Are Your Assets Working for You

Asset Utilization vs. Asset Productivity

There’s a big difference between having an asset in service and having it working productively.

A truck may be “utilized” on paper, but if it's making short loads, idling at job sites, or running inefficient routes, it's bleeding margin.
A plant may be running all day, but if downtime events, QC rework, or batching inconsistencies occur, it’s driving up cost per cubic meter.
A loader may be busy, but if maintenance schedules are missed or fuel consumption is spiking, you're trading longevity for throughput.

The question isn’t how much your assets are being used—but how effectively they’re creating value.

The Visibility Problem

Historically, tracking asset performance required manual logs, telemetry exports, or post-mortem maintenance reviews. Most of this data lived in silos—if it was even collected at all.

Even with modern GPS and telematics, producers often lack:

A unified view across all asset classes
Real-time performance indicators tied to cost and revenue
Predictive alerts that warn of inefficiencies or impending failures

As a result, decisions about fleet expansion, plant upgrades, or job planning are often made based on anecdote or incomplete data.

BPM and AI Can Turn Assets Into Strategic Levers

With Business Performance Management (BPM) systems that incorporate AI and real-time analytics, producers can:

Track asset productivity at the job, plant, and fleet level
Detect early signs of inefficiency—like route deviations, abnormal idle time, or increased cycle time
Forecast equipment stress or maintenance needs, reducing unplanned downtime
Tie asset usage directly to profitability, highlighting which assets are generating margin—and which are quietly eroding it

Instead of reacting to asset performance after the fact, producers can optimize in real time and prioritize investments that truly enhance throughput and margin.

Industry Insight: Why This Matters

According to Deloitte’s 2023 report on industrial performance, companies using predictive asset analytics reported:

10–15% improvement in overall equipment effectiveness (OEE)
30% reduction in unplanned downtime
Up to 20% lower maintenance costs

Source: Deloitte – 2023 Global Smart Manufacturing Survey

These aren't just maintenance gains—they’re bottom-line results.

And for ready-mix producers, where the average mixer truck costs over $200,000 and plant outages can halt thousands of dollars in daily revenue, the stakes are even higher.