How to Improve Project Controls in Construction: 5 Changes That Make a Difference

Dr. Asif Sharif holds a Ph.D. in International Procurement Strategies and has spent over 25 years working across construction and cloud computing.

A 2025 McKinsey review of more than 300 billion-dollar-plus megaprojects found average cost overruns of 80% and schedule delays of 50%, with poor data sitting squarely at the centre of most of those failures.

There’s a reason project teams have failed to achieve on-time and on-budget projects for decades, even with the sophisticated tools available to them. The root cause is almost always problematic data. Most poor decisions, missed signals, and flawed forecasts can be traced back to unreliable or incomplete project data that produced faulty insights that led to faulty decisions.

Improving project controls, and ultimately project performance, means fixing the data first. When the data is accurate and reliable, teams get better project intelligence, make better decisions and achieve better outcomes.

How Can Teams Improve Their Project Controls?

Improving project controls starts with fixing the project data environment, and requires five structural changes:

Aligning schedule and cost structures
Standardising project data definitions
Establishing ownership of project data
Improving forecasting and reporting
Connecting project controls systems.

So where do you start? For most organisations, the answer is the same place the problem begins: the structure of the data itself.

Change 1: Align Schedule and Cost Structures

When the Work Breakdown Structure (WBS) in your scheduling tool does not match the cost code hierarchy in your cost management system, earned value analysis becomes manual and error-prone.

What alignment requires:

A common WBS mapped consistently across scheduling and cost systems
Cost codes linked to schedule activities or control accounts
Consistent progress measurement methods for both schedule and cost
Maintained alignment when scope or schedules change

Structural alignment is what makes earned value reporting trustworthy — and reliable reporting is what gives project teams the accurate picture they need to improve performance.

Change 2: Standardise Project Data Definitions

When one project team defines Estimate to Complete (ETC) differently from another, or contractors measure schedule progress differently than the owner, programme-level reporting becomes meaningless.

Standardisation should cover:

Forecasting methods: how ETC, Estimate at Completion (EAC), and Variance at Completion (VAC) are calculated
Progress measurement: how percent complete is determined for schedule activities and cost accounts
Performance metrics: how Schedule Performance Index (SPI) and Cost Performance Index (CPI) are reported
Risk impacts: how risk events are quantified and reflected in forecasts

Consistent standards mean a cost report from one team means the same thing as one from another — the precondition for any meaningful programme-level performance conversation.

Change 3: Define Accountability for Project Data

Aligned structures and standardised definitions only hold if someone is accountable for maintaining them. Without a clear data governance strategy, WBS structures diverge across projects, cost hierarchies drift, and forecasting logic varies by team.

Governance requires:

A designated owner for the project data model and reporting standards
Defined authority over WBS structures, cost hierarchies, and forecasting logic
A review process for data structure changes across systems
Enforcement of standards across contractors and project teams

The goal isn't necessarily a single owner — on large programmes with multiple contractors and systems, accountability is often distributed. What matters is that there are no blind spots. Every part of the data model needs someone watching it, because the places where nobody is accountable are exactly where standards quietly erode.

Change 4: Automate Forecasting and Reporting

When data is aligned and governed, forecasting improves — but manual reporting processes are where data quality goes to die. Most organisations still produce forecasts through spreadsheet reconciliation: pulling numbers from one system, reformatting them, pasting them into another. Every step introduces lag, inconsistency, and human error.

More reliable forecasting requires:

Integrated and continuous inputs from schedule, cost, and risk systems
Consistent reporting logic across all projects and programmes
Reduced reliance on manual reconciliation
Unified programme-level visibility

That shift moves project controls from a reporting function to a decision-support function, which is where it can actually influence project outcomes.

Change 5: Connect Project Controls Systems

Of the five changes, this one warrants the most depth, because system integration is where most organisations struggle the most, and where the gap between knowing what to do and knowing how to do it is widest.

What Does Connecting Project Controls Systems Mean?

Connecting project controls systems means using data integration tools to link scheduling, cost management, risk, and analytics tools so that data flows automatically between them. Instead of exporting a schedule update from Primavera P6, reformatting it in a spreadsheet, and importing it into a cost system, connected systems exchange data directly, eliminating the reconciliation burden.

Why Disconnected Systems Are a Project Controls Problem

Data latency. Manual transfers introduce delays. By the time a cost report reflects the latest schedule update, the schedule may have changed again. Teams make decisions on data that is days or weeks out of date.
Reconciliation burden. Project controls engineers often spend the majority of their reporting cycle reconciling data rather than analysing performance.
Inconsistent baselines. Without a shared data structure, maintaining a consistent performance baseline is difficult. Change management becomes manual and earned value analysis loses reliability.
Limited programme visibility. Disconnected systems require manual consolidation for programme-level reporting, adding inconsistency and delay at every level.
AI and analytics barriers. AI tools require clean, consistent, timely data. Disconnected systems produce the opposite.

What Good Integration Looks Like in Practice

Automated data flows. Schedule updates, cost actuals, and risk changes flow between systems automatically on a continuous basis, on demand, or event-triggered.
Shared data structures. A schedule activity in P6 maps directly to a cost account in the cost system. Progress updates in one system are reflected accurately in the other.
Unified reporting layer. Integrated environments support dashboards that draw from both systems simultaneously. Programme managers see one version of project performance.
Change propagation. When scope changes, both systems reflect it consistently. Change management is supported by the integration rather than working around it.
Audit trails. Data flow records support governance, claims management, and owner reporting.

When systems are connected, what leaders see in their reports actually reflects what is happening on the project. That is the foundation every other improvement in this list depends on.

The Real Starting Point for Better Project Controls

Most organisations trying to improve project controls start by adding something — a new tool, a better dashboard, another analytics layer. The five changes above suggest a different starting point: before you add anything, fix what the data is telling you. Clean, connected, consistently governed project data doesn't just improve reporting. It changes what your team is able to see, decide, and do. That's where project performance actually improves.

See What Better Project Controls Data Looks Like

If any of the five changes above describe where your programme is struggling, we're happy to walk through what fixing it looks like in practice. Talk to our team today to discuss your environment.

Frequently Asked Questions

What are project controls in construction? Project controls are a set of data-driven processes, tools, and techniques used to plan, monitor, and manage a project's cost, schedule, and scope. Acting as a project’s navigation system, they provide actionable insights to keep projects on track and ensure they are delivered on time and within budget.

Why are project controls important in construction projects? Project controls are important because they provide visibility into project performance. By integrating schedule, cost, and risk data, project controls help teams identify issues early, improve forecasting, and make more informed decisions.

How do you improve project controls in construction? Improving project controls involves aligning schedule and cost data, standardising data definitions, establishing clear data ownership, and connecting systems used to manage project performance. These practices help create more reliable reporting and forecasting.