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Missing Numbers: A QS Guide to Resource Tracking
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8 min read
September 20, 2024

Missing Numbers: A QS Guide to Resource Tracking

Missing Numbers: A QS Guide to Resource Tracking
William Doyle
William Doyle
CEO at Gather
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The Data Foundation Problem

Every quantity surveyor knows the frustration. You're preparing a claim for additional resources deployed on a variation. You know extra labour was brought in. You know additional plant was hired. But when you try to substantiate the numbers, the data isn't there.

The allocation sheets are incomplete. The timesheets don't differentiate between planned and additional resources. The plant records don't show what was deployed where. You're left building a claim on estimates and assumptions rather than facts and evidence.

This isn't a QS problem. It's a data capture problem. And it starts long before the claim.

What Resource Tracking Should Capture

Effective resource tracking answers six questions for every resource deployed:

  • What? The specific resource (person, machine, material)
  • Where? The location of deployment
  • When? Start time, end time, duration
  • Why? The activity or instruction driving deployment
  • Who instructed? The authority behind the deployment
  • Which cost code? The budget or variation it charges to

Miss any of these and commercial recovery becomes harder. Miss several and it becomes nearly impossible.

The Common Gaps

When we audit resource tracking systems, the same gaps appear repeatedly:

The Allocation Gap

Timesheets capture total hours worked, but not how those hours were allocated across activities. Twenty operatives worked ten hours each. That's 200 hours. But which activities consumed those hours? Without allocation data, you can't prove additional resources were deployed on variations.

The Instruction Gap

Resources get deployed based on verbal instructions, but those instructions aren't captured. The PM said "throw more labour at it." Where's the record? Without documented instructions, additional resources look like contractor inefficiency rather than client-caused acceleration.

The Location Gap

Plant moved around site, but records show only that it was "on site" not where it was working. When you need to prove equipment was deployed on a specific variation area, "on site" isn't evidence.

The Baseline Gap

You can prove current resource levels, but can you prove what the baseline should have been? Without clear planned versus actual comparison, claims for additional resources lack foundation.

The Commercial Impact

Each gap translates directly to commercial exposure:

Allocation gap: Can't substantiate acceleration claims. £50-100K exposure per major variation.

Instruction gap: Additional resources attributed to contractor inefficiency. Margin erosion of 2-5% on affected work.

Location gap: Can't link resources to specific variations. 30-50% reduction in variation recovery.

Baseline gap: Claims rejected for lack of comparison. 40-60% of legitimate entitlement unrecovered.

Building Better Resource Tracking

Closing these gaps requires deliberate systems:

1. Daily Allocation Discipline

Every operative, every piece of plant, allocated to specific activities or cost codes daily. Not weekly. Not retrospectively. Daily, at source, by people who know what resources worked where.

2. Instruction Capture

Any instruction to deploy additional resources gets documented immediately. Who said it, when, what resources, what purpose. Even verbal instructions get confirmed in the daily diary.

3. Location Specificity

Plant records include location of deployment, not just presence on site. Grid references, chainage, or area descriptions that allow resources to be linked to specific works.

4. Baseline Documentation

Planned resource levels captured at project start and updated with programme. This creates the comparison point that makes "additional" claims meaningful.

The Role of Technology

Modern site management tools can automate much of this capture. GPS tracking for plant. Digital timesheets with activity allocation. Photo evidence with location stamps. Integration between site records and commercial systems.

But technology only captures what it's configured to capture. The design of the system determines the data it produces. If your tools don't prompt for allocation, location, and instruction, they won't capture them.

What Your QS Needs to Ask

If you're a QS trying to improve resource data, ask these questions:

  • Can I see exactly which activities consumed today's resources?
  • Can I prove additional resources were instructed versus voluntarily deployed?
  • Can I link specific plant and labour to specific variation locations?
  • Can I demonstrate the delta between planned and actual resources?

If the answer to any of these is "not really," you have a data gap that will cost you money.

The Investment Case

Better resource tracking takes effort. Daily discipline. System configuration. Training. Is it worth it?

Consider a typical infrastructure project with £500K of potential acceleration and disruption claims. With poor data, you might recover 30%, approximately £150K. With strong data, recovery rates of 75%+ are achievable, approximately £375K+. The £225K difference justifies significant investment in data capture.

What This Means for Your Projects

Your CVR is downstream of your data. Weak data means weak commercial positions, regardless of QS competence. Strong data enables strong claims, even when resources are stretched.

The investment in resource tracking isn't administrative overhead. It's commercial infrastructure. And like all infrastructure, it pays returns long after the construction cost is forgotten.

Close the gaps. Capture the data. Watch your recovery rates transform.

Key Takeaways

  • Resource tracking should answer six questions: what, where, when, why, who instructed, and which cost code
  • Common gaps include allocation, instruction, location, and baseline documentation
  • Each gap translates to specific commercial exposure ranging from 30% to 100% reduction in recovery
  • Solutions require daily allocation discipline, instruction capture, location specificity, and baseline documentation
  • Better data can transform recovery rates from 30% to 75%+ on legitimate claims

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