CHAPTER 3
The Future of Decision-Making

*THE FUTURE OF DECISION-MAKING IS DATA-DRIVEN*

Digital transformation has led to a world where data can be accumulated in real time, stored digitally, and retrieved at the push of a button. Bringing together multiple data sources into a single source of truth will be a game changer, eliminating fragmentation and misalignment across project stakeholders, and ensuring that teams work from real-time, consistent, and verified information. It will also allow decision-making to happen closer to the work itself — on-site, where problems arise — rather than at a distance, reducing the lag between problem identification and resolution.

What percentage of your construction data typically goes unused?

None
Less than 25%
25–50%
50–75%
More than 75%

Complex decision-making will shift from human-only to hybrid.

Rather than rely on error-prone, static spreadsheets or people’s gut instinct, future decision-making will leverage meaningful data-driven insights. AI, predictive analytics, and automation will shift decision-making from a human-only process to a hybrid one, where technology assists in making better-informed decisions based on a huge range of data.

More than 80% of survey respondents agreed or strongly agreed that access to historical data is critical to current and future projects, connected data across teams is imperative for project success, and accurate historical data helps reduce financial risks.²⁷ But while construction leaders realize that data is the foundation of decision-making, 76% of civil and infrastructure builders say they are not realizing the full potential of their data.²⁸

80%

OF RESPONDENTS AGREE
OR STRONGLY AGREE THAT:

⬢

Having access to historical data is critical to current and future projects

Having data connected across teams is imperative for project success

Accurate historical data significantly helps reduce financial risks

Having access to historical data is critical to current and future projects
Having data connected across teams is imperative for project success
Accurate historical data significantly helps reduce financial risks

Hybrid Model Decision-making

Click on the graph to enlarge.

AI will surface insights and recommendations, but experienced professionals will still validate and apply judgment to those insights. Leaders will lean into guiding decision frameworks, managing risk, to make better business calls faster, as they rely on AI for contextualized data and predictive analytics. Ordering and scheduling will become streamlined as AI assistants collate past models to anticipate future needs. The more data they collect, the better they will get at hitting the sweet spot between running short and oversupplying, minimizing wait times and waste.

“The industry doesn’t have a decision-making problem. It’s filled with experienced people who can make the right decision in a split second. What we have is an information problem.

They need the right information to make the right decision, so they can prove those hunches if needed.

We’ve all talked to that veteran superintendent with 20 years of experience who can walk next to a project and just sense that something is off. Now, that super can start with their hunch and say, ‘OK, let’s check the data.’ They can point out exactly what the problem is to their supply chain and move forward.”

^⬣^{AMIR BERMAN, VICE PRESIDENT OF INDUSTRY TRANSFORMATION AT BUILDOTS}

“The industry doesn’t have a decision-making problem. It’s filled with experienced people who can make the right decision in a split second. What we have is an information problem.

They need the right information to make the right decision, so they can prove those hunches if needed.

^{AMIR BERMAN, VICE PRESIDENT OF INDUSTRY TRANSFORMATION AT BUILDOTS}

⬣

Data will be integrated, providing key insights into project delivery.

Internet of Things (IoT) devices and sensors, which include smartphones, smart tools, and automated sensors placed on construction equipment, will automate data collection to provide key insights we haven’t been able to leverage in the past.

Data will also drive simulations, such as digital twins, which provide visibility into what will be required to build and how the end product will function. This data-based simulation enables teams to test decisions and their outcomes, before moving people and property to the project.

By analyzing all this data, we can begin to predict when supplies will need to be reordered, where and when to assign workers to specific areas of the jobsite, and how to better assess the team’s performance. Everyone will be capturing data, but those who ask the best questions of the data will thrive.

“Without a collaborative project delivery platform, I would need one or two extra full-time equivalents to produce the actual charts, the reporting structure, the report outs, and the continuous updating. Each full-time equivalent, depending on what they cost, adds up really quickly. A project that has 150 people, will have 40 or 50 people sitting in a meeting to get this information. Think about the efficiency you could gain if you saved those 30 minutes meeting every week.

These projects go on for two years in preconstruction; you’re now talking about hundreds of thousands of dollars saved.”

^⬣^{JASON BRENNER, HEAD OF INDUSTRY STRATEGY AT JOIN}

These projects go on for two years in preconstruction; you’re now talking about hundreds of thousands of dollars saved.”

^{JASON BRENNER, HEAD OF INDUSTRY STRATEGY AT JOIN}

⬣

CASE STUDY

ARCO/Murray uses data to unlock personal connections.

Impersonal decisions are a common criticism of data-backed decision-making, but ARCO/Murray is using data to go the opposite direction.

The design-build contractor’s process for subcontractor selection formerly involved hours of meetings to determine who had worked with whom and when, and what the outcome was. This was necessary to ensure the best selections were made for each project, but it was time-consuming and had to be repeated for each project.

Then, ARCO/Murray used their construction management platform’s API to implement a simple rating system for subcontractors. Each project in the system now comes with a handy drop-down menu where employees can rate the subcontractors they worked with.

Ratings are tied to individual employee accounts, which makes it easy to break experiences out by department and find the best person to talk to for context.

Now, when ARCO/Murray is looking at an earthwork subcontractor, it can instantly see who has collaborated with that group before and what kind of experience they had. Setting up further conversations to get relevant details takes minutes rather than hours, and all this valuable information is instantly available for projects down the line. This context enables ARCO/Murray to make smarter decisions about who it hires, faster.²⁹

Key takeaways:

THE FUTURE OF DECISION-MAKING

^{Tech and people}^{will be partners
in complex decision-making.}

^{Integrated data models}^{will provide new and critical information on jobsites.}

^{AI models, automation, and predictive analytics}^{will synthesize historical and real-time data, unlocking actionable insights and recommendations.}

^1.^{Tech and people}^{will be partners
in complex decision-making.}

^2.^{Integrated data models}^{will provide new and critical information on jobsites.}

^3.^{AI models, automation, and predictive analytics}^{will synthesize historical and real-time data, unlocking actionable insights and recommendations.}