WHAT GIVES VINCENTRIC DATA ITS POWER?

Although there are many components that create the power inherent in the Vincentric data, there are three primary factors that drive the knowledge gained through the data:

Dynamic and Static Data – Because the marketplace changes every day, Vincentric has built its compilation system to allow the integration of updated costs, prices, and new vehicles to determine shifts in marketplace dynamics.

Multiple Sources – With both public and private licensed information used to compile the Vincentric data, we have developed accurate, sustainable data sources, with the necessary redundancies to ensure uninterrupted access to a steady stream of accurate, actionable data.

Data Quality Management – Effective data quality practices are critical to the development of insightful, actionable information. The disciplined, comprehensive approach to data quality management used by Vincentric powers meaningful statistical analyses and predictive models, which in turn create the unique Vincentric data.  This system is the foundation of the Vincentric information supply chain, and allows Vincentric to deliver the knowledge and insights that enable effective business decisions.

Some of the key data elements we measure are:

• Depreciation Costs  - Depreciation is the reduction in value a vehicle incurs during a given period of time. Using a combination of data sources, Vincentric estimates the annual depreciation on each vehicle using a basic set of assumptions.
• Fees and Taxes - Fees and taxes include sales tax for the initial vehicle purchase, registration fees, and license plate fees that add to the cost of owning a vehicle. Because taxes and registration fees vary greatly by state, especially for high priced vehicles, the Vincentric system can customize the values by state to better meet your specific needs.
• Financing - Financing is the amount it costs to borrow money for a vehicle purchase.  Using data from multiple lending institutions, along with averages provided by the financial industry, we calculate this “cost of money” to help determine overall cost of ownership.
• Fuel Costs - As the starting point for our calculations, we access the U.S. Government Environmental Protection Agency’s estimated mileage figures for both highway and city driving, then adjust based on the estimated percentage of mileage for these two types of driving. We then add in an estimated price for each gallon of fuel.  We update our fuel estimates monthly using industry sources that track up-to-date fuel prices nationwide.
• Insurance - Insurance costs vary by type of vehicle, driver, and coverage amounts.  Using data from multiple insurance industry sources, we estimate insurance costs for each vehicle in our analysis set.
• Maintenance Costs (includes scheduled and unscheduled) - Maintenance costs are affected by four key elements: frequency, labor rates, labor times, and parts prices. Maintenance costs are based upon the manufacturer’s recommended maintenance schedules, with unscheduled maintenance items such as tires and batteries added to determine overall maintenance cost. Any free maintenance plans offered by the manufacturer are included. To create data that is well-suited for comparison, we use both scheduled and unscheduled maintenance costs to estimate total maintenance costs.
• Opportunity Costs – This cost takes into account the loss of interest earnings that could have been earned if the vehicle’s out-of-pocket expenses had been invested into a savings account. The lost “opportunity” to earn interest income is an often overlooked cost of buying a vehicle, but nevertheless is critical to understanding overall costs and a key component when comparing one vehicle to another. Using data from respected financial information firms, we apply current savings interest rates to determine this cost.
• Repairs - Repair costs are estimated for what consumers will pay to keep their vehicle in operating condition, excluding the costs for scheduled and unscheduled maintenance.

The result is a data repository with the depth and breadth of data necessary to allow in-depth analysis to support critical business decisions.