Business Process Improvement with IoT Analytics

Business Process Improvement and IoT Analytics

Business Process Improvement with IoT Analytics can happen in many ways resulting in new revenue opportunities, lower costs, and enhanced operational efficiency. The growing adoption of IoT is becoming clear in a wide range of industries and use cases. In addition, a wider range of roles are involved in the projects – business managers, operations managers, IT staff, and analytics professionals are all now involved in IoT projects. It is clear to everyone that Analytics on IoT device data is fundamental, but it is only now becoming clearer to all parties that it is very important to consider the business process impact, which will sometimes be as large or larger.

The broad impact of business process changes means many more opportunities to generate economic value with IoT Analytics than simply looking at device data.

Autonomous or semi-autonomous Things are becoming active participants in business processes.  IoT Analytics can generate predictions related to business processes using the device and sensor data.

These predictions give operators and managers the ability to understand the business process context, and then take actions to alter or improve business processes accordingly.   This could be to either avoid costly/negative outcomes or enhance processes to generate revenue/lower costs.

This wider lens on business process improvement means that business and operations managers must carefully consider the collaboration and orchestration between humans, business processes, and “Things” to increase the impact of IoT Analytics initiatives.

Some examples where device data can lead to a wider business process impact are:

Examples:

  • Utilities can leverage information not only on the operating state of transformers and other equipment, but that data than can be used to re-design the routes, schedules, and logistics for the service and maintenance staff – changing the business process and generating major cost savings.
  • Manufacturers can use data from sensors on critical equipment in the field to re-design their support and product configuration business processes to reduce support incidents and enhance customer satisfaction.
  • Supply Chain managers can take advantage of data flowing from IoT devices in their network to anticipate or predict supply disruptions, and act to prevent those disruptions.

The fundamental point for all these examples is that IoT Analytics project managers need to integrate business and operations managers into all aspects of the development process.   This will ensure that more opportunities to generate value with business process improvement will be considered and executed in IoT initiatives.

 

 

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