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Commercial Intelligence

How an Australian Mining Firm Reduced Contract Overruns by 61% with Commercial Intelligence

A detailed case study of how a mid-tier Australian mining services contractor reduced contract overruns by 61% and recovered AUD 4.7 million in previously unidentified variation entitlements within 14 months.

SK
Sneha Kulkarni
|July 7, 20255 min readUpdated Jul 2025
Australian mining site with commercial intelligence dashboard overlay showing contract performance metrics

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Key Takeaways

  • 1The Challenge
  • 2The Solution
  • 3The Results (14 Months Post-Deployment)
  • 4Key Lessons

The Challenge

A mid-tier mining services contractor operating across Western Australia and Queensland — with AUD 420 million in annual revenue and 35 active contracts — was experiencing a pattern that its leadership described as "death by a thousand cuts."

No single contract was catastrophically unprofitable. But across the portfolio, a persistent pattern of small overruns, missed variations, and late-detected subcontractor issues was eroding margins to the point where the firm was consistently delivering 1.2% operating margin against a target of 3.5%.

The firm's commercial team — three contracts managers and a commercial director — was talented but overwhelmed. They managed AUD 140 million in contract value per person, well above the industry benchmark of AUD 80-120 million per senior commercial FTE. The result was reactive management: problems were addressed when they became visible, rather than detected and prevented when they were still manageable.

Specific pain points:

  • Variation identification: The team estimated they were identifying and claiming approximately 65% of legitimate variation entitlements. The remaining 35% was lost — either because variations were not identified in time, or because notification deadlines under AS4000 and AS4902 contract conditions were missed.
  • Subcontractor risk: In the prior 24 months, two subcontractor defaults had occurred with no advance warning, costing AUD 1.8 million in replacement costs and programme delays.
  • Bid selection: The firm was bidding on 22-28 tenders per year with a 14% win rate, spending an average of AUD 95,000 per major tender submission. Annual wasted bid costs exceeded AUD 1.7 million.
  • Commercial reporting: Portfolio-level commercial reporting required 3-4 days of manual compilation each month, producing a snapshot that was already outdated by the time it reached the board.
Does this sound familiar? Most Australian contractors we speak with describe a version of this pattern. See how your firm compares — our diagnostic assessment identifies your specific margin leakage points.

The Solution

The firm deployed DealGuard's commercial intelligence platform in a phased implementation over 16 weeks:

Weeks 1-4: Data Integration - Connected to the firm's MYOB AccountRight ERP for financial data - Integrated with their Procore project management platform for contract documentation and correspondence - Established ASIC and credit bureau feeds for the firm's 180+ active subcontractors and suppliers - Imported 3 years of historical tender data (outcomes, pricing, competitor intelligence)

Weeks 5-10: Model Calibration and Testing - Calibrated tender win-probability models against the firm's historical bid outcomes - Configured counterparty risk thresholds aligned with the firm's risk appetite - Tested variation identification algorithms against completed project records (benchmark: identified 94% of historically documented variations) - Trained the commercial team on dashboard interpretation and alert response

Weeks 11-16: Production Deployment and Optimisation - Full production deployment across all 35 active contracts - Parallel running of old and new processes for the first 4 weeks - Iterative refinement of alert thresholds based on team feedback - Decommissioned legacy spreadsheet-based tracking

> Try our free Contract Risk Exposure Calculator — a practical resource built from real implementation experience. Get it here.

## The Results (14 Months Post-Deployment)

Before and After

MetricBefore DealGuardAfter DealGuard (14 Months)Improvement
Operating margin1.2%2.9%+1.7 percentage points
Variation identification rate~65%91%+26 percentage points
Variation recovery valueAUD 8.2M/yearAUD 12.9M/year+AUD 4.7M
Contract overrun rate23% of contracts9% of contracts-61%
Subcontractor defaults (undetected)2 in prior 24 months0 in 14 months-100%
Bid win rate14%21%+50%
Annual wasted bid costsAUD 1.7MAUD 980K-42%
Monthly reporting time3-4 days2 hours (automated)-93%
Contract value per commercial FTEAUD 140MAUD 165M+18%

Financial Impact Summary

Value DriverAnnual Impact (AUD)
Additional variation recoveryAUD 4,700,000
Avoided subcontractor default costsAUD 900,000 (annualised)
Reduced bid wasteAUD 720,000
Margin improvement (beyond variations)AUD 2,100,000
**Total annual value****AUD 8,420,000**
Platform and implementation cost (Year 1)AUD 240,000
**Net annual benefit****AUD 8,180,000**
AUD 4.7 million in recovered variations alone would have been enough to justify the investment. The broader margin improvement and risk reduction made this one of the highest-ROI technology investments the firm had ever made. Explore how DealGuard works for mining services contractors.

What the Commercial Director Said

"We knew we were leaving money on the table with variations. We just did not know it was AUD 4.7 million a year. The platform did not replace our commercial team — it gave them the visibility and the time to do their jobs properly. For the first time, I have a real-time view of commercial risk across every contract in the portfolio, rather than finding out about problems when it is too late to fix them."

— Commercial Director, Mid-Tier Mining Services Contractor, Western Australia

Key Lessons

1. The biggest value was in variation recovery, not cost reduction. The firm initially expected the primary benefit to be operational efficiency — freeing up commercial staff time. The actual primary benefit was recovering AUD 4.7 million in variation entitlements that were previously falling through the cracks. This is consistent with our broader deployment data: variation management is the single largest source of value for Australian contractors implementing commercial in

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  • How AI Tender Win-Probability Scoring Improves Bid Success by 47% for Australian Infrastructure Firm

telligence.

2. Subcontractor monitoring needs to be continuous, not periodic. The firm had previously relied on annual prequalification reviews. Continuous monitoring through ASIC data , credit bureaus, and payment behaviour analysis detected three subcontractors showing early distress signals — all three were managed proactively (reduced exposure, enhanced payment security) before any disruption occurred.

3. Bid selection discipline requires data, not just process. The firm had a bid/no-bid process before DealGuard, but it was qualitative and often overridden by business development enthusiasm. The quantified win-probability scores provided an objective basis for declining low-probability opportunities, which reduced bid costs by 42% while improving the win rate from 14% to 21%.

4. Implementation speed matters. The 16-week implementation timeline kept the project focused and prevented scope creep. By the time the commercial team had fully adopted the platform, they had already seen enough value in the pilot phase to become advocates rather than resistors.

Every month without systematic commercial intelligence is a month of undetected margin leakage. Talk to our ANZ team about your deployment timeline.

View more case studies | Learn about DealGuard for mining and resources

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Frequently Asked Questions

How long did it take for the mining firm to see measurable results from commercial intelligence?

The firm deployed DealGuard over a 16-week implementation period. Measurable results began appearing within the first 8 weeks of production use. The variation identification improvements were the first to materialise, as the automated scanning of project correspondence and documentation immediately began flagging entitlements that the manual process was missing. Subcontractor risk detection benefits accumulated over the following 6 months as the continuous monitoring system built a behavioural baseline for tracked entities. Full portfolio-level benefits were realised by month 10-12.

What was the primary source of ROI in this mining case study?

The primary source of ROI was variation recovery — an additional AUD 4.7 million per year in legitimate variation entitlements that were previously not identified or not claimed within contractual notification deadlines. This accounted for 56% of the total annual value. The next largest contributor was broader margin improvement beyond variations (AUD 2.1 million), followed by avoided subcontractor default costs (AUD 900,000 annualised) and reduced bid waste (AUD 720,000).

What systems did the mining firm integrate with DealGuard?

The firm integrated three core systems: MYOB AccountRight ERP for financial data (project costs, invoicing, payment records), Procore project management platform for contract documentation, RFIs, site instructions, and project correspondence, and ASIC/credit bureau feeds for continuous monitoring of 180+ subcontractors and suppliers. The integration was completed within the first 4 weeks of the 16-week implementation, with data normalisation and validation running in parallel.

How did commercial intelligence reduce the contract overrun rate from 23% to 9%?

The 61% reduction in contract overruns was driven by three mechanisms. First, earlier identification of scope variations meant cost impacts were captured and claimed before they accumulated into overruns. Second, continuous subcontractor monitoring prevented the cost blowouts associated with undetected subcontractor defaults. Third, improved bid selection meant the firm was winning contracts that better matched its capabilities and risk appetite, reducing the incidence of projects that were problematic from inception due to aggressive pricing or poor fit.

Is this case study relevant to Tier 1 mining contractors or only mid-tier firms?

The principles and mechanisms are relevant across all tiers, but the specific implementation approach differs. Mid-tier firms (like the one in this case study) typically see the fastest time-to-value because their system landscape is simpler and decision-making is more centralised. Tier 1 mining contractors with AUD 1 billion+ revenue, multiple divisions, and complex JV structures require a phased implementation by division and more extensive integration work, but the per-contract value drivers — variation recovery, risk detection, bid efficiency — are identical and often larger in absolute terms.

How did the firm handle change management during implementation?

The implementation included a 4-week parallel running period where the commercial team used both the legacy spreadsheet process and DealGuard simultaneously. This served two purposes: it validated that DealGuard was producing accurate and actionable outputs, and it allowed the team to build confidence in the new system before decommissioning the old one. The commercial director championed the project internally, and early wins — particularly the identification of previously missed variation entitlements — converted initial sceptics into advocates within the first month of production use.

About the Author

SK

Sneha Kulkarni

Director of Digital Transformation, APPIT Software Solutions

Sneha Kulkarni is Director of Digital Transformation at APPIT Software Solutions. She works directly with enterprise clients to plan and execute AI adoption strategies across manufacturing, logistics, and financial services verticals.

Sources & Further Reading

Harvard Business Review - StrategyMcKinsey Strategy & Corporate FinanceWorld Bank Doing Business

Related Resources

AI & ML IntegrationLearn about our services
Data AnalyticsLearn about our services

Topics

Case StudyMining ContractsAustralian MiningCommercial IntelligenceCost Overruns

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Table of Contents

  1. The Challenge
  2. The Solution
  3. The Results (14 Months Post-Deployment)
  4. Key Lessons
  5. FAQs

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