In a recent eBook, Dr. Rob Nelson shared how to achieve business at the speed of now by driving business results with intelligent analytics and decision-making using real-time streaming data.
There are many sources for data appropriate to streaming processing and advanced analytics. Let’s dive into a specialized topic – Customer Location Intelligence – and look closer at predictive maintenance and performance optimization which rely on sensor-driven real-time customer location data. This use case can be quite relevant and transferable to other types of data and circumstances. Plus, you can see how bringing different data sets into the mix with AI is very powerful.
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With more than 30 billion things connected to the Internet, IoT presents a significant challenge and opportunity for enterprises to ingest effectively, process, manage, store, and drive insights from all the data generated by connected devices and assets. Take the case of auto manufacturers and dealers and even car rental agencies. At most auto dealerships, services is the main contribution to profit and the increasingly elusive but business-critical customer loyalty.
Automotive Repair & Maintenance Service Market
Consider also that Automotive Repair & Maintenance Service Market Is Estimated to Reach USD 810.30 Billion By 2026.
Last year, dealerships wrote more than 310 million repair orders, with services and parts totaling more than $116 billion. That’s some definite hits to the driving consumers or any vehicle fleet owners’ wallet book.
At the car dealer, the service advisor is usually your first and primary contact at the auto dealership. The service advisor is responsible for understanding what needs to be done to your vehicle — routine maintenance or addressing a specific concern.
This is a critical reactive step in the process because the service advisor must interpret and note these concerns on the paperwork in terms the service technician will understand.
Most service advisors will repeat all problems and services requested in a concise form to ensure that no miscommunication has occurred.
Upon the customer’s sign-off of the estimate for service, the paperwork is distributed to the dispatcher (see below) for routing.
But, this is reactive and inefficient. It doesn’t intervene on service opportunities that are real-time and location and vehicle specific.
It is time for something different.
Enter the Connected Vehicle
With real-time data streams that include vehicle performance data and location and driving patterns, it is possible to identify problems before they manifest, to identify sub-standard performance that can be tweaked with some proactive maintenance to save hassle, miles per gallon performance and larger, unwanted bills.
- Behavioral Data is generated by, or in response to, the driver’s use of the vehicle. For example, telematics data is relayed about speed, steering, braking, and fuel-efficient driving. It can even be used to issue alerts due when data suggests driver fatigue.
- Diagnostic Data results from the ability to access a vehicle’s data, enabling car dealers or rental agencies to assess a vehicle’s health and notify drivers when a service is required with in-car voice communication.
Not only can the alerts and use of machine learning for predictive maintenance identify when and what type of proactive intervention is needed based on actual vehicle performance, but the entire process of enacting a service event can also be triggered automated from scheduling to check-in to pick-up.
Real dollarized value creation for both the owner/driver and the dealer or renter in terms of fuel and maintenance can be tracked and articulated to customers or rental agency that dollarizes the impact. There are many benefits, including:
- Improved vehicle performance
- Reduced downtime
- Cost avoidance
- Proactive, hassle-free customer engagement
For rental agencies and other fleet owners, the dilemma is often to cut costs while also providing the services necessary to maintain and grow the customer base and provide better service.
This real-time predictive intervention translates to real savings and efficiency while helping assure maximum uptime of the vehicle asset while lowering total vehicle costs by avoiding some more expensive repairs down the road.
Intelligent vehicle management and automated service using actual location data with GPS and real-time performance monitoring are disrupting the world, and it should. We are only beginning to realize what is possible real-time data and machine learning to drive efficiency, cost-savings, revenue opportunity, and genuinely better customer experience.