Overview
A leading road marking and highway safety contractor transformed its operational and financial performance by embedding data-driven decision making across the business. By fully utilising the built-in reporting capabilities of Triangle Software and systematically extracting operational data, the company gained clear visibility into productivity, subcontractor usage, travel efficiency, and contract profitability.
This strategic shift enabled the business to identify weaknesses, implement targeted improvements, and measure the impact of those changes month on month and year on year.
The Challenge
First installed in 2015, Triangle’s bespoke software initially supported onsite data capture and contract productivity analysis. As the business grew, however, greater clarity was needed across four key areas:
- True operational productivity
- Subcontractor reliance
- Time inefficiencies
- Profitability at contract level
Without detailed reporting and consistent performance tracking, it was difficult to confidently assess whether strategic decisions were delivering measurable results.
The leadership team recognised that instinct-based decisions were no longer sufficient. The business needed accurate, structured data to guide operational and commercial strategy.
The Solution: Leveraging System Data for Strategic Insight
The company opted for a full rewrite of the first iteration of the software, tasking Triangle with building a system that monitored costs and time alongside the operational onsite data. Using Triangle’s built-in reporting tools alongside structured data extraction, a framework for continuous performance monitoring was established.
Rather than reviewing performance in isolation, the business analysed trends over time, comparing:
- Month-on-month performance
- Year-on-year improvements
- Pre- and post-strategy implementation results
This allowed the business to move from reactive management to proactive, evidence-based decision making.
Key Areas of Data Analysis
1. Operational Productivity
Workforce efficiency was analysed by reviewing total operative shift time, actual working time, and output measured in square metres laid. This enabled the business to identify gaps between paid hours and productive hours, and to understand performance by:
- Work type
- Customer type
- Individual contract
By segmenting productivity data in this way, management could pinpoint underperforming areas and implement targeted operational improvements.
2. Subcontractor Productivity and Resource Strategy
Subcontractor usage was evaluated against internal workforce capacity. Key questions included:
- Were subcontractors being used while direct employees were underutilised?
- Could frequently outsourced disciplines be brought in-house?
Data analysis revealed patterns of subcontractor reliance. In cases where usage was consistently high, the business assessed the feasibility of developing internal capability, reducing external spend and increasing margin control. This strategic review allowed resource planning to be aligned with long-term profitability goals.
3. Travel Time and Geographic Efficiency
Travel time was analysed to identify time lost travelling to low-margin or non-profitable jobs, and inefficient deployment based on depot locations. By reviewing geographic data alongside job profitability, the business identified opportunities to:
- Optimise depot coverage
- Improve job allocation
- Reduce non-productive travel time
This directly improved utilisation rates and reduced hidden operational costs.
4. Contract-Level Profitability
Contract profitability became a core performance metric. The business analysed revenue rates, plant costs, labour costs, and material costs. A critical insight was examining material cost as a percentage of overall profit. Where material costs were disproportionately high, it indicated that contract rates were too low.
This data-driven approach empowered commercial teams to adjust pricing strategies, renegotiate contracts where necessary, and protect margins proactively. Rather than discovering profitability issues at year-end, they could intervene in real time.
The Results
Through structured use of system data and reporting tools, the business achieved:
- Greater operational transparency
- Improved workforce utilisation
- More strategic subcontractor management
- Reduced travel inefficiencies
- Stronger contract profitability control
- Evidence-based commercial decision making
The business moved from reactive management to a culture of measurable, data-led strategy.
Conclusion
This case study demonstrates how operational data, when properly extracted, analysed, and monitored, can transform a contracting business.
By fully leveraging Triangle’s reporting capabilities, the business embedded a disciplined approach to performance management. Every strategic decision, from pricing to resource allocation, is now supported by measurable evidence.
No longer relying on assumptions. Making confident, data-driven decisions.
