Abstract
We study financial management performance during 2008–2013 for the Spanish aerospace manufacturing value chain and the links with managerial decisions. Data from company financial statements is analysed with Principal Component Analysis, Data Envelopment Analysis and an Artificial Neural Network. Top financial performers focus on liquidity management rather than on returns: both in the short term, by increasing levels of current assets and funding them with short-term liabilities, as well as increasing asset turnover; and in the long term, by aligning equity to non-current assets, while reducing asset and debt intensity levels. Only the manufacturing value chain is analysed, showing the potential for future research in related fields (e.g. Value chain, country). Benchmarking and forecasting financial performance yields information and enables agility and accuracy in the strategy setting process. This study makes a unique contribution because it applies the scientific method where no previous related studies have done. It offers the novelty of using a single metric while Ratio Analysis requires multiple unweighted measures. We contribute by: (a) providing a method based on publicly information to benchmark and predict financial performance, thus offering benefits for aerospace stakeholders and academia; and (b) employing a big data sample that closely represents the population.
Highlights
Benchmarking the managerial decisions that drive financial performance in a sector yields important information for companies, associations, researchers, other related industries and governments
The only information it requires is that provided in financial statements, which is an advantage for a number of reasons: (a) no proprietary databases are needed as data can always be gathered from free access sources that are audited by an independent third party organization; (b) the use of standard information and variables allows comparison; (c) scale effect is avoided because the measurement model relies on ratios, and (d) simplicity, reliability and robustness is achieved by using commonlyaccepted financial concepts and metrics
A super-efficiency Data Envelopment Analysis (DEA) model, which broadens the range of efficiency, may be applied; it would subsequently be expected that the Artificial Neural Network (ANN) result, as displayed in Figure 3, would be smooth along the fitted regression line on such points
Summary
Benchmarking the managerial decisions that drive financial performance in a sector yields important information for companies, associations, researchers, other related industries and governments It is even more crucial for certain strategic sectors, such as the aerospace manufacturing sector. Some other factors that differentiate the aerospace industry from other industries are: the dumping effect due to the military-defence dyad, delivery of high value added products and services, and high entry barriers (high investments, complex products, short series, long development lead times, and high pay back periods) It is worth studying a sector that moves in the opposite direction to national industrial trends and actively contributes to Spanish economic recovery.
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