Put your construction data to work with predictive AI

November 29, 2021 | 5 minute read
Todd Dakin
Product Marketing Content Manager
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Most construction analytics tools have two functions: observe and report. These are effectively passive functions. They collect data, and they present it in a user-defined context.

But someone still has to define that context. The tools look where they are told to look, and any anomalies occurring outside of that are ignored. But that’s the thing with surprises: they rarely happen when and where you’re expecting.

Outside of construction, technology has moved beyond passive data reporting. Consider web mapping apps like Google Maps or Waze. They run real-time analysis of traffic and use historical data to predict slowdowns. If a faster route is available, the user is notified.

Drivers don’t have to constantly run reports to ensure they’re taking the fastest route because these apps are designed to be dynamic and proactive.

In every industry, there is a data explosion. But with construction’s rapid and relatively recent adoption of technology, this explosion is particularly pronounced. There’s simply more data available than can be humanly processed. Luckily, this is robot work anyway.


In every industry, there is a data explosion. But with construction’s rapid and relatively recent adoption of technology, this explosion is particularly pronounced.


Enabling predictive intelligence in construction

Proactive analytics tools in construction are finally catching up with other industries. Oracle’s Construction Intelligence Cloud (CIC) Advisor continually monitors project data to identify any anomalies that indicate potential exposures.

See what’s possible with the Oracle Smart Construction Platform

You can think of it like a “risk radar” that never stops assessing your project’s performance, accessing deep data stores from the past and present to identify potential issues before they cost you time and money.

Let’s take a quick look at several ways CIC Advisor helps optimize your projects.

Predict delays and their impacts

CIC Advisor’s machine learning algorithms analyze both structured and unstructured data to look for patterns in projects and activities to find potential causes of delay. It learns from similar projects in the past, identifies outliers, and applies past performance measures to current measures.


For example, we can see the likelihood of a delay occurring on a project, and how many days the project could be set back. Drilling in further, it’s possible to see which activities are most likely to cause a delay.

This allows us to readjust the schedule, find out if certain activities could be performed in parallel rather than a series, and plan for any potential changes in scope.

CIC Advisor not only identifies potential problem areas, but it pinpoints the root cause as well. And with a more thorough understanding of where slowdowns are occurring, decision makers are better equipped to identify areas of improvement and act.

Catch potential litigation risks

Another way CIC Advisor identifies risks is by analyzing project correspondence in Oracle Aconex, an Oracle construction document management tool, using semantic natural language processing. Just like what you’d find in Alexa, Siri, and Google home, CIC can understand the sentiment and the context of a conversation, enabling it to spot potential risk.

Here’s an example of how CIC can identify a potential litigation risk. Even though the statements are very similar, CIC can understand the sentiment of the communication and detect the risk accordingly.


"On inspection, I have found a crack in the concrete. Please fix the issue before you proceed any further because this is a breach of contract. No payment will be made until this issue is resolved."

-Litigation risk

"On inspection, there is a crack in the concrete. I understand that extra time is ineeded to fix this and I am willing to accomodate an extension. I want to ensure there is no breach of contract the end. Please fix this as soon as possible."

-Not a litigation risk


Identify potential health and safety incidents

The features for predicting health and safety risks are similar to litigation, except we’re looking for different early indicators. For example, someone could have said that a gate was left open, or guardrails may not have been installed correctly, or perhaps there were potholes detected on the site that could result in accidents.

CIC Advisor looks at project correspondence managed in Oracle Aconex to identify health and safety-related conversations and highlights risks based on severity and contextual sentiments.

With this ability to benchmark and get a more complete picture across projects, planning becomes far more accurate, and resource allocation can be far more efficient.

Information is power

The next competitive edge in construction belongs to the companies who can harness their data. Dedicating teams of people to pore over reports is inefficient and costly.

Intelligent solutions that can find patterns and determine potential risks from contextual clues across projects and systems are already beginning to make construction safer and more profitable.


The next competitive edge in construction belongs to the companies who can harness their data.


Ultimately, this gives the boots on the ground and the decision makers in the office the ability to make more informed decisions, empowers them to plan with confidence, and unlocks the power of the data they already have at their fingertips.

Watch our webcast, part of a series on the Oracle Smart Construction Platform. Oracle data science experts on the webcast explore the ways AI turns project data into predictive intelligence.

Oracle Construction and Engineering, the global leader in construction management software and project portfolio management solutions, helps you connect your teams, processes, and data across the project and asset lifecycle. Drive efficiency and control in project delivery with proven solutions for project controls, construction scheduling, portfolio management, BIM/CDE, construction payment management, and more.

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Todd Dakin

Product Marketing Content Manager


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