Bias busting for construction project excellence

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 • 09/23/25 • 4 min read

Categories: Infrastructure, Construction

Image credit: Vilkasss/Pixabay

Lead

Construction projects often launch awash in optimism. That optimism can be an asset — but it can also become a hidden source of unconsciously biased decisions, commonly called optimism bias, that undermine budgets and schedules. The clearest immediate remedy is to pair optimism with realism and measurable information so project teams can make timely, evidence-backed adjustments.

Key risks and blind spots

Project teams generally select contractors with care, assign roles and set clear, incentivized goals. Yet research shows many project leaders are largely unaware of how optimism bias can affect budgets and deadlines. Typical optimism-bias blind spots include potential labor disputes, site-specific challenges, and regulatory complications. The discussion that follows focuses on ways to recognize and manage these blind spots without endorsing a pessimistic approach.

What to do first

The article frames managing optimism bias as more about managing risk than managing personality. It notes that biases of any kind can be problematic, especially when unacknowledged, and that it is impossible to entirely remove bias. The recommended starting point is to raise awareness of the bias, then challenge it. The simplest practical step is to check optimism against measurable information. If optimistic budget assumptions are proven by the numbers, data-supported optimism may be justified. If they are not, there may still be time to adjust the budget.

Data, detail and controls

The article asserts that the best construction insights are data-driven and that shared, real-time data forms the foundation for trusted performance monitoring. Diverse project stakeholders are more likely to act on insights when they have access to a common data platform. The most relevant data ties directly to the project schedule or budget, and detail and accuracy are necessary counterparts to the potential distortion of unwarranted optimism.

Accuracy begins with project setup and disciplined data collection practices. Starting with highly detailed data results in more accurate analysis, forecasting and progress tracking. Reference class forecasting is identified as a useful control mechanism: it compares historical, similar project data with current project data to improve forecasting and scheduling, and to guide adjustments when budgets or schedules must shift.

Systems and methods that help

Software systems that include benchmarking, quick access to historical and as-built data and native support for complex work demands can help manage optimism bias. Advanced performance management practices mentioned as supporting realistic assessments include earned value management and schedule performance index.

One industry executive explained that if quantities in scope are wrong, forecasts will be wrong as well, and that standardizing processes around the managed capture of quantities ensures data integrity. Another project controls leader described the forecasting process as largely happening in the system, with the team then tweaking forecasts based on project knowledge and context. A project services executive advised connecting estimate, budget, and schedule to short-interval planning and controls, and to collect data as close as possible to the workplace.

Items worth tracking

The article lists items useful for checking optimism against reality: change orders, RFIs (requests for information), contract deliverables and quantity claims. Budgetary items to monitor include 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. Excellent data sets serve multiple downstream uses, including integrated forecasting, ERT scheduling, contract lifecycle management, estimating financial impacts and stakeholder collaboration.

Practical close

Optimism may be warranted, but it never hurts to back it up with a quick check on the data.

Page and footer facts

Corporate product and scope claims (reported)

Hashtags

#budget #construction #data #forecast #optimism bias #project management #schedule #timeline

FAQ

Q: What is the headline on the page?

A: Bias busting for construction project excellence

Q: What is the subheadline?

A: How optimism can hurt budgets and timelines — and what to do about it

Q: Who is the visible author credit at the very top?

A: By InEight

Q: What is the page date shown?

A: 09/23/25

Q: What estimated read time is shown?

A: 4 min read

Q: What page categories/tags are shown near the top?

A: Infrastructure and Construction

Q: What opening factual claims are presented?

A: Contractors are selected with care; roles are assigned; goals are clear and incentivized.

Q: What common project condition is stated?

A: Construction projects commonly launch awash in optimism.

Q: What are common optimism-bias blind spots listed?

A: Potential labor disputes, site-specific challenges, and regulatory complications.

Q: What is the first step to mitigate bias, according to the article?

A: Raising awareness of the bias.

Q: What is the second step to mitigate bias?

A: Challenging the bias.

Q: What practical closing statement does the article include?

A: 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 What it helps with Why it matters
Shared, real-time data Trusted performance monitoring Enables stakeholders to act on the same evidence
Reference class forecasting Improved forecasting and schedule accuracy Uses historical similar projects to correct optimism bias
Detailed quantity management Accurate forecasts Forecasts depend on correct scope quantities
Performance metrics Realistic project assessments Includes earned value management and schedule performance index
Trackable items Budget and schedule verification Change orders, RFIs, contract deliverables, quantity claims, timesheets, payments, billings

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