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Would an Early Warning Radar help to prevent recalls? And if yes, why isn’t there one in place?

An analysis of last year´s car recalls and presentation of an preventive method using an Early Warning Radar.

The most important facts around recalls:

  • The overall number of recalls is increasing; in recent years, an increase of 10% per year was recorded in the USA alone, and the number of vehicles affected has also risen significantly (2018): 929 recalls / 750 different error characteristics). This is related to increasing legal requirements (e.g. environmental). The increased stakeholder interest (loss of trust among customers, employee liability, availability of information, public discussions) is aggravating the situation.
  • An analysis of the recall statistics showed that 2/3 of all recalls were caused by integration with the OEMs, only 1/3 by problems with suppliers.
  • The focus is on assembly and design errors
  • Drivetrain technology is by far the most affected by recalls, 28% of all error characteristics can be assigned either to the engine/fuel supply module or to the axles and suspension module – both modules are part of the drivetrain technology.
  • Most recalls are safety related (affected modules including engine/fuel supply, axles and suspension, seats and belts, airbag systems, steering systems).
  • In 2015, BMW recalls vehicles from the X3 and X4 model series, the reason being: possible breakage of the Isofix child seat fasteners. This is followed by a recall from Mercedes in 2018, the reason being: the Isofix console for attachment to the chassis does not meet specifications. One and the same component – with almost identical error descriptions – would Mercedes have been able to avoid the recall?

Preventive work: 6 Steps to recall prevention using an Early Warning Radar

  • Extract data records from the available sources: Rapex (Europe), ADAC (Germany), DVSA (UK), NHTSA (USA), Transport Canada (Canada).
  • Analyse, interpret, and consolidate data records from multiple source recalls.
  • Combine recalls to manufacturer-independent error characteristics to ascertain whether the same error characteristic exists for several manufacturers and has led to the same recall.
  • Refine error characteristics (What? Why? Because of? Who?)
  • Use the now available database and the company’s own experts to analyse the results and derive measures if necessary.

Why recall statistics are not assessed preventively – an analysis

An increase in recalls significantly increases warranty costs. As a rule of thumb, it can be said that by reducing the cost of recalls by 50%, the return on sales can be increased by 10% – another aspect to consider is the loss of image and trust caused by the recalls. In markets such as the Asian one, for example, this can have a considerable impact on the market position of a Premium OEM.

A comprehensive worldwide evaluation requires not merely the data evaluation of, for example, the ADAC, but that of all databases. In addition, the data alone are not sufficient; they must be interpreted. This means a necessary investment to minimise a potential risk which would only become concrete once the actual recall takes place.

Do you want to avoid recalls in the future and are you interested in our Early Warning Radar?

We look forward to hearing from you and to a non-binding discussion.

Männliche Person, braune kurze Haare, braune Augen, lächelnd, trägt ein weißes Hemd, eine dunkelblauen Anzug, stehend mit beiden Händen in den Hosentaschen
Männliche Person, braune kurze Haare, braune Augen, lächelnd, trägt ein weißes Hemd, eine dunkelblauen Anzug, stehend mit beiden Händen in den Hosentaschen
Maximilian Klee
Senior Partner

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