Forecasting is the foundation of any successful construction company’s stability — it informs hiring decisions, project bids, cash flow planning, and risk management. When forecasting is built on inconsistent or outdated financial data, it puts companies at risk of budget overruns, misallocated resources, and lost profitability.

Today, industry research shows that only 8.5% of infrastructure projects finish on time and within budget.¹ Without structured, timely, and accurate financial data, even the most experienced CFO is left making educated guesses rather than informed decisions.

This article addresses the limitations of intuition-based planning, highlights the risks of fragmented financial data, and outlines actionable steps to transition to a data-driven forecasting model that enhances financial stability and decision-making.

Making the Shift

Intuition-driven forecasting can be inconsistent. One project manager (PM) may underestimate costs to stay competitive, while another builds in excessive buffers that inflate project budgets.

Without a standardized forecasting approach, these variations create financial blind spots that ripple across organizations, leading to cash flow uncertainty and costly miscalculations.

Historical data proves this volatility. In a study of 500,000 project schedules, it was found that 14% of activities were delayed by at least 100%, while over 1% of tasks took 20 times longer than planned.²

Fragmented data compounds this issue. Many companies still operate with financial information scattered across spreadsheets, disconnected accounting software, and project management tools that don’t talk to one another. And when forecasting models are built on incomplete or outdated information, even the most experienced professionals can find themselves making the wrong call.

Companies that build a culture of data-driven forecasting can embrace:

• Capturing financial knowledge in structured data, ensuring that forecasting models and historical trends don’t disappear when leadership changes.
• Training senior professionals on modern financial tools, so they can document and pass on their expertise through data-backed systems.
• Knowledge-sharing between seasoned leaders and younger employees, so the next generation isn’t left to start from scratch.
• Standardizing forecasting methods across departments, so decision-making is consistent, transparent, and scalable across teams.

By reducing the dependency on a handful of experienced team members, companies ensure forecasting remains accurate, proactive, and resilient — no matter who is in charge.

Data Challenges in Construction

Not all financial data carries equal weight in forecasting. While construction companies generate an enormous amount of project information daily, much of it remains fragmented, inconsistent, or outdated — making it unreliable for financial planning.

Poor data management has massive financial consequences — IBM estimates that bad or incomplete data costs U.S. businesses up to $3.1 trillion annually.³

The most common challenges caused by disorganized data are inconsistent cost categorization, duplicate or missing entries, disconnected financial systems, and delayed financial updates. Each of these issues ties back to inadequate data management.

Cost Categorization

In situations of inconsistent cost categorization, different project managers can log similar expenses under varying categories, making company-wide financial comparisons nearly impossible.

A structured cost categorization system can ensure financial clarity, while seamless integration with enterprise resource planning (ERP) platforms prevents data silos from distorting financial reports.

Duplicate or Missing Entries

Manually recorded expenses create discrepancies in reconciliation and reporting.

Without routine validation, errors such as duplicate cost entries, missing transactions, and incorrect categorizations creep into financial records, resulting in unreliable forecasts.

Disconnected Systems

Separate accounting and project management tools create financial silos, limiting visibility and oversight.

Delayed Financial Updates

Construction projects frequently face delays driven by poor data visibility, including issues with staffing, materials, and equipment. When data isn’t captured in real time, forecasts become outdated before they’re even finalized.

In forecasting, data delays can hinder decision-making, leading to missed financial targets and cash flow issues. Manual data entry remains a major obstacle for many companies; if expense tracking is delayed, for example, then companies may unknowingly overcommit resources or postpone vendor payments, putting cash flow at risk.

Key Principles for Organizing & Maintaining Clean Data

Creating a Standardized Framework

Reliable forecasting starts with a disciplined approach to financial data management. In construction, where costs shift daily and projects last months or even years, structured, real-time financial records are non-negotiable.

By implementing stronger data governance, automated validation tools, and financial integration solutions, companies can eliminate forecasting blind spots and gain clearer financial visibility — ensuring every financial decision is based on real, reliable numbers.

When teams record costs inconsistently — for example, one listing subcontractor payments under “labor,” while another lists it under “subcontractor services” — company-wide financial comparisons become unreliable. These discrepancies make it nearly impossible to track spending patterns or ensure accurate cost projections.

A standardized approach eliminates this uncertainty. Establishing clear cost categories, enforcing structured reporting guidelines, and using automated 
validation tools creates a uniform financial language across projects. It ultimately results in improved project profitability insights, more precise forecasting, and greater financial control at every level of the business.

Eliminating Data Silos

Disconnected financial systems create blind spots in forecasting. Relying on a mix of spreadsheets, separate accounting software, and project management tools that don’t communicate with each other is reactive financial planning — when budgets are adjusted after issues arise.

Integrated financial systems break down these silos. A cloud-based accounting platform ensures that financial data is always up to date and accessible across teams. Real-time synchronization among accounting, project management, and procurement tools eliminates manual reconciliation errors, keeping finance teams aligned with on-the-ground project conditions.

Maintaining Data Integrity

Even the best financial systems require oversight. Without active data governance, errors accumulate, leading to budget overruns, cash flow issues, and forecasting inaccuracies.

Effective governance starts with regular financial audits. Instead of waiting for errors to surface in quarterly reports, companies can implement continuous data monitoring to catch discrepancies before they distort financial models.

Automated compliance tools flag duplicate transactions, missing entries, and inconsistencies in real time, reducing the risk of flawed forecasts.

Access controls add another layer of protection, ensuring that only authorized personnel can make financial adjustments, reducing the likelihood of manual errors or unauthorized changes.