In early 2025, the FHWA published a US DOT Office of the Inspector General study that revealed one-third of federal highway project bids are impacted by complementary bids. Based on seven years of historical data, the report estimated that the cost of these anti-competitive bidding practices is approximately $ 1.19 billion. In order to identify and prevent anti-competitive bidding practices, the report recommended the following:
- Frequent, regular, and systematic reviews of procurement data
- Use of specific statistics to identify potential anti-competitive patterns
- Reduction of reliance on historical data when developing engineers’ estimates
How are DOTS that are ahead of the curve approaching the identification and prevention of anti-competitive bidding behavior? We sat down with Tim Pritchard of Ohio DOT’s Office of Estimating and Jeff Hisem, former ODOT Estimator, to find out.
This interview has been edited for brevity and clarity. The full discussion is available here.
What was the origin of bid analysis at the Ohio DOT?
Hisem: In my 36-year tenure at the DOT, the approach to bid analysis evolved a great deal, to the point where our estimators now understand that they also need to be analysts of bids and estimates and to properly determine reasonability.
This change happened in part as a result of using AASHTO’s software tools that helped us understand contractors’ bidding patterns. In 2004, our local paper published an article questioning whether the DOT was doing all it could to ensure contractors were bidding properly. Our Director at the time called me into his office, and after much discussion, it led to the hiring of two full-time people devoted to managing the data and providing for long-term bid analysis for bid rigging and collusion detection.
We named this group the Bid Analysis and Review Team, or BART. We did not use the Simpsons character as our mascot. BART has been in existence now for over 20 years.
How does ODOT approach pre-award analysis?
Hisem: The estimators’ responsibility is to create a benchmark estimate of a bid project, and after the bids are opened, analyze those bids and estimates again to determine how their bidding activity would influence award and rejection decisions.
This is a day-to-day pre-award analysis of contractors’ bids for all the project bid openings throughout the year, and is specifically focused on providing information to the Award Committee. The Award Committee meeting is generally 10 days after the bid opening, and at that point in time, the vast majority of those projects are either awarded or rejected.
We told our estimators, “It’s not your job to figure out who needs to get the project. It’s your job to figure out what the bids are telling you about their activity, where there are unbalanced bids, and where the bids just don’t seem to make sense.”
They are heavy users of AASHTOWare Project Data Analytics and use the software live in award meetings to point out all kinds of questionable bidding activity that could impact the award or rejection process.
How does ODOT approach big-picture, long-term market analysis?
Pritchard: We have to get away from the conveyor belt of projects. We have a different perspective. We’re looking at bids much more long-term, sometimes it’s called long-term market analysis. Anywhere from one, three, five, seven, upwards of ten years if you’re really going to do collusion detection.
We look at market behavior and how it changes over time, and also how it changes in specific areas of our state. We do a lot of ad hoc work, too, because collusion detection sometimes requires some flexibility in approach.
We couldn’t do our work without the work our engineers and analysts who are doing the engineers’ estimate do. They see things emerging in real-time that inform me before I even get started.
But this type of work requires deep dives into the data that are best done without the consistent drumbeat of the project conveyor belt.
Is ODOT’s data analysis focused primarily on bidding data?
Pritchard: Early on, we wanted to build a team that did a variety of work. We’re analysts first, who happen to do collusion detection and monitoring of bidding behavior. Our bread and butter data is the bidding data, but we have branched out many times.
As one example, I like to screen for antitrust violations for mergers and acquisitions. When I hear about a merger or acquisition in one of our suppliers or one of our bidders, I’m interested in that. We’ll do some analysis to see if that’s going to reduce competition in a meaningful way. And if it does, then I take it to an investigative authority.
What is ODOT’s methodology for collusion detection?
Pritchard: This is Infotech’s methodology, and I follow it very closely. It always starts with data work, and really, that never ends. We have to make sure that our data is analysis-ready. We work really hard at getting a single point for location for these projects, because that’s really important for mapping.
If we’re going to do analysis, the first thing we do is define our analytical markets. For something like bridge painting, it’s not statewide, it’s really a regional thing, so we’ll define the analytical market. It’s all based on who bids against whom. AASHTOWare Project Data Analytics has some really great tools for defining analytical markets.
Once we have the analytical markets, we analyze market shares. Which contractors are getting the lion’s share of the work? And we’re looking for red flags. Are they stable market shares over time? If so, that’s a bad thing. If we get the rock and roll of competition, then everybody’s happy.
Then, vendor competition analysis. That is looking at winning percentages, and sometimes, losing percentages. Do we have a bidder who’s putting in bids all the time and never winning? That’s always suspect.
There is no such thing where you push a button and it tells you you’ve got collusion. That’s not how this works. We’re looking for red flags. We’re looking for areas of concern.
Finally, there’s contract analysis, pricing analysis, and contract modification analysis, which is really change order analysis. There are some tools in AASHTOWare Project Data Analytics for doing that, but that’s also where we start getting into customizing an ad hoc analysis depending upon the market.
What kind of training has helped ODOT develop in this area?
Pritchard: What got me started was the Market Analysis Training from Infotech. I went to the Collusion Detection Seminar in Gainesville. That sort of was a prerequisite for doing this work. What was nice about that was getting to know other people who are doing this type of work. And of course, we also learned tips and tricks. It was important for really getting hands-on and understanding what it meant to do this type of work.
Can you share any wins that have come from ODOT’s market analysis?
Pritchard: When we started, our Director wanted to know about asphalt markets. I started in April. By January of that first year, we were presenting to the director what we had found. We’ve revisited the asphalt markets many times, because that’s where the money is. We spend a whole lot of money on asphalt every year, so it’s really important to keep an eye on that market
Over time, we’ve become experts in construction cost trends. We do a construction cost inflation forecast now. And that is a very important part of how we’re known within our department.
Hisem: We were a little reluctant to do that first cost index, and now the department is doing them quarterly. You can find them on ODOT’s website. It includes a lot of information about how those costs came to be and how ODOT went about performing the cost indexing.
What recommendations do you have for other agencies?
Pritchard: You have to invest time in the data infrastructure. That means doing the data work. It takes time and energy to fix stuff that is broken. Keep the conveyor belt at bay, because it takes time and energy to focus on the analysis outside of the deadlines. And then, leveraging the available tools, I think AASHTOWare Project Data Analytics is a great tool to use. It does make things easier, and it does provide lots of insights.
If you want to hear our full conversation with Tim Pritchard and Jeff Hisem, it’s available here. To learn more about how Infotech works with DOTs to grow their data analysis expertise and find insights in their data, explore our Data Services.
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Nate Binder
Digital Marketing Manager
A proud graduate of Florida State University, Nate works with subject matter experts and sales professionals to produce targeted marketing collateral.