Data Driven Energy Decision Making

Problem description

Energy saving and energy efficiency has been a strategic area of the ​​state policy and one of the factors of regional development for more than twenty years. However, many years of attempts to improve legislation in the field of energy saving have led to the adoption of ineffective bylaws on energy saving and have created a functionally unstructured, amorphous system of public administration in this area. As a result, most energy saving measures are chaotic, fragmentary in nature, and do not give tangible results.

A modern  energy saving ideology requires a comprehensive strategy to successful problem solving and effective decision-making , which utilizes a DDDN (Data Driven Decision Making) – decision-making based on data approach. Its main postulate is that decisions must be made based on the data analysis, not intuition or personal assumption. Applying this approach in energy efficient development, a realistic picture of what is happening in the field of energy consumption is required to choose the right strategy for the regions.

Ways to solve the problem

The first practical step towards implementing the DDDN strategy in the field of energy efficiency in buildings was the development of the National Database of Energy and Performance of Buildings as the official government source of data for informed decisions on thermal renovation. One of the important criteria for the functioning of the National Database of Buildings is availability of sufficient data in the system (at least 90% of institutions involved). That guarantees that information on energy efficiency of building stock is reliable and can qualitatively affect the calculation of indicators for medium-term planning.

To address this issue, FIATU LLC has developed and implemented an effective algorithm for data collection in 24 regional state administrations, based on the optimization of communication links and the application of an effective scheme of documentation and information flows. As a result, the level of involved institutions of the 1st wave of regional state administrations was increased from 70% to 94%, while the involvement of the 2nd wave oblast institutions varied from 90 to 100% at the initial stage due to the correct expert support strategy.

The main factor of success is continuous expert support of the process.

Results and benefits

The result is the dynamic array of quality data with over 600 thousand indicators (operational, technical, energy consumption, etc.), which grows monthly by 50-60 thousand indicators. The data are already used in publicly available energy efficiency ratings by region. The collected data are a worthy basis for the development of the state and regional medium-term plans for thermal modernization of buildings and further verification of the effect of the implemented measures.

We provide the state with an invaluable tool for implementing energy efficiency policy aimed at increasing the level of regional development.

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