Learning from millennials

By Gilles L. Letourneau
In the construction industry, we are seeing technology affect long-standing work flows and processes used to research, prepare, develop, and distribute construction information, but that is not necessarily a bad thing. We can all agree, specifications as a key component of construction documents won’t go away in the foreseeable future. What I have been pondering are the inevitable process changes required to satisfy the new generations of young designers who experience information saturation as a normal part of their daily routines.

Consider the following comparison from Bharat Anand’s book, The Content Trap: A Strategist’s Guide to Digital Change: “Five exabytes (or five billion billion bytes) of data could store all the words ever spoken by humans between the birth of the world and 2003. In 2011, five exabytes of content were created every two days.”

Never mind the fact the millennial generation experiences 331.2 million posted images on Instagram every day! This is what I call “information saturation” and it has a drastic effect on how millennials interact with content-rich technologies. If you have any doubts, watch how fast your teenager scrolls through their Facebook feed. Millennials and post-millennials (those born since the mid-90s) have trained their brains to scan information quickly and to extract nuggets of information pertaining to them at that very moment.

Daniel Newman, writing for Forbes magazine, noted: “Millennials communicate with each other far more than any advertising campaign can. When trying to figure out whether something is worth buying, millennials will go to their friends and social networks to see what people think. They use this collective filter to sort out research and other word-of-mouth style information when making decisions.” Extraordinary!

The construction information supply chain must respond to this in ways one has never before witnessed. We need data systems that can serve us “just the data we need, at the time we need it, for what we need it for.” Fortunately, there are some very smart data engineers who have seen this coming in other industries and have approached the problem in innovative ways. New systems of storing and retrieving non-relational databases are now available and becoming the norm. The days of familiar databases storing and retrieving relational data have gone the way of the dinosaur. The sheer amount of data we interact with today is simply too large for these systems; “big data” systems have taken over.

So, what drives our attraction to Facebook, Instagram, and Snapchat? What makes these companies so successful in gathering and dispersing big data? Thinking back to our smartphone-scrolling youngsters, maybe it is not the amount of data attracting them but the possibility of making new connections. Millennials thrive on these connections, the thrill of getting the scoop, staying on top of scuttlebutt, and following new contacts. The social media industry takes great advantage of this phenomenon and, in many cases, relies on pattern recognition, machine learning, and artificial intelligence (AI) technologies (think Pinterest).

AI systems search for patterns within large groups of data and allow users to make projections based on patterns found in the connections between the data points. This allows users to discover trends and make smarter data-centric and informed business decisions. That has been the modus operandi of Google, Amazon, LinkedIn, and others for years now for their custom internet advertising. You see this whenever you shop on one site for a hat and then search Google for shirts and the hat you just reviewed shows up as an ad. I prefer to perceive this practice as a personalized private service rather than an invasion of privacy.

Bringing it all back home
Pattern recognition is not new in our industry. Traffic analysis technology employed for the design of automobile traffic control, large retail malls, and office parks has been used to analyze traffic patterns to inform designers for space planning and efficiencies of proposed pedestrian pathways. There is technology available today to perform this in real time. That is just one small example.

Sam Ransbotham and David Kiron, writing in MIT Sloan Management Review about the organization’s 2018 Data & Analytics Global Executive Study and Research Report, stated: “Innovative, analytically mature organizations make use of data from multiple sources: customers, vendors, regulators, and even competitors.” This makes a ton of sense to me. I envision this big data advantage driving the next wave of construction information management and interaction technology. It will become available sooner than you might think.

So, yes, I do think millennials will be writing specifications, but they will do so within entirely different environments and platforms. Platforms that serve “just the data they need” because the systems will access user profile data, product search history, technology use tendencies, and day-to-day practices, and use this to cut through the information static and provide the most likely relevant data set. This platform will be a real-time digital assistant and predict the most appropriate time to provide the proper data “at the time they need it” based on past use cases of the user as well as the trends of a community of colleagues.

Specification and product data will be accessible anywhere at any time and in the proper format and structure, packaged “for what they need it for,” based upon the technology application being used. As timeframes and project budgets continue to get more demanding and projects grow in scope and complexity, we need systems to work smarter, not harder.

Let us demand technologies that use the community and the power of big data to make our construction information, and specifically our specification information, real time, dynamic, curated, trusted, and “smarter.”

Gilles L. Letourneau, CSI, AIA, is the general manager of architectural and engineering product at Avitru, LLC. Letourneau joined Avitru through the acquisition of InterSpec, where he was founder and CEO. While at InterSpec, he developed patented technology for building information modeling (BIM)-to-specs integration. He provides–in equal measure–insights in building architecture and software architecture. He can be reached at GLetourneau@avitru.com.

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