Views: 20
Summary – Faced with the imperative of equipment availability and the rise of Machine-as-a-Service, after-sales service must become a value driver. A modern ERP centralises and automates after-sales processes, unifies inventory, scheduling, and invoicing, tracks every machine, deploys scalable contracts and premium services, and leverages IoT and data analytics for predictive maintenance. Adopt an API-first, open source solution integrated with CRM and telemetry to turn your after-sales service into a sustainable profit center.
In an environment where industrial equipment availability is critical and service models are evolving toward Machine-as-a-Service, after-sales service is no longer limited to incident handling; it becomes a genuine value-creation lever.
A modern ERP, combined with IoT, data, and automation, enables rethinking every step of after-sales service to turn it into a profit center and a loyalty tool. It unifies inventory, schedules interventions, tracks traceability, and optimizes spare-part costs, all while ensuring efficient predictive maintenance. Swiss manufacturers can thus transform a traditionally costly function into a sustainable competitive advantage.
Structuring Industrial After-Sales Service at the Core of Your ERP
An up-to-date ERP centralizes and standardizes after-sales service processes for greater discipline and responsiveness. It replaces information silos with a single, coherent workflow.
Centralizing After-Sales Service Processes
Centralizing intervention requests and tickets through an ERP eliminates duplicates and input errors. Each incident, from a simple repair to a parts request, is logged and timestamped automatically.
Predefined workflows trigger approvals at each stage—diagnosis, scheduling, intervention, invoicing. Managers thus have a real-time view of the status of interventions and deployed resources.
Automating alerts and escalations ensures compliance with service deadlines and contractual SLAs, while freeing after-sales teams from manual follow-up tasks and dashboard updates.
Unifying Inventory, Scheduling, and Invoicing
Implementing an ERP module dedicated to after-sales service consolidates the inventory of spare parts and consumables as part of a maintenance management software solution. Stock levels are adjusted based on service history and seasonal forecasts.
For example, a Swiss mid-sized machine-tool company integrated its after-sales service into a scalable ERP. It thus reduced its average intervention preparation time by 20%, demonstrating the direct impact of automated scheduling on operational performance.
Invoicing is triggered automatically upon completion of an intervention or validation of a mobile work order. Discrepancies between actual costs and budget forecasts are immediately visible, facilitating financial management of after-sales service.
Industrializing Traceability
Each machine and component is tracked by serial number, recording its complete history: installation date, software configuration, past interventions, and replaced parts.
Such traceability enables the creation of detailed equipment reliability reports, identification of the most failure-prone parts, and negotiation of tailored warranties or warranty extensions.
In the event of a recall or a defective batch, the company can precisely identify affected machines and launch targeted maintenance campaigns without treating each case as an isolated emergency.
Monetizing After-Sales Service and Enhancing Customer Loyalty
After-sales service becomes a profit center by offering tiered contracts, premium services, and subscription models. It fosters a proactive, enduring customer relationship.
Maintenance Contracts and Premium Services
Modern ERP systems manage modular service catalogs: warranty extensions, 24/7 support, exchange spare parts, on-site training. Each option is priced and linked to clear business rules.
Recurring billing for premium services relies on automated tracking of SLAs and resource consumption. Finance teams gain access to revenue forecasts and contract-level profitability.
By offering remote diagnostics or priority interventions, manufacturers increase the perceived value of their after-sales service while securing a steady revenue stream separate from equipment sales.
To choose the right ERP, see our dedicated guide.
Adopting Machine-as-a-Service for Recurring Revenue
The Machine-as-a-Service model combines equipment leasing with a maintenance package. The ERP oversees the entire cycle: periodic billing, performance monitoring, and automatic contract renewals.
A Swiss logistics equipment company adopted MaaS and converted 30% of its hardware revenue into recurring income, demonstrating that this model improves financial predictability and strengthens customer engagement.
Transitioning to this model requires fine-tuning billing rules and continuous monitoring of machine performance indicators, all managed via the ERP integrated with IoT sensors.
Proactive Experience to Boost Customer Satisfaction
By integrating an AI-first CRM with ERP, after-sales teams anticipate needs: automatic maintenance suggestions and service reminders based on recorded operating hours.
Personalized alerts and performance reports create a sense of tailored service. Customers perceive after-sales as a partner rather than a purely reactive provider.
This proactive approach reduces unplanned downtime, lowers complaint rates, and raises customer satisfaction scores, contributing to high retention rates.
Edana: strategic digital partner in Switzerland
We support companies and organizations in their digital transformation
Leveraging IoT, Data, and Automation for Predictive Maintenance
IoT and data analytics transform corrective maintenance into predictive maintenance, reducing downtimes and maximizing equipment lifespan. Automation optimizes alerts and interventions.
Sensor- and Telemetry-Based Predictive Maintenance
Onboard sensors continuously collect critical parameters (vibration, temperature, pressure). This data is transmitted to the ERP via an industrial IoT platform for real-time analysis.
The ERP automatically triggers alerts when defined thresholds are exceeded. Machine learning algorithms detect anomalies before they lead to major breakdowns.
This proactive visibility allows scheduling preventive maintenance based on actual machine needs rather than fixed intervals, optimizing resource use and limiting costs.
Real-Time Alerts and Downtime Reduction
Push notifications sent to field technicians via a mobile app ensure immediate response to detected issues. Teams have the necessary data to diagnose problems even before arriving on site.
For example, a Swiss construction materials manufacturer deployed sensors on its crushers. Continuous analysis enabled a 40% reduction in unplanned stoppages, illustrating the effectiveness of real-time alerts in maintaining operations.
Post-intervention performance tracking logged in the ERP closes the loop and refines predictive models, enhancing forecast reliability over time.
Orchestrating Field Interventions via Mobile Solutions
Technicians access the full machine history, manuals, and ERP-generated work instructions on smartphones or tablets. Each intervention is tracked and timestamped.
Schedules are dynamically recalculated based on priorities and team locations. Route optimization reduces travel times and logistics costs.
Real-time synchronization ensures any schedule change or field update is immediately reflected at headquarters, providing a consolidated, accurate view of after-sales activity.
Implementing an Open and Scalable Architecture
An API-first ERP platform, connectable to IoT, CRM, FSM, and AI ecosystems, ensures flexibility and scalability. Open source and orchestrators safeguard independence from vendors.
API-First Design and Connectable IoT Platforms
An API-first ERP exposes every business function via standardized interfaces. Integrations with IoT platforms, CRM systems, or customer portals occur effortlessly without proprietary development.
Data from IoT sensors is ingested directly through secure APIs, enriching maintenance modules and feeding decision-making dashboards.
This approach decouples components, facilitates independent updates, and guarantees a controlled evolution path, avoiding technical lock-in.
Open-Source Orchestrators and Hybrid Architectures
Using BPMN orchestrators, open-source ESBs, or microservices ensures smooth process flows between ERP, IoT, and business tools. Complex workflows are modeled and managed visually.
A Swiss municipal infrastructure management authority implemented an open-source orchestrator to handle its after-sales and network maintenance operations. This solution proved capable of evolving with new services and business requirements.
Modules can be deployed in containers and orchestrated by Kubernetes, ensuring resilience, scalability, and portability regardless of the hosting environment.
Seamless Integration with CRM, FSM, and AI
Connectors to CRM synchronize customer data, purchase history, and service tickets for a 360° service view. FSM modules manage field scheduling and technician tracking.
AI solutions, integrated via APIs, analyze failure trends and optimize spare-parts recommendations. They also assist operators in real-time diagnostics.
This synergy creates a coherent ecosystem where each technology enhances the others, boosting after-sales performance and customer satisfaction without adding overall complexity.
Make Industrial After-Sales Service the Key to Your Competitive Advantage
By integrating after-sales service into a modern, scalable ERP, coupled with IoT, data, and automation, you turn every intervention into an opportunity for profit and loyalty. You unify inventory, optimize planning, track every configuration, and reduce costs through predictive maintenance. You secure your independence with an open, API-first, open-source-based architecture, avoiding vendor lock-in.
Our experts support you in defining and implementing this strategy, tailored to your business context and digital maturity. Benefit from a hybrid, modular, and secure ecosystem that makes after-sales service a driver of lasting performance and differentiation.
