Data. It’s a word many use without knowing what exactly it entails. Like “awesome” or “perfect” or “very,” it means everything, yet it means nothing. Like Schrödinger’s nebulous cat experiment, the word “data” is simultaneously resonant and boring.

There is no doubt that data is the future of not only construction, but of the entire global economy.

In the words of Hal Varian, Google’s chief economist, “A billion hours ago, modern homo sapiens emerged. A billion minutes ago, Christianity began. A billion seconds ago, the IBM PC was released. A billion Google searches ago…was this morning.”

Today, the technology exists to measure and record nearly every action in the real world, and as a result there was more being produced in the last 10 years than in all of human history. But is it truly understood what this awesome—and overwhelming—resource can do?

The simple answer is yes, but it is proving much more complex than that. In this new paradigm of data-driven decision making, many companies are asking the wrong questions, investing in the wrong tools and truly missing the point on what data can and should do.

NOT ALL DATA IS CREATED EQUAL

First, data is just half of the battle—the other vital input in data-driven decision making is the prediction machine that allows for anticipating outcomes. In this sense, it isn’t the data alone that is valuable, but rather the data in conjunction with powerful analytics.

Second, not all data is created equal. Like the fuel that powers cars and machinery, there are different grades and blends of data. Input data feeds an algorithm to return a prediction. Training data prepares the algorithms to make predictions. Feedback data is used to improve the performance of an algorithm. Sometimes this data comes from within a company, such as historical financial data, and other times it is captured directly from the field with the use of IoT devices or the trades’ field applications.

Aside from the types of data needed, the other popular question is how much data is needed? Contrary to popular belief, there is a decreasing return to scale in the amount of data collected. According to Avi Goldfarb, the chief data scientist at the Creative Destruction Lab in Toronto, “You get more useful information from the third observation than the hundredth, and you learn more from the hundredth observation than the millionth.” In other words, millions of permutations don’t need to be run in order to find trends. The first hundred or even first dozen will return valuable results.

A Piece OF THE PUZZLE

Ultimately, there is a lot of excitement about data in construction, as there should be, but there is not enough focus on the technologies that come with it. Automation, prediction and storage are all components in the New Machine Age. Over-indexing on data is like rushing to produce oil with no market—how useful would a tanker of diesel be with no engine to put it in?

The future of data is real time, not historical. Queries are done on unstructured and messy data sets, not squeaky-clean rows and columns. Machines create avatar data to simulate real-world scenarios and help leaders evaluate strategic and complex decisions. Eventually, executives will not even need to query their data platform for insight—they will receive unsolicited recommendations advising courses of action to avert otherwise unexpected disasters. This is why data is important.

To get there, however, contractors must rethink the way their companies operate. This starts in the workflows, which is where lots of valuable data gets stuck. PDFs, labyrinthian Excel files, owner-mandated systems, applications that struggle to integrate—these challenges must first be addressed before moving to the promised land of what real data analysis offers. When an operations or finance employee is complaining about double data entry, what that individual is really saying is “I need a better way to make decisions.”

Today, conversations around data are “How do I move it between systems?” not “Who is my most valuable owner?" Or “I don’t know where my data is?” not “Which of my projects are most at risk?” Data is not something to be hoarded. Instead, construction leaders must shift their thinking about data to see how they can use it to solve real questions about their people, companies, projects and markets. When contractors learn to use data at scale, it will change the fundamentals of the industry.