolation but a further danger: studies of human decision making reveal that people take decisions intuitively, on the basis of readily available rather than necessary, well-structured information, even in sensitive, high-risk and high- gain areas like finance. Share trading, for instance, is usually presented as a highly skilled business but performance is not consistent: it seems more a game of luck than one of skill. It is therefore important to take such failures into account also when we try to learn from other areas, especially with respect to management.
In addition to acknowledging and controlling our biases, so as to use Type 2 processes more frequently and purposely, we must take care that we always have access to the right information for these processes. This information, structured in transparent and operational descriptions of a task and its context, is the real goal for digitization in any AECO project: it returns human-computer partnerships, where machines support human decision making through extensive data collection, analysis and representation. Note that this does not imply a lessening role for humans in decision making. On the contrary, it adds to the capacities of humans by facilitating Type 2 thinking through explicit information, as well as by freeing resources for Type 2 processes.
The general conclusion is that AECO digitization is in urgent need of substantial improvement but this improvement is not merely a matter of importing new technologies as panaceas. The prerequisite to any change is a thorough understanding of building information and how it relates to our cognitive and social processes. As we shall see in the following chapters, once this is achieved, all goals, including IM and decision support, become clear and fundamentally feasible.
• AECO digitization is characterized by slow, limited uptake, bounded by analogue conventions and confused by its dual origins: automation of design and computerization of drawing
• The persistence of analogue practices makes digital AECO information not only inefficient but also redundant, incoherent and inconsistent
• BIM is a transitional technology, still bounded by analogue practices, but, as a symbolic representation, also an indication of things to come
• Digitization is critical not only for information management but also for decision making
Exercises
1. Calculate how much data a design project may produce and explain your calculations analytically, keeping in mind that there may be several design alternatives and versions. Use the following categories:
1. CAD or BIM files
2. PDFs and images produced from CAD & BIM or other software 3. Alphanumeric files (texts, spreadsheets, databases etc.) 4. Other (please specify)
2. Calculate how much of the above data is produced by different stakeholders, explaining your calculations analytically:
1. Architects
2. Structural engineers 3. MEP engineers 4. Clients
5. Manager
Notes
1. Two examples of studies of digitization in AECO are: (a) a typically opinion-based view of digitization in AECO: https://www.mckinsey.com/business-functions/operations/our-insights/imagining-constructions- digital-future#, and (b) a more detailed account, using relevant data and meaningful proxies:
https://www.zew.de/en/publications/zukunft-bau-beitrag-der-digitalisierung-zur-produktivitaet-in-der- baubranche-1.
2. Performance and in particular the avoidance of failures and related costs are among the primary reasons
for adopting BIM, as argued in: Eastman, C., Teicholz, P.M., Sacks, R., & Lee, G., 2018. BIM handbook (3rd ed.). Hoboken NJ: Wiley.
3. Research conducted in 2015 in the UK: https://www.newforma.com/news-resources/press-releases/
70-aec-firms-say-information-explosion-impacted-collaboration/