Tesla & Cariad — Under the Magnifying-glass
The automotive industry must consistently adapt to changing consumer demands and preferences. When consumers purchase a vehicle, they want innovative features and a luxury feel. Two companies that have continued to meet consumer demands are Tesla and Cariad.
Tesla has become a household name with their line of luxury electric vehicles. On the other hand, Cariad is in a different position on the supply chain, remaining an automotive software creator for Volkswagen.
Today we will analyze if the position on the supply chain shows differences in the employment specifics of Tesla and Cariad. To do this, we will utilize Osterus, a software program that sorts through thousands of data points to create useful statistics that we can use for comparison.
Let’s first start with the top previous companies that employees worked at before going to Tesla and Cariad. We can see that 0.95% of employees worked at Apple before joining Tesla, with another 0.55% at Solarcity and another 0.52% at Amazon.
The data shows that 8.39% of employees previously worked at Audi, with another 3.60% at Volkswagen and 2.20% at Carmeq Gmbh. Tesla focuses on innovation, which is why we see employees coming from outside of the automotive industry; however, some industry experience would be useful.
Cariad does have employees coming from their primary clients, Audi and Volkswagen. This is beneficial to gain insight into operations and find new ways to innovate to benefit the end consumer. Moreover, when employees come from various companies, such as one from Amazon and another from Apple, it can be hard to implement effective training. This is why Cariad might see some advantages with a high number of employees coming from singular locations.
Moving onto the job titles, we see some similarities and differences in the areas each company prioritizes. Tesla has 10.83% of employees in the engineering category, while Cariad has 8.61% of employees there. Unlike Tesla, Cariad prioritizes software development, with 13.94% of employees located in that job title. This makes sense given that Cariad is a software development company, while Tesla focuses on the production of vehicles from start to finish.
The next highest category for Tesla is consulting, with 8.36% of employees there, followed by middle management showing 5.88% of employees in that category. Cariad only has 1.81% of employees in the consulting category and 7.31% of employees in the middle management category. The job title discrepancies support that these companies are found in different areas of the supply chain.
Next, let’s look at the education of employees. We see some similarities between Tesla and Cariad in education degrees, with 55.43% and 53.51% of employees holding bachelor’s degrees, respectively. In addition, 14.9% and 20.84% of employees have master’s degrees for Tesla and Cariad, respectively.
The distribution of these degrees is held primarily by males, indicating some diversity issues. The ratio of males to females with degrees is 76.65% to 23.4% in Tesla and 77.05% to 22.95% in Cariad. We would like to see this discrepancy decrease in the next few years as the labor force continues to move toward gender equality.
The top languages spoken also indicates differences. For both companies, the most spoken language is English, with 34.91% in Tesla and 31.69% in Cariad. The next highest language for Cariad is German, with 29.62%, while Tesla reports Spanish at 10.96%. This does make sense given that Cariad provides software to Volkswagen, which is a German-based company.
Finally, looking at the demographics of each company is very telling. Both companies employ a male-dominant workforce, with 73.7% males to 21.3% females in Tesla and 76.8% males to 21.3% females in Cariad. Looking at this data tells us that there are minimal differences in the gender of employees at different points in the supply chain.
Moreover, since Tesla is predominantly located in the United States, while Cariad is based in Germany, we can infer that gender differences exist regardless of geographic location.
In summary, Tesla and Cariad showed stark similarities in the gender distribution and male predominance in education degrees, while there were differences in the job title distribution. It will be interesting to see how supply chain disruptions and changing consumer demands impact each of these companies.
We would not be able to draw the conclusions that we did without the use of Osterus. Osterus breaks down complex data into readable and understandable statistics. This is just the beginning of the inferences we can make when partnering with a powerful software program like Osterus.
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