What CEOs Need To Know About M2M – Part 5 (Automating business processes and driving efficiency)
Today’s blog post continues the discussion on the value of machine data integration with other enterprise business applications and processes. In my previous post on “what CEOs need to know about M2M”, I listed 10 processes that can be enhanced with machine data. Today, we’ll discuss specific customer examples of business processes that have been enhanced and improved using machine data. Many of these examples are about improving efficiency and taking out costs and drive the business cases for investing in connected products.
Let’s start with field service. Many field service requests and visits are initiated by a customer “call” into the call center, typically due to a down or malfunctioning machine. There is often a lag time between the customer placing the call and the initial occurrence of the problem. To remove the lag and improve the service, we have several customers who have automated the creation of a case and a field service request in their back office systems by having rules in our machine cloud monitor machine events and trigger a web service call into their systems. This removes the lag and also proactively starts the repair procedure minimizing downtime.
Customer service and support is another example. Many of these same customers above prepopulate case and asset data in their CRM app with machine status, reading and logs. This shortens call times and improves time to repair. It also eliminates the need for 2 workflows or UIs (one for Axeda and one for CRM) since the customer service and field service reps can continue to use the CRM app they use today. But now their screens are enhanced with close to real-time machine data.
Another process that can be improved with machine data is warranty management. An industrial manufacturing customer was able to add temperature and humidity sensors to their factory equipment and then monitor the operating conditions of the factories their equipment ran in. This enabled them to forewarn their customers of potential issues and drive them to improve their operating conditions to reduce breakdowns. In some cases, it also enabled them to deny warranty coverage for customer out of compliance. Overall, simply adding a couple of sensors saved this company millions in warranty costs.
Another process that can be improved with machine data is billing. An industrial equipment maker of ours was able to introduce a new “pay-per-use” billing model enabled by machine data. Axeda collects usage data from their machines that generate reports for the invoicing process. This enabled the customer to offer a “product-as-a-service” and go downstream to the mid-market by lowering the cost entry point for their end-users.
In all these examples, think of Axeda as the “M2M middleware”… the software that collects the machine data, transforms it, and integrates it. In my next post, I’ll discuss level 6 – Differentiation. This level is about changing the product experience for customers by adding value-added apps that extend the utility of a machine. These apps can help differentiate machines and provide a competitive advantage. These expanded offerings are driving rapid adoption of connected services, because it’s no longer about just value for the machine supplier/manufacturer, the connectivity is providing value to the end-user… what a concept!