Method To Evaluate Factors Influencing The Energy Efficiency Index Of The German Industry

Indices allow for representing large amounts of data and converting diverse data into a ratio. This creates measurable ratios, providing a basis for forward-looking decisions. One such index is the Energy Efficiency Index of the German Industry. In its six-monthly survey cycle, it maps the German industry’s energy efficiency state, using various survey factors within its three sub-indices. Although the index observes and evaluates the energy efficiency climate with specific analysis models, external influencing factors have not been included in the analysis. This paper addresses this issue by proposing a new analysis model. It combines two methods: influence factor derivation and index analysis. The influence factor derivation generates an influence factor from specific external influences, while index analysis is used for user-independent analysis, based on the component model for time series. Combining these two methods enables a relative evaluation of external influences directly related to the index. With the new analytical method an influence-adjusted index trend can be derived. This method also allows for evaluating an influence-corrected index trend specifically for the Energy Efficiency Index of the German Industry. Transferring the proposed method to other indices opens up new application areas, such as predicting the impact of a particular event.