Before you can answer this question, let’s define the three types of service: (Note: All three contain a portion of some reactive services).
The Reactive service model waits for a device failure and an end-user to place an emergency service call to their service provider. In most cases this device is not functioning at all, which creates downtime and loss of productivity for the employees. Five to seven times out of ten, when the technician does finally arrive, they are not armed with the correct parts to address the current and/or potential near term component failures. This reactive method results in a 50% to at best, 70% first time fix rate. This leads to even more down time and inconvenience due to the technician having to order parts and return days later when these parts do arrive. In this model, downtime will equal 6 to 12 business hours to respond and repair, and additional time for parts to arrive, total estimated downtime equals, 16-24 business hours average.
The Preventative service model is a more effective process than reactive service. In the proactive service model, the service provider uses some analytics to assist them. As an example, the provider may base the need for service on days or productive time (in this case page volume) since the last service event, similar to the recommended oil change sticker they place on your windshield. In this model the technician should perform basic maintenance and inspect all areas of a device, replacing any questionable components proactively, and preventing potential near term failures. Proactive service organizations will also ensure that they arm their technicians with components when responding to any reactive calls, so that they can drive that first call effectiveness up to 85%-90%, reducing potential downtime to 8-16 business hours on average.
The Predictive service model is the highest service level and most effective process of all. In this model the service provider is utilizing monitoring tools via the customer’s network to collect, analyze and potentially react to the device alert data being collected. As trending of error data is collected and analyzed, these providers can dispatch a service technician prior to the device going completely down. The provider will also be sure to arm the technician with potential components due to fail based on service history data, alerts received, analytics, or a combination. In this model, a predictive service event has no downtime until the technician is actually onsite performing the service. In this model the total estimated downtime is 2-6 hours on average and the first call effectiveness will be 90% or greater.
This Predictive model is only in its infancy stages at this time. But as technology advancements continue and our ability to analyze big data in more effective and efficient ways improves, look for more focus on this process from your service provider, or look for a provider with the vision and knowledge to understand the importance, not only to their benefit, but most importantly to yours, the customer.
Feel free to contact me for more information on Flo-Tech’s predictive service.
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