The public construction industry faces a pricing disorder that surpasses the confusion of pre-Internet real estate, according to one industry insider. While residential homebuyers once struggled to value properties without reliable sales data, contractors bidding on public infrastructure projects face even greater information gaps—resulting in bids on identical projects that can differ by millions of dollars.
Mark Zurada, COO and co-founder of PinPoint Analytics, says these bid spreads reveal a market with almost no effective price discovery. “For a million-dollar project, you might have one bidder come in at 750, another bidder come in at a million, another at 2 million, another at 4 million,” Zurada explains. “The spread is that great.”
This disparity, Zurada notes, is not due to differences in project scope or quality. Instead, it reflects contractors working with little to no market information. Unlike residential real estate, where platforms like Zillow aggregate property records to provide price transparency, public construction has never developed a comparable data infrastructure—even though every bid submitted is technically a matter of public record.
How the Market Lacks Price Discovery
Zurada points to the estimation process as the root of the problem. “There’s basically no Home Depot catalog for these types of line items,” he says, referring to the heavy civil components that make up infrastructure projects. “You can’t just price out these things very easily. I was shocked at how different prices can be.”
Without standardized pricing data or broad market comparables, each contractor builds their estimate in isolation, assembling costs line by line and adding profit margins. The result is that five contractors bidding on the same project may arrive at five vastly different figures—not because they’re offering various solutions, but because each is guessing at what the market will support.
Zurada compares this to the era before Zillow, when various agents relied on a limited, often outdated set of comparable sales. “Before Zillow, if you were going out to buy a house, you would hire an agent. But how do you price that house? It was a tough thing to do. You’d get a few comparables, but they were never exactly like the house you wanted. You’d have to really guess at the market price.”
In that environment, Zurada says, five buyers might each come up with a different value for the same property—one at $800,000, another at $1.25 million, and a third at $1.5 million, even though the house is actually worth $1 million. “You sure don’t want to be the person bidding 1.25 when it’s actually worth 1 million,” he says, “because you’re overbidding by $250,000.”
The Lowest Bidder Problem
Public construction bidding is further complicated by the rule that the lowest qualified bidder wins. This forces contractors to compete against their own interests, as underbidding leaves profit on the table, while overbidding means losing out entirely.
“The worst part of the situation is that the lowest price bidder wins,” Zurada says. “Let’s say the fair market value of the project is a million dollars, and somebody bids 750,000. They’re doing the same work. If the second-place bidder bid $ 1,000,000 and bid 750, he left $249,000 on the table. That’s money the company could have earned.”
The contractor who bids $750,000 is legally required to complete the project at that price, even if the next-lowest bid is nearly $250,000 higher. They deliver the exact scope of work, but with a sharply reduced profit margin solely because they lacked reliable market data.
This dynamic results in significant inefficiency across the industry. Contractors may lose out on substantial profits by underbidding or waste weeks preparing bids that are too high to be competitive. The entire public cost sector operates with less price transparency than a typical homebuyer now enjoys.
Why Data Infrastructure Never Emerged
Zurada argues that the data needed to solve this problem already exists and is publicly accessible. “Every single public construction project in the country, every one of those prices that’s submitted is a matter of public record,” he says. The problem is that no one has aggregated and analyzed this information at scale.
The process of collecting this data has been labor-intensive. PinPoint Analytics had to retrieve records from municipal filing cabinets nationwide and digitize them to create a usable dataset for AI models. Building a national database of five years’ worth of historical bid data is the kind of foundational work typically seen in new industries—not in a sector as established as construction.
According to Zurada, the reason this data infrastructure never developed is structural. Construction is highly fragmented, with thousands of regional contractors and no dominant national players. Unlike the real estate market, which a company like Zillow can aggregate, public construction lacks a single entity with both the incentive and the resources to build a comprehensive national database.
New Approaches to Price Discovery
PinPoint Analytics is addressing this gap with an AI-driven solution. The company uses machine learning models trained on historical bid data to predict winning prices for public construction projects. “We’re predicting the winning price of any public construction project in the country,” Zurada says, likening the approach to Zillow’s home value estimates.
Recently, PinPoint Analytics partnered with BidNet, which Zurada calls “the largest bid aggregator in the country” for public construction. The goal is to create a more comprehensive solution that helps contractors not only find projects but also price them more accurately using real market data.
Zurada reports strong interest from contractors who recognize the advantages of data-driven pricing. “The people that we do pitch to, it’s like an instant buy,” he says. “We’re selling very, very well, very easily.” The company is expanding from its New Jersey base, with plans to launch nationally in early 2026, targeting Florida, Texas, Pennsylvania, New York, and California as priority markets.
The Future of Data-Driven Bidding
Whether tools like those offered by PinPoint Analytics become standard across the construction industry will depend on how quickly contractors accept that working without market comparables puts them at a disadvantage—costing them either lost bids or lost profit margin on nearly every project.
As more contractors adopt these platforms, it is hoped that public construction bidding will move closer to the price transparency now standard in residential real estate. Until then, the industry will continue to grapple with unpredictable bid spreads, wasted effort, and profit margins determined as much by guesswork as by strategy.
