In this talk, we discussed a series of concrete use cases through which IoT data analysis can be used to improve operational efficiencies and customer and field support:

– how to analyse historical asset data to predict future failures and estimate when maintenance should be performed;

– how to create support tickets in your preferred support software in an automated way, by correlating known asset fault codes with sensor data;

– how to analyse the root cause of an issue signalled by the customer by using historical data from the affected asset, before dispatching the field engineer.

– how to analyse faulty asset data by processing log files uploaded by the technician while on site, from offline machines or from additional data sources

– how to automatically process raw data in batch and provide next best-action recommendations to your (outsources) field technicians, while tracking their process adherence.

Challenges addressed in this presentation

Smart asset manufacturers and vendors are busy with collecting asset data, displaying it on IoT dashboards and sometimes analysing it to identify areas for product improvement. There is little to no operational use of IoT asset data in the context of customer and field support. In this talk we’ll look at how we can use IoT data to improve customer service and field support through intelligent data processing, automation and integration with back-end IT systems.

Learning takeaways

Learn how to improve the ROI from IoT investments by putting IoT data from your connected assets to operational use. By making IoT operational, your teams start to see immediate benefits in improved customer service, optimized field support, better resource allocation and lowered costs.

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