vehicle component information

What is Carwatch?

There are currently about 1.3 billion motor vehicles worldwide. Electric cars will further boost growth. By 2030, a world stock of 2.3 billion vehicles is expected (UPI Institute). Other studies are more cautious about the speed of growth and expect it to peak at 2.7 billion by 2050. Nevertheless, the numbers are increasing, the model ranges and variants are becoming more diverse, and the degree of vehicle distribution in more and more regions of the world is approaching that of the western industrialized countries.

Motor vehicles are among the most observable consumer products on the market, if only because of the official registration and approval requirements. The information obligations of vehicle manufacturers and suppliers in the context of product safety in conjunction with the vehicle recalls, which may have to be published, as a result, create a fundamentally high level of confidence in the product “vehicle.” But, does the reality live up to this high level of trust?


Since the “diesel scandal,” at the latest, confidence in car manufacturers has suffered considerably. And so private and commercial vehicle owners, professional service providers such as garages, insurance companies, and leasing firms, and even automotive suppliers ask themselves questions such as:

  • Do we really know about all of the current recalls?
  • Do we get the necessary information as early as possible, or only then, when it can no longer be avoided?
  • Are all relevant facts about a case published, or is information withheld?


If you want to find out more about a particular vehicle manufacturer, model, or even year of manufacture, publicly available information is generally a good source of information to start with. But if you want to question this information or also draw realistic comparisons, you quickly reach the limits of such one-dimensional information. Instead, there are questions such as:

  • Is the vehicle type of interest really so error-prone, or can this be limited to specific assemblies/components?
  • Do failures of certain vehicles have any correlation with cars of other manufacturers?
  • Do the rankings for errors and recalls change if the horizon is extended to include other markets?


In the end, it is always interesting to take a look into the future. If current and historical data are available in sufficient quantity and quality, mathematical-statistical methods can be used to make predictions about future behavior. Although these are always associated with statistical deviations (variances), they still provide a solid planning basis for many activities. Especially in a professional environment, this can help to clarify exciting questions, such as:

  • At what mileage does a vehicle owner have to be prepared for major repairs?
  • What (realistic!) workshop and replacement cycles can a leasing company expect for its vehicle fleet?
  • What financial provisions does an automotive supplier have to make to cover the risks of the next 6 to 24 months?