Why Telematics Alone Isn’t Reducing Downtime For Agricultural Equipment Manufacturers – And How To Fix It

Over the past few years, the agricultural industry has experienced an explosion in telematics technology. 

Agricultural equipment manufacturers have rapidly integrated telematics into their fleets, with adoption rates rising dramatically. The agriculture telematics market is forecasted to grow at a compound annual growth rate (CAGR) of 12.4% between 2024 and 2030. From monitoring equipment health to optimizing field operations, the data being generated is vast.

But equipment downtime remains a significant issue for manufacturers and farmers alike. Despite the wealth of information telematics provides, many are still struggling to reduce downtime.

Why? Because gathering data is only part of the solution. Making sense of it, quickly and accurately, is the missing piece – and where current approaches fall short. 
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The telematics revolution in agricultural equipment

The adoption of telematics in agricultural equipment promises to help businesses stay competitive, improve productivity, and reduce costs. Key use cases include: 
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• Predictive service planning: Help identify potential equipment failures before they occur, reducing unplanned downtime and extending the life of machinery.

• Operational efficiency and fleet management: Optimize fuel consumption, route planning, and task allocation by providing real-time data on equipment usage and location. 
• Yield optimization: Optimize inputs and maximize yields through real-time data on soil health, irrigation, and fertilization. 
• Remote diagnostics and troubleshooting: Enable remote diagnostics, allowing issues to be identified and addressed without delays, reducing the time it takes to repair equipment and minimizing downtime. 

But despite the promise, the industry has not seen a corresponding reduction in downtime. Downtime costs US farmers billions of dollars in losses annually, and the cost of farm equipment repairs has shot up by over 40% since 2020. 

While equipment downtime is a challenge in every industrial sector, it’s particularly devastating in the agricultural industry. Farming is a low-margin, commoditized business – making any impact to business operations particularly harmful. Due to high seasonal time-sensitivity, equipment failures during critical planting or harvesting windows have outsized impacts on productivity and yield. And finally, many farms are located in remote areas, making equipment repairs challenging and time consuming. 

So why has the industry not yet been able to deliver on the promise of telematics to reduce downtime? The challenge lies in transforming raw telematics data into actionable insights.
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Why telematics data hasn’t (yet) reduced downtime

One of the reasons downtime remains stubbornly high despite the proliferation of telematics is the complexity and noisiness of the data. Telematics systems generate massive amounts of time-series data from different sensors embedded in vehicles, engines, and other components. 

This data is complex to interpret and difficult to unify into a single system. The sheer volume of the data – multiple sensor types, each measuring different components over time, combined with variations in format and context – can overwhelm traditional analysis tools, leaving important patterns undetected.

Consider this example from a large tractor manufacturer whose latest model encountered a series of unexpected engine failures. Traditional BI approaches pointed to the fuel injection system, leading to costly and time-consuming investigations. But upon closer analysis of the telematics data, an unexpected culprit emerged: a faulty sensor in the cooling system was providing incorrect readings, causing the engine control to miscalibrate fuel injection timing. This type of subtle interaction between systems is nearly impossible to detect with conventional analysis methods.

To prevent these types of failures, manufacturers need more than just access to data—they need tools capable of identifying patterns and correlations at scale. This is where Viaduct comes in.
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How Viaduct helps

Viaduct has spent years developing an AI-powered solution designed to sift through vast amounts of connected equipment data and uncover hidden insights. At the heart of our technology is a patented correlation engine that not only organizes telematics data but also connects seemingly unrelated data points to surface actionable insights.

We help agricultural equipment manufacturers reduce downtime through three core capabilities:
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1. Search: Our platform consolidates all telematics and service data into a unified system. With Viaduct, users can quickly search for patterns across multiple datasets, without needing an in-depth understanding of the underlying data architecture. This “single pane of glass” view simplifies investigations and saves time.
2. Detect: Viaduct's platform proactively identifies patterns in the data that suggest systemic quality issues. For example, we can detect early signs of a recurring part failure before it leads to widespread downtime or warranty claims. By identifying the root cause early, manufacturers can take preventative action.
3. Predict: Our predictive analytics capabilities allow manufacturers to forecast equipment health and identify potential failures before they happen. With Viaduct, you can build customized, predictive maintenance plans that minimize unplanned downtime and maximize equipment utilization.

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The bottom line

Agricultural equipment manufacturers face a unique set of challenges when it comes to preventing downtime—challenges that traditional data analysis tools are not equipped to solve. Telematics data holds the key to reducing downtime, but it must be analyzed with precision and at scale. Viaduct’s solution brings the power of advanced AI analytics to your telematics data, giving you the directly reduce equipment downtime.

If you’d like to learn more about how Viaduct can help reduce downtime and improve equipment reliability, reach out for a demo today.