Enhancing Efficiency and Customer Satisfaction
As required by the paradigm shift in digitalization, the automation and optimization of business processes are already being intensively pursued in numerous companies. However, many of these measures focus primarily on internal processes, often neglecting the critical aspect of customer experience.
Use Case: Global Machine MaintenanceImagine an industrial company selling machinery worldwide. Occasionally, machines may experience sudden failures, leading to significant downtime and frustrated customers. Even with immediate service technician support, repairs can be delayed, and expensive spare parts may need to be ordered from the manufacturer.
Effectively utilizing existing data can minimize such issues. Predictive maintenance, driven by accurate data, can help prevent machine failures and reduce costly downtime.
Using Data for Precise Planning of Maintenance Slots
With proper data analysis, companies can schedule maintenance activities more accurately. Considering factors such as local conditions (humidity, climate, etc.) and machine usage allows for precise planning and helps prevent unexpected breakdowns.
Proactive maintenance planning, based on data insights, reduces emergency repairs, lowers costs, and enhances customer satisfaction by minimizing disruptions.
“Many of the measures taken focus primarily on internal processes, while customer focus has often been neglected.”
Andreas Balsiger
Head of Product Management, Axon Ivy AG
Real-Time Forecasting for Proactive Service
Leveraging customer-specific data allows for precise, real-time forecasting of maintenance slots. This data-driven approach helps companies determine exactly when and which machines require maintenance. Suppliers can use these insights to proactively alert customers about upcoming maintenance needs or offer the convenience of scheduling maintenance appointments online.
For businesses relying on machinery, this approach allows for better maintenance scheduling, reduces emergency service calls, and positively impacts overall cost management.
Digital Transformation: A Strategic Approach
The initial step for an industrial enterprise in digital transformation is to evaluate both existing and future data to design a seamless, non-disruptive service. This service should be fully integrated and supported by digital technology throughout its entire lifecycle.
According to a study by the World Economic Forum and consulting firm Accenture, predictive maintenance can reduce unplanned machine failures by up to 70%. The US Department of Energy (DEO) even estimates up to 75% fewer outages.
Enhancing Customer Relationships
The fact that the customer perceives this proactive information as a service, thereby strengthening all involved parties' relationships, is a side effect that should not be underestimated. A study by inContact shows that 87% of consumers appreciate proactive service and are likelier to engage positively with businesses that offer it. This approach ensures that customer expectations are met and exceeded, fostering loyalty and turning satisfied customers into advocates.
Integrating predictive maintenance into service offerings allows companies to achieve operational excellence, enhance customer satisfaction, and secure a competitive edge in the market.
