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Jason Doring

Recent Posts

Vehicle Data's Role in Grid Planning Explained

Electric Vehicle (EV) charging stations are a novelty right now, but in the United States, they will become both ubiquitous and a necessity in the next decade. The 2030 National Charging Grid Report finds 2.3 million charging ports will be needed to accommodate the 28 million EVs expected to be on the road by 2030, but as of right now, only 160,000 exist nationwide. This will be an enormously expensive venture – grid analytics company Kevala believes that California alone will need $50 billion to accommodate its EV and emissions targets. 

Utility companies will have an unprecedented amount of financial capital, scope of work, and public pressure to adapt their service areas to the EV era. While not applicable to all the challenges inherent in this transition, curated, in-depth, and accurate vehicle data will be essential to develop optimal grid planning strategies. 

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Topics: Electric Vehicles

3 Reasons Utility Companies’ EV Programs Need Standardized Vehicle Data

Legendary physicist Marie Curie once said “I was taught that the way of progress was neither swift nor easy,” and the United States’ inevitable nationwide shift toward fully electrified vehicles (EVs) is the perfect example of that sentiment. Many states have set ambitious initial zero-emissions targets as early as 2025, which will require radical infrastructure change and an exponential increase in consumer EV adoption.

The Inflation Reduction Act, California’s Advanced Clean Cars standards (which are opted into by an additional 14 states), and other state initiatives are kickstarting that adoption by offering numerous rebates and discounted billing programs for EV owners. These programs will present unprecedented operational challenges for the utility companies tasked with implementing and managing them. These challenges include parsing and processing a massive influx of new data, inconsistencies within that data, and continual shifts in guidelines and regulations that need to be followed as both the government and auto industry landscape evolves.  This article will outline the core benefits of ongoing access to in-depth, 17-digit VIN data in ensuring a sustainable, productive response to the US’ electric vehicle transition.

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Topics: Electric Vehicles

3 Ways OEM Service Schedules Data Can Transform Auto Service Businesses

Inflation has been outpacing wages for many years, which has created significant hardship for workers and forced them to extend the life of key necessities such as their personal vehicles. Kelley Blue Book (KBB) has found that the average vehicle life has now been extended to 12 and a half years, in an effort to avoid adding a new car payment to already strained budgets. Timely, cost-effective, and quality vehicle maintenance is necessary to attain this ambitious lifespan, and customers typically have many local options for servicing and repairs. The parts and services industry has become an enormous market ($137 billion in 2022 from dealerships alone) with intense competition, so how can these businesses generate the customer loyalty and positive experiences needed to thrive with repeat business and word-of-mouth recommendations? 

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Topics: Parts & Services, Service Data

Future-Proofing Your Auto Insurance Risk Analysis Modeling - Get the Whitepaper

The automotive industry is running parallel races toward fully electrified and fully autonomous vehicles, and both races have a deceptively close finish line. EVs will become the norm within 10 years due to a combination of government legislation and manufacturer mandates – Progressive estimates that EVs could comprise 40% of car sales by 2030. Vehicle autonomy, meanwhile, remains a top priority for OEMs as well, with the market projected to reach $200 billion by the end of the decade. Mercedes-Benz is already certified for Level 3 autonomy, a standard that encompasses conditional hands-free driving, suggesting that Level 5 (totally automated driving) is a feasible goal for automakers more quickly than initially anticipated.

The technology involved in developing electrified, autonomous vehicles will not be universal; each feature package will have its own unique benefits, drawbacks, and relationship to road conditions and driver capabilities. Consequently, auto insurers cannot treat “ADAS” or “EV” as monolithic or even loosely segmented variables in their risk analysis; all levels of the organization must have a comprehensive understanding of their car’s technology stack to maintain a balanced risk-to-rate ratio. 

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Topics: VIN, Insurance

Pattern-Level vs. Option-Level VIN Decoding: Which Does Your Business Need?

VIN Decoding solutions offer multiple levels of information for vehicle inquiries. Pattern-level VIN decoding provides information from the World Manufacturer Identifier (WMI), Vehicle Descriptor Section (VDS), the vehicle’s model year, and production plant. Option-level VIN decoding includes the serial number of the specific vehicle and often presents “as-built data” from the Original Equipment Manufacturer (OEM), such as installed options and packages, as well as the exact exterior and interior colors.

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Topics: VIN

Clear and Actionable Vehicle Data is Now Essential for Auto Insurers

Traditional risk models in the auto insurance space incorporate multiple data points, including vehicle details, the driver’s safety record, the vehicle’s geographic location, and that location’s associated weather patterns. While these factors may be weighed differently by each insurer’s model, the entire auto industry is now facing the reality that increased vehicle complexity will force a significant change to risk analysis. 

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Topics: Automotive Data, Insurance