Constructors of Inexactitude, Architects of Imprecision

datapostitsArchitects and contractors I have worked with over the years like to be precise in what they do.

And good thing. They have be.

Architecture and construction aren’t just crafts and trades – they’re disciplines.

There’s a level of accuracy involved in delivering a successful project.

Shouldn’t we expect our data to be equally precise?

Design specifications call for building tolerances to be in the fraction of an inch.

Construction tolerances have to follow the letter of the documents or be rebuilt.

accuracyprecisionSo, how are architects and contractors going to fare given the imprecision of big data?

Given the impurities and errors so often found when churning large quantities of information?

At a time when design and construction professionals are wondering whether their future includes sitting side-by-side with AEC-dedicated data scientists, how ironic that it isn’t the laser-like precision of statisticians or number-crunching of big data scientists – but the necessary inexactitude and imprecision of vast quantities of data – that they will be contending with.

This imprecision may prove the more difficult thing for architects and contractors to get their heads around.

Accepting errors as part of the mix may be the bigger part of change for those in the AEC industry.

Are building design architects going to be able to handle big data’s messiness?

Are contractors going to be comfortable dealing with sloppy but vast metadata?

designprocessSure, most projects in the earliest stages are no more than a collection of hunches, assumptions, intuitions and WAGs.

But when designers run a dimension string, or calculate square footages while preparing a permit set, they have to be sure that all their numbers add up.

Constructors, too, are often contractually required to report inconsistencies and errors they find in the construction documents.

Are they going to learn to live with errors in the large quantities of data they’ll be working with?

Will this require a new or different mindset from the those who design, model, construct, own and operate buildings?

Will building teams learn to live with and tolerate these quirks of big data?

Or perhaps, as with any contradictions, see them as additional opportunities to gain knowledge and insight?