InEight (online), September 24, 2025
News Summary
Construction projects often start ‘awash in optimism,’ but unchecked optimism bias can undermine budgets and schedules. The article recommends treating optimism as a managed risk by validating assumptions with detailed, real-time data, reference-class forecasting, benchmarking and performance metrics like earned value. Accurate quantity management and linking estimates, budgets and schedules to short-interval planning improve forecast reliability. Tracking change orders, RFIs, contract deliverables, timesheets and payments supports realistic assessments. Software platforms that centralize historical and as-built data enable better comparisons and timely adjustments. Bottom line: back optimism with data to protect outcomes and improve project performance.
Bias busting for construction project excellence
How optimism can hurt budgets and timelines — and what to do about it
By InEight • 4 min read • 09/23/25
Categories: Infrastructure, Construction • Image credit: Vilkasss/Pixabay
Top line
Construction projects commonly launch awash in optimism, and when that optimism turns into unconscious optimism bias it can undercut budgets and schedules. The prescription presented here is simple: optimism in construction requires realism, and realism starts with shared, reliable data and disciplined forecasting.
Why this matters
Contractors are selected with care, roles are assigned, and goals are clear and incentivized, yet projects still face cost and time shortfalls because optimism bias is often unseen. Optimists tend to be driven, cool under pressure and resilient, qualities that make strong project leads, but research shows project leaders are largely unaware of the potential negative impact optimism bias on project budgets and deadlines. That blind spot can let predictable issues slip through early planning.
Common optimism bias blind spots
- Potential labor disputes
- Site-specific challenges
- Regulatory complications
This is not a call to run projects by pessimists. Biases of any kind can be problematic, especially when unacknowledged. The types of biases most likely to affect projects are organizational, leadership, group and human biases. It is impossible to entirely remove bias, but a practical, stepwise approach reduces its impact.
Practical steps to reduce bias
First step: raising awareness of the bias. Second step: challenging the bias. The easiest way to manage project bias is to check it against measurable information. If optimistic budget assumptions are proven by the numbers, then data-supported optimism may be warranted. If optimistic assumptions are not supported by data, there may still be time to adjust the budget. Framed this way, managing optimism bias is less about managing a disposition and more about managing risk.
Data and controls that work
The best construction insights are data-driven. Shared, real-time data forms the foundation for trusted performance monitoring. Diverse project stakeholders are more likely to make decisions based on insights when they have a data platform. The most relevant data for supporting or correcting optimism ties directly to either the project schedule or budget. Detail and accuracy are necessary counterparts to the potential distortion of unwarranted optimism.
Starting with highly detailed data results in more accurate analysis, forecasting and progress tracking. Accuracy starts with project setup and data collection practices. Justin Terminalla, Kiewit Industrial Vice President, said that fundamentally, if your quantities in scope are wrong, your forecast is inherently going to be wrong as well. Kiewit standardizes processes around controlled management of pure quantities, ensuring they are entered into the system at the right time and that everything else is a by-product of quantity management.
Reference class forecasting is identified as a useful control mechanism. Reference class forecasting involves comparing historical, similar project data with current project data to make forecasting and scheduling more accurate and to help if budgets or schedules must shift. Software systems that include benchmarking, quick access to historical and as-built data and native support for sophisticated work demands can help manage optimism bias.
Advanced performance management practices that support realistic project assessments include earned value management and schedule performance index. Ricardo Filho, CCC Group Director of Project Controls, said that General rule of thumb, I’d say that 75 to 80% of the effort of forecasting really happens in the system. And then based on project knowledge, the team tweaks and fine-tunes by applying context. If the remaining work is more complex than previous projects, CCC Group will further scrutinize the previous forecast.
What to track
The right data makes for great project outcomes. Track items that directly reveal changing scope and friction: change orders, RFIs requests for information, contract deliverables, and quantity claims. Track budgetary signals as well: timesheets, payments and billings. A thorough assessment of data needs should be followed by a clear-eyed look at what it takes to collect accurate and detailed information.
Rouan du Rand, Redpath Mining Vice President, Project Services, advised that You have to find ways to connect your estimate, your budget, and your schedule to your short interval planning and controls effort. His reason for that connection is so construction teams can focus on the work they must be doing and not evolve into things they like to do. He also advised to collect your data as close as possible to the workplace, because that’s where the work gets done.
Excellent data sets serve multiple downstream use cases, including integrated forecasting, ERT scheduling, managing contract life cycles, estimating financial impacts and collaborating among stakeholders. Optimism may be warranted, but it never hurts to back it up with a quick check on the data.
Tags and navigation
Tags: #budget #construction #data #forecast #optimism bias #project management #schedule #timeline
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Platform and provider facts
Construction By InEight
InEight is a leader in construction project controls software. InEight empowers over 850 companies taking on challenging projects in industries including construction and engineering; transportation infrastructure; mining; water; power and renewables; and oil, gas and chemical. Its software is uniquely suited to capital construction and other complex work. The integrated, modular software manages projects worth over $1 trillion globally. The software takes control of project information management, costs, schedules, contracts, and construction operations, and delivers insights with advanced analytics and AI. The solutions adapt and scale to meet the dynamic needs of modern construction, driving operational excellence and successful project outcomes. For more information, follow InEight on LinkedIn or visit InEight.com.
Frequently Asked Questions
What is the main risk of starting a construction project with optimism?
Construction projects commonly launch awash in optimism, and when that optimism turns into unconscious optimism bias it can undercut budgets and schedules.
What first steps reduce optimism bias?
First step: raising awareness of the bias. Second step: challenging the bias. The easiest way to manage project bias is to check it against measurable information.
How does data help manage optimism bias?
The best construction insights are data-driven. Shared, real-time data forms the foundation for trusted performance monitoring.
What did Justin Terminalla say about quantities and forecasting?
Justin Terminalla, Kiewit Industrial Vice President, said that fundamentally, if your quantities in scope are wrong, your forecast is inherently going to be wrong as well.
How does Kiewit manage quantities?
Kiewit standardizes processes around controlled management of pure quantities, ensuring they are entered into the system at the right time and that everything else is a by-product of quantity management.
What is reference class forecasting?
Reference class forecasting involves comparing historical, similar project data with current project data to make forecasting and scheduling more accurate and to help if budgets or schedules must shift.
What did Ricardo Filho say about forecasting effort?
Ricardo Filho, CCC Group Director of Project Controls, said that General rule of thumb, I’d say that 75 to 80% of the effort of forecasting really happens in the system. And then based on project knowledge, the team tweaks and fine-tunes by applying context.
What practical advice did Rouan du Rand give?
Rouan du Rand, Redpath Mining Vice President, Project Services, said You have to find ways to connect your estimate, your budget, and your schedule to your short interval planning and controls effort. He also advised to collect your data as close as possible to the workplace, because that’s where the work gets done.
What is the practical closing recommendation?
Optimism may be warranted, but it never hurts to back it up with a quick check on the data.
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Key features at a glance
| Feature | Purpose | Examples or items to track |
|---|---|---|
| Real-time, shared data | Foundation for trusted performance monitoring | Timesheets, payments, billings |
| Reference class forecasting | Compare historical projects to current project for better forecasts | Benchmarking, as-built data |
| Quantity control | Ensure forecasts start from accurate scope quantities | Pure quantities entered at the right time |
| Performance management metrics | Measure schedule and budget health | Earned value management, schedule performance index |
| Tracking scope signals | Detect changes that affect budget and timeline | Change orders, RFIs, contract deliverables, quantity claims |
Deeper Dive: News & Info About This Topic
Additional Resources
- InEight Blog
- Wikipedia: Optimism bias
- Engineering News-Record (ENR)
- Google Search: reference class forecasting construction
- Construction Dive
- Google Scholar: earned value management construction
- American Society of Civil Engineers (ASCE)
- Encyclopedia Britannica: forecasting
- McKinsey — Capital Projects & Infrastructure
- Google News: construction project data optimism bias
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