The number of studies that assess the level of maintenance in a country is still very small, despite the contribution of this area to national competitiveness. The literature analyses asset management based on key performance indicators, but not via a multicriteria model. This chapter describes a multicriteria model, constructed by means of the fuzzy analytic hierarchy process (FAHP). The weightings are converted into utility functions, allowing the final utility of an alternative to be calculated via a multi-attribute utility function. Data on the state of asset management in Spain, in 2005 and 2010, are used to produce discrete probability distributions. Finally, a Monte Carlo simulation is applied to estimate the uncertainty of a complex function. In this way, the level of excellence of asset management in small businesses in Spain, before and after the recession, could be determined. The results show that the economic crisis experienced in Spain since 2008 has had a negative effect on the level of asset management in most sectors.
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Asset Management has an increasingly important role in organisations, because it can affect productivity and profitability (Alsyouf, 2007; Mazidi et al., 2017; Raknes et al., 2017), the useful lifespan of the facilities, the quality of the processes (Carnero and Gómez, 2017) and compliance with safety and environmental standards, and it is currently important to ensure the sustainable and productive operation of resources (Younus, Fahad and Khan, 2016). This has brought about increasing concern with the measurement of performance asset management (see for example Bazrafshan and Hajjari, 2005), as shown by the abundant literature analysing the matter (see Raouf, 1993; De Groote, 1995; Martorell et al., 1999; Löfsten, 2000; Chan et al., 2001; Kumar, 2006; Parida and Kumar, 2006; Muchiri and Pintelon, 2008; Tsarouhas, 2013; Kumar et al., 2013; Pekkola et al. 2016; Gonzalez, et al. 2017; Shohet and Nobili, 2017).
Different countries carry out surveys through their national maintenance associations. In the case of Spain, the Spanish Maintenance Association (SMA) carries out surveys every five years; these suggest how maintenance can contribute to improvement in the most immediately apparent weaknesses of the Spanish productive sector, such as the lack of competitiveness and innovation (SMA, 2010). Other results from Spanish companies are described in Conde (2007) and Álvarez (2007) in the chemical industry, and in Paredes (2007) in manufacturing. These national surveys encourage continuous improvement in asset management by the use of benchmarking. However, while in the United States, Canada and New Zealand this tool is used extensively, in Spain it has scarcely been used at all. (González, 2007).
The literature assesses asset management in a number of countries, generally using a set of Key Performance Indicators (KPI). These KPIs are given similar importance, despite the fact that some KPIs influence the competitiveness of a company, while others only have slight implications for cost. A multicriteria model, then, allows a more accurate assessment of the real situation in applied asset management to be made, as it allows the real importance that each KPI has for the company to be assigned. Using a multicriteria model, it is possible to obtain a value for the overall performance of maintenance, and for each criterion analysed. This shows the development over time of applied maintenance, the criteria with the highest valuation, and those where there are deficiencies. Benchmarking also generally makes a comparison between the mean values of each KPI, produced from the data of a given industrial sector or the general situation of the country, with those obtained from a company (Komonen, 2002); however, in the subject of asset management, this type of benchmarking is of little use (Komonen, 2002; Dwight, 1999). Asset management benchmarking is considered essential to achieving world-class maintenance performance levels (Madu, 2000) and a process of continuous improvement (Ahrén and Parida, 2009). Only 11% of the literature analysed in Simões et al. (2011), however, includes benchmarking or relates it to maintenance performance measurement.