The application of neural networks in the study of the influence of temporality on strategy map indicators in a Spanish hospital

Abstract

This article analyses the effect of temporality on the strategy map of a hospital by the use of neural networks. An attempt is made to temporally align all strategy objectives in order to test how temporality affects relationships between the indicators. The strategy map was prepared using a new method based on the European Quality Model (EFQM) and the BSC (Balanced Scorecard). Using the case of a hospital, and being based on the premise that the customer is the principal objective, this article demonstrates (by the application of artificial neural networks) that the two perspectives of finance, and learning and growth show a temporality of three and six months respectively in relation to prospective customers – as proposed by Kaplan and Norton (2002). In addition, the article considers whether the relationship between the financial perspective and the customer perspective is direct, or if other relationships exist between the financial perspective and internal processes or training and growth; this is possible because artificial neural networks (ANNs) allow for the simultaneous inclusion of the interrelationships of all the indicators upon introducing the deduced temporality into the strategy map. The effect of the existence of internal relationships between indicators of the same perspective is also analysed.

Keywords:

• business excellence
• Balanced Scorecard
• management and organisational strategy
• quality management
• enterprises strategy
• obtaining indicators
• performance measurement