“We can be proactive and say, ‘In 12 months, we’ll have extra people that are very successful in remodels. Let’s go after some more remodels,’” says Daniel Barry, VP of Operations at Schimenti.
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That’s demand forecasting working the way it should. Barry isn’t guessing about capacity or hoping the pipeline aligns with his workforce. He’s looking at projected availability, seeing a surplus of specific expertise, and telling business development to go find work that fits. The pipeline shapes the pursuit strategy, not the other way around.
Most contractors work backward. BD chases opportunities. Operations figures out staffing after the win. If the timing works, great. If it doesn’t, someone gets pulled off another project or everyone works overtime until a new hire gets up to speed. 93% of construction leaders report labor shortages, which means that scramble is getting harder every year.
Demand forecasting flips the sequence. It projects future labor needs based on your pipeline, backlog, and project timelines, then compares that demand against your available supply. The gap between those two numbers tells you what’s coming: how many people you’ll need, which roles will be tightest, and whether you can realistically staff the work you’re pursuing.
Why demand forecasting matters for general contractors
Without demand forecasting, workforce decisions happen in the dark. You hire when projects are already understaffed. You pass on pursuits assuming you can’t staff them, without checking. You discover conflicts after commitments are made.
Jamie Miller, Director of Engineering Development at Sellen Construction, describes what this looked like before: “We have weekly meetings for business development and operations, and we would spend the operations meetings talking about staffing, not the business. We were too busy coordinating our different spreadsheets.”
That’s time that should go to strategy. Instead, it goes to figuring out basic facts that should already be visible.
The cost of reactive hiring
When you don’t see demand coming, hiring happens under pressure. A project needs a superintendent in three weeks. Your options are whoever happens to be available, not whoever is the right fit. You pay placement agencies premium rates for speed. You interview while a project waits.
The industry faces a projected shortfall of 499,000 workers. Finding good people takes time even under ideal conditions. Demand forecasting gives you that time by surfacing needs months before they become emergencies.
The cost of blind bidding
Every pursuit commits future capacity. Winning a project you can’t staff creates problems that ripple across your organization: the PM pulled off another project, the client whose schedule slips, the operations meeting spent figuring out how to cover commitments you shouldn’t have made.
Demand forecasting answers questions before you bid: Do we have the people if we win? What else gets affected? Would we need to hire, and is that realistic given the timeline? Without those answers, pursuit decisions are educated guesses at best.
How construction demand forecasting works
Demand forecasting translates project information into labor requirements. Every project needs people. The question is how many, in which roles, and when.
From projects to people
The starting point is understanding what labor each project requires:
| Factor | What to capture |
|---|---|
| Roles | Which positions does the project need? |
| Timing | When does each role need to be staffed? |
| Duration | How long will each role be needed? |
| Allocation | Full-time or partial? |
Aggregate these requirements across all projects and you get total demand by role and time period. That’s the demand side of the equation.
Probability weighting for pipeline opportunities
Demand from signed contracts is relatively certain. Demand from pursuits is probabilistic. A $50 million project at 10% win probability shouldn’t affect your forecast the same way as a $50 million signed contract.
Johnathon Grammer, Director of Operational Excellence at Rogers-O’Brien, describes how they handle this: “We’ve allocated resources to awarded projects and have all these ‘what if’ projects. We gauge project pursuits on their chances of winning. It allows us to consider multiple scenarios.”
| Demand source | Typical confidence |
|---|---|
| Active projects with current staff | 95%+ |
| Contracted backlog with set dates | 80-90% |
| Pursuits in final stages | 40-60% |
| Pursuits in early stages | 10-30% |
Probability-weighted demand keeps your forecast grounded instead of swinging wildly every time BD adds a new pursuit to the pipeline.
Supply meets demand
Demand forecasting is half the picture. The other half is supply: who do you have, and when are they available?
Comparing demand against supply reveals gaps and surpluses. A gap three months out means you need to hire, reassign, or reconsider what you’re pursuing. A surplus might mean you can bid more aggressively or pursue work you’d otherwise pass on.
Barry at Schimenti uses this for real-time visibility: “It shows our capacity in real-time. If you get asked by a board member or an owner, ‘How are we looking with capacity in two, three months?’ Bridgit Bench takes the guesswork out of it.”
Connecting business development to workforce planning
The most valuable application of demand forecasting is connecting your pursuit pipeline to workforce capacity. When those two systems talk to each other, pursuit decisions become workforce decisions.
Pipeline integration
When your CRM and workforce planning connect, pursuits automatically feed demand forecasting. Forecasting tools show how winning specific pursuits would impact capacity before you commit to bidding.
This changes the conversation. Instead of BD pursuing everything and operations figuring out staffing after the fact, both teams see the same picture. Pursuits get evaluated not just on margin and fit, but on whether you can actually deliver them.
Go/no-go decisions with real data
Before committing to a pursuit, demand forecasting answers:
- Do we have capacity to staff this if we win?
- Which other projects would be affected?
- Would we need to hire, and is there time?
- What roles would be most constrained?
Shawn Gallant, COO at Columbia Construction, describes the value: “Running scenarios where we can run specific projects like we’ve got 25 active projects and ten pursuits, 3 of which are 95%, so I can factor them into my forecasting. That’s priceless.”
Without this visibility, go/no-go is a gut call. With it, you’re making decisions with actual data about what winning would require.
Timing pursuits to capacity
When you can influence project timing, forecasts help identify optimal windows. If Q2 shows surplus capacity, accelerating pursuits that would land then makes sense. If Q3 is already constrained, pursuits landing then might get deprioritized or priced to reflect the strain.
This is how demand forecasting shapes strategy, not just operations. You’re not just reacting to what BD brings in. You’re pointing BD toward opportunities that fit your workforce reality.
Using demand forecasts for hiring decisions
Forecasts reveal when you’ll need people you don’t have. The question is what you do with that information.
Lead time planning
Hiring a senior superintendent might take four months between posting, interviewing, negotiating, and onboarding. If your forecast shows you need one in six months, recruiting should start now. If you wait until month five, you’re back to scrambling.
Barry at Schimenti describes what good looks like: “Bridgit Bench paints a picture of what we need to fill these slots with the right people. Bridgit Bench helps us grow responsibly and give HR the right facts so they know what we need and can recruit the right people.”
HR seeing the same forecast as operations means recruiting starts when it should, not when someone remembers to send an email.
Role prioritization
Not all hiring needs are equal. Forecasts show which roles face the largest gaps and which have adequate supply. A forecast showing three superintendent openings and one PM opening tells you where to focus recruiting energy.
Hiring versus alternatives
Forecasted demand doesn’t always mean hiring. Options include:
- Reassigning people from projects with surplus capacity
- Adjusting pursuit strategy to match available workforce
- Subcontracting specific roles or phases
- Partnering with other contractors on large pursuits
Demand forecasting provides lead time to evaluate options instead of defaulting to whatever’s fastest.
Maintaining forecast accuracy over time
Forecasts degrade without maintenance. The assumptions that were accurate three months ago may not hold today.
Regular refresh cycles
| Timeframe | Refresh frequency | Purpose |
|---|---|---|
| 0-3 months | Weekly | Near-term operational planning |
| 3-6 months | Monthly | Standard workforce forecasting |
| 6-12 months | Monthly | Strategic planning |
Each refresh incorporates new information: projects that started or ended, pursuits won or lost, timeline changes, staffing adjustments.
Variance tracking
Compare forecasted demand against actual outcomes. If you consistently overestimate, adjust probability weights down. If you consistently underestimate, adjust up. If certain project types always take longer than planned, build that into your duration assumptions.
The goal isn’t perfect accuracy. It’s accuracy good enough to make better decisions than you’d make without a forecast.
Assumptions that need checking
Common assumptions that drift over time:
- Win rates: Are your probability weights realistic?
- Durations: Do projects actually end when planned?
- Staffing curves: Do role requirements match historical patterns?
- Timing: Does backlog start when expected?
Invalid assumptions produce invalid forecasts. Checking them periodically keeps the model honest.
Building forecasting into your workflow
Forecasts create value when they inform decisions that are already happening.
Staffing meetings
Reference forecasts when discussing assignments. What does the forecast say about next quarter? Are current staffing decisions creating bottlenecks three months out? Regular review keeps forecasts useful and surfaces problems while there’s still time to act.
Pipeline reviews
Include forecast implications in pipeline reviews. How does current pipeline compare to capacity? Which pursuits would create significant resource strain? This connects BD and operations around the same data.
Executive reporting
Leadership needs forecast visibility for strategic decisions. Melissa Hockey, People and Culture Manager at Mosaic Property Group, describes the shift: “Bridgit has given us a level of insight into our workforce planning that we simply didn’t have before. This visibility is now critical for making proactive decisions about resource allocation and future growth.”
When executives can see the capacity outlook, conversations about growth strategy become grounded in workforce reality.
Getting started with construction demand forecasting
Most contractors do well with a rolling 12-month forecast updated monthly. The first three months should be accurate within 10-15% of actual headcount. Months 4-6 should be within 20%. Beyond that, scenario ranges matter more than point predictions.
Start with the data you have. Current assignments, project schedules, and headcount by role are the minimum. Add pursuit pipeline with probability weighting when you can. Add historical duration data to improve timeline assumptions. The forecast gets better as input quality improves.
For contractors managing workforce planning in spreadsheets, the first step is often consolidating scattered information into a single view. Construction forecasting tools connect projects, people, and pipeline in one place, with pursuit tracking that shows how potential wins would affect capacity.
The contractors who forecast well share a common trait: they use forecasts to make decisions, not just to produce reports. Forecasts inform what they pursue, when they hire, and how they allocate people across projects. That discipline, connecting planning to action, is what turns demand forecasting from an exercise into a competitive advantage.
