Big Data and Architects Part 1: Big vs. Little Data in the Architectural Practice

The Big Picture

The image accompanying this blog is my Google Analytics map from the cities across the globe from which I have had new visitors this year: The blog is big in Samara and Almaty and of course Dunedin and Lagos. So, thank you everyone who has visited from near and far. 

Cities_Blog

There has been a lot of talk about big data and data analytics of late. I saw a talk at work the other day about metrics concerning global-cities and thought: Wow ! We all love the macro-view. It makes us feel that we are above it all. Big data nowadays is kind of like a juggernaut as online information is constantly being gathered by big, big, big firms like Google and Faceybook. Arguably Trump employed data analytics from Cambridge Analytica to win HIS election. Of course, much closer to home is AURIN.

It’s easy to get seduced by the big picture stuff and BIG DATA; it has become such a catchphrase for the academic, consulting and elite chattering classes; So, I thought I might devote a few blogs to discussing it from the architect’s perspective.

For the architect it is not so much about BIG data but in fact LITTLE data.

Little Data = Data generated within and circulating through the architect’s firm.

Architects are too small and certainly not the cloud platform or solutions we might find at Google.

I am quite interested on following Meltwater a firm that gathers and gains insights from the realm of online data that exists outside of “internal reporting systems.” I guess when I saw those words I wondered about the internal and external reporting systems of architects. Do these systems actually exist? Or, is it all just seat of the pants decision-making and guess-work in the architect’s office? Their CEO of Meltwater has written a book which looks good and can be found here.

It’s probably a good idea to start with some of the basics of what I might call Little Data pertaining to the architect’s studio. Then further blogs will cover big data, data analytics and strategic intelligence (including its politics and ethics) and most importantly how data analytics might be employed in the design studio. I might even throw in a bit of critical theory for fun.

Think of this as a crash course in data, information and knowledge management. For most architects there is probably three or four types of data that they need to gather (and scrubbed), and manage in order to make effective decisions.

1. Internal Firm Data and Information:

Information about the firm internally is really critical. Especially, given that for architects the primary input is the amount of hours worked accurate data on this is crucial. Another category of data central to the firm This can then be mapped against the fixed and variable expenses that the firm incurs in doing the work. Of course, in Australia, as is the case elsewhere, keeping time and wages records (like overtime) is an important thing to do under the Architects award.

2. Broader Industry Structure Data and Information:

This covers information about the broader Industry, other similar, or contrasting  firms and how all of these things are performing. How much profit should a firm be making, how many hours should it be spending on particular project phases? How much should be spent on marketing each year, for example, and how does this compare to other architectural firms?

Yes, all architects really need to pressure our professional associations, groupings and even governments to continually collect and distribute this kind of information about the market for architectural services.

3. External Facing Data and Information:

This includes information about potential clients, potential areas or sites of development and expertise. In the real world they call this Business Intelligence. If an architectural firm is to be entrepreneurial and anticipate future work then it needs to develop a base of research and knowledge in particular area. For any firm it is important to understand that overall demographics and needs of the entities or agents that might fund architectural work.

For this reason data gathered around the strategic imperatives, culture, asset management, site, planning and regulatory contexts, demographics and anything at all to do with the client is important. How is client’s business and operations structured? Who should we develop relationships with?A good question to ask is: where is the money coming from and who actually owns a company that might give you work?

4. Online Information:

A rapidly rising subset, if not the only one to be concerned with, is online information. This could mean anything from collecting data and about the firm’s own websites or new media channels like Instagram or Farcebook. Or collecting (scraping, is the term used, I think) information, from online, about areas of knowledge the firm is interested in. I will discuss this more in future posts.

So what ?

Once you have all of this data a firm might then be in a situation to make some reasonable design decisions. But all of this data, once gathered needs to be readily at hand. In other words it needs to be in some kind of legible and easily accessible data, information and knowledge management system. Maybe it’s an just an excel spreadsheet, database or maybe that’s  a IT system with a legible file directory.

It’s not rocket science but too often data, information and Knowledge Management in architectural firms is not seen as high priority.  But, how many architectural firms have a knowledge manager or even think about having a Knowledge Management function within their firms.

For small firm’s it is a stretch to even get the right information and data systems, even if it is only an excel spreadsheet of contacts, in place and for large firms too often data is spread across to many different silos and knowledge is too often locked into people’s heads or hidden from view by management.

Too often architects are sucked in by the production and delivery orientated technologies. Yet in the future, for both clients of architects managing data, information and producing knowledge will be where it is at. Not producing actual things. This is especially the case,  in terms of design and design outcomes, so let’s hope architects don’t miss the boat on this one.

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