Using publicly available financial data to measure production depth in the automobile industry

Abstract

Often companies must make the decision whether or not to manufacture a part on their own or to outsource the manufacturing of that part to a supplier. The results of these "make-or-buy" decisions have impacts on that company's manufacturing competencies and strategies moving forward [1]. They also compound over time to define that company's production depth. A company's production depth is defined as the ratio of value-adding content that a company creates itself [2]. While the impact of "make-or-buy" decisions have clear implications on a company's long-term strategies, the relationship between a company's production depth and its profitability has not yet been studied as there is not a defined way to measure production depth from a company's publicly available financial data. This study examines two different methods of estimating production depth using publicly available financial data.

The first method uses the ratio of raw and in-progress materials versus finished goods in a company's inventories to represent the company's production depth. The second method for estimating production depth is the ratio of the difference between the company's manufacturing cost and total trade purchases to its total cost of manufacturing. This study used the first method to evaluate different automotive companies' production depth in 2018. This study also examines BMW's production depth using both methods. The first method of measuring production depth is advantageous because all public automotive companies published the data on their inventories necessary to make the calculation. The second method is advantageous because it takes into account costs with manufacturing outside of just material costs.

While there were no statistically significant relationships found between this study's production depth estimates and profitability, applying these two methods two automotive companies allowed us to gain insight into estimating production depth using publicly available financial data.