Cross-Company Data Flows for Machine Uptime

Why agricultural OEMs need a new integration approach

Modern agricultural service processes rarely stay within a single company. Machine uptime depends on seamless collaboration between OEMs, dealers, service technicians, parts suppliers, and farmers. Each stakeholder operates different ERP systems, dealer management systems (DMS), IoT platforms, and cloud applications.

While electronic data exchange is not new, achieving fully automated, end-to-end processes across company boundaries remains difficult and costly. Many integration initiatives still require large investments and ongoing operational effort from already stretched IT teams.

However, cloud maturity and the emergence of AI are changing what is possible. A new class of integration providers is emerging that combines technology, business expertise, and ready-to-run partner connectivity.

This article explores how this shift enables new service capabilities in agricultural machinery and why specialized integration partners are becoming strategic for IT leaders.

What you will learn:

‍🔶 Why cross-company integration projects often underperform

‍🔶 Why generic ETL platforms struggle in the agricultural machinery ecosystem

‍🔶 How specialized integration providers differ

‍🔶 How OEMs and dealer networks can move toward scalable, cloud-based connectivity

The growing value of data in agriculture

Precision farming has transformed agriculture into a data-driven industry. Modern machines continuously generate operational and sensor data that can improve productivity, service quality, and lifecycle management.

To unlock this value, data must move securely and reliably between:

🔶 Machines and IoT platforms

🔶 Dealers and service providers

🔶 OEM backend systems

🔶 Farm management software

This requires trusted, scalable cross-company data sharing.

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The current reality: fragmented OEM connectivity

Most OEMs already use ETL tools and APIs to move data between systems.

Quick explanation:

🔶 ETL (Extract, Transform, Load): software that collects data from one system, converts it into a usable format, and loads it into another system.

🔶 API (Application Programming Interface): a technical interface allowing software systems to exchange data directly.

Despite these technologies, real end-to-end integration remains incomplete and error-prone.

Why? Because generic tools rarely capture the business logic of agricultural service networks.

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The Current Challenge: Incomplete OEM Data Connectivity

Traditional ETL solutions work well inside a single enterprise. They struggle when integration must span thousands of independent partners.

Key limitations:

1. Thousands of custom interfaces

Each dealer and partner may use different ERP or DMS systems.
Generic ETL requires building and maintaining custom integrations per partner, creating massive long-term maintenance overhead.

2. Data without context

Dealer systems often deliver raw transactional data.
Transforming this into meaningful agricultural service insights requires industry-specific interpretation and business rules.

3. Constant ecosystem change

Dealer networks evolve continuously:

🔶New partners join

🔶Systems change

🔶Processes adapt

Integration must therefore be dynamic and scalable, not static and project-based.

4. Long project timelines

Integration programs often take years before delivering value, far too slow for a rapidly digitizing industry.

The result is fragmentation affecting every stakeholder:

🔶Farmers experience reduced machine uptime

🔶Dealers struggle with inefficient workflows

🔶OEMs lack full fleet visibility and service insights

The agricultural industry needs better approaches to OEM data connectivity to keep up with current technological advancements and speed.

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The traditional market for data integration in the world of ERP

Transferring and integrating data across company boundaries is a challenging topic almost as old as IT itself. Today, the ETL and integration market is considered one of the largest IT markets and is undergoing rapid change. From on-premise tools to cloud-based solutions, companies today have a variety of options, and ETL tools are a common component in the IT landscapes of enterprises.

However, complex data integration projects are among those most likely to fail or significantly exceed their budgets. Gartner Predicts 80% of D&A Governance Initiatives Will Fail by 2027 (Gartner, 2024).  Complexity is underestimated, and business benefits fall short of expectations.

Main reasons are:

🔶 Lack of understanding of business processes and service complexities

🔶 Data content and scope needed are underestimated

🔶 Variety of legacy technology involved turns out to be way beyond original plans

For these reasons often the core integration inside OEMs is restricted to standard interfaces provided by large solution players like Microsoft, SAP or Salesforce. These enterprise standards and technologies established during the 80/90ties (EDI, X.25 standards, BAPI) are still the backbone of most business processes.

Quick explanation:

🔶 EDI (Electronic Data Interchange): lets companies’ systems automatically exchange standardised digital documents (like orders, invoices, or shipping notices) directly with each other, without manual retyping.

🔶 X.25: a legacy network protocol that reliably routes transactional data over long‑distance networks.

🔶 BAPI (Business Application Programming Interface): a standardized SAP interface that lets external applications read and update SAP business data.

Often IT departments struggle to keep existing ETL solutions and interfaces inside a company running. Capacity for new technology, such as AI, and adoption of complex tasks in a complete industry is not available.

The rise of integration platforms with business intelligence

As the internet and cloud services are now widely standard in the industry, a new type of technology providers for ETL arrives. These providers act as software and solution providers and data managers at the same time. According to their specific marketplace they bring extensive business knowledge and ready to run interfaces connecting systems, partners and business processes. As a result, a complete service is provided which allows immediate realization of business benefits and reduction of complexity in IT landscapes.

Cloud computing has enabled a new category of providers that combine:

🔶 Integration technology

🔶 Industry knowledge

🔶 Pre-connected partner ecosystems

Unlike generic ETL vendors, these platforms deliver integration as a business service, not just as infrastructure.

Common characteristics:

🔶 Ready-to-use interfaces to industry partners

🔶Embedded business logic and process knowledge

🔶 Scalable cloud deployment

🔶 Faster time-to-value

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The right partner to integrate agricultural machine operation and lifecycle management

Machine service and lifecycle management rely on efficient coordination across the entire service supply chain. With the rise of IoT, robotics, autonomous equipment, and advanced analytics, seamless data sharing is becoming essential.

Specialized platforms such as ClearOps focus on connecting:

🔶 Dealers and workshops

‍🔶 Parts and logistics networks

🔶 OEM backend systems

By acting as a single integration hub, these platforms allow OEMs to access dealer and service data across entire markets without building thousands of individual connections.

For IT departments, this offers several advantages:

🔶 Faster onboarding of dealer networks

🔶 Reduced internal integration workload

🔶 Access to continuously evolving technology, including AI-driven data processing

A unified data foundation enables high-impact use cases:

🔶 Automated spare parts planning

🔶 Inventory optimization across networks

🔶 AI-driven demand forecasting

🔶 Predictive maintenance and machine health monitoring

These capabilities directly contribute to improved machine uptime, reduced service costs, and better customer experience.

Every IT executive today challenged by the complex data issues in the world of agricultural machinery can benefit from looking into full scope service providers to have the relevant data immediately available.

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Conclusion: The Future of Agricultural Machinery Data Integration

Organizations face a fundamental decision:  

Option 1: Invest significant resources attempting to build custom integrations using generic ETL tools with high failure rates.

Option 2: Work with purpose-built solutions, such as ClearOps, that bring proven OEM data connectivity, deep industry expertise, and immediate business value.

The complexity of agricultural machinery data integration will only increase as IoT sensors proliferate, autonomous equipment arrives, and customer expectations for seamless service continue to rise. The dealers and OEMs who embrace purpose-built data connectivity solutions today will be the market leaders tomorrow.

About ClearOps

ClearOps is the leading aftersales platform for the mobile machinery industries, enabling OEMs and dealers to maximize machine uptime for their end customers and unlock their full aftersales potential.

By connecting OEMs, dealers, and machines on a single cloud platform, ClearOps transforms the service supply chain into a predictive and proactive ecosystem. It forecasts parts demand, coordinates technician and parts deployment, and captures critical lifecycle data worldwide, delivering higher fill rates, stronger dealer and service partner performance, increased part sales, and a systematic boost in both machine uptime and customer lifetime value.

ClearOps is headquartered in Munich, Germany with additional offices in Lisbon, Atlanta and San Jose.

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