Making data available to users can be an effective way of providing clear information. This can ensure transparency, bring about changes in behavior or even exercise control.
In retrospect, it is fundamentally informative to analyze which data actually provides a benefit for a longer operating phase. One example is feedback systems that give users insights into consumption, action patterns or op
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erating data. The continuous provision of high-resolution data can help to rethink consumption patterns or technical changes, especially in the initial phase. In the longer term, however, often only minor effects can be triggered because interest cannot be maintained or potential has been exhausted. Studies that have investigated the longer-term effects of feedback systems on energy consumption have come to very different and sometimes contradictory results, so that the analysis of longer-term effects can be informative (see, for example, Aretz et al. (2022), Tiefenbeck et al. (2019))
An evaluation of the routines by the users can be used to assess how the offer is used and also which data provision can still achieve effects in the long term. This can be done, for example, by evaluating the number of visits to a website or by conducting a survey, which can also provide qualitative insights into which data is used in detail.
Sufficiency measures:
Various sufficiency measures can be derived from this, which can reduce the overall volume of data:
The collection of data can be reduced if data does not provide any additional benefit or the information is not requested by users. This can minimize the number of measuring points.
The processing or preparation of the data can be simplified. This can be particularly effective for computationally intensive data processing steps, for example with the so-called NILM algorithms (non-intrusive lo
ad monitoring), with which total consumption data is traced back to individual devices based on their characteristic patterns.
The frequency of data collection can be reduced if high-resolution data collection does not have an effect or does not meet with interest. High-resolution and processed data can also be provided after the introduction of a digital offering, which is then continued after an initial phase with a lower frequency as the default setting. The phases of high-resolution data collection can be repeated at regular intervals or on request.