There’s no doubt that service businesses are organizing themselves to be more predictive in the service that they provide. Instead of responding to a service event, they can now act on information and data available and prevent future repair issues with predictive actions. This has significant ramifications, especially on the customer who is potentially facing a shutdown of operations due to product failure. The impact on the service organization is significant too, as resources don’t need to be scrambled to meet an emergency service request. Being able to predict service needs allows the service organization the luxury to plan for future resource needs.
Achieving predictive service outcomes can be expensive. One can approach predictive service with more of a time-based preventive maintenance model, but that doesn’t really weed out all service issues and therefore doesn’t afford all the cost benefits of reactive service avoidance. We also believe that service buyers will begin to question the value of preventive maintenance schedules without real insight into how these visits are driving the outcomes desired by their businesses.
For true predictive service, one needs to get a better view into what’s happening with products in the field. This view isn’t limited to the operating performance of the product or the equipment, but also covers the environment that the equipment is in, and the nuances of how operators are handling the equipment. To enable real-time data capture and management, many organizations are heading towards the introduction of more sensors on their equipment. Anyone who has tried to do this knows how difficult it is. Sensors raise the short-term cost and complexity in R&D cycles and can get discarded in R&D’s attempts to remain on time and under budget. It takes a senior business leader who understands the long-term enterprise value of an investment in sensors to ensure that R&D and service can work hand-in-hand. Even then, it isn’t guaranteed that the service organization will receive all the information needed to develop a predictive picture. Sensor data can be supplemented by data that’s captured through customer requests or during on-site service visits – all models of data capture that should be considered by service organizations looking to introduce predictability into their delivery models.
While predictive service is being enabled, organizations mustn’t lose sight of the opportunity in becoming more proactive in how they approach their customers. Predictive service is one element of a more proactive customer management strategy. We believe that a proactive support strategy encompasses the following elements:
- Predictive Service / Maintenance
- Resource Planning for Predictive Service Operations
- Proactive Operations Management
- Proactive Installed Base Management
- Proactive Customer Communication
I recently spent some time highlighting the various stages of The Service Council’s proactive support strategy on a Smarter Services™ Webcast called “Raising the Bar for Field Service with Predictive Technologies.” To hear a recording of the webcast, please click here. This webcast is supported by ClickSoftware and includes a wonderful presentation by team members at Stedin a leading energy management company based out of the Netherlands, who are focused on driving business value with the aid of predictive technologies. Next week, I’ll be summarizing my thoughts and presenting them on a post-event blog available on The Service Council’s website.
