Energy consumption prediction

Annual energy expenses represent a major portion of variable costs for companies in many industries. With an active approach to forecasting, purchasing, and optimization companies can directly address and decrease these expenses.


By combining historical data from the client and knowledge of external factors such as the weather and special events, mathematical and statistical methods can be used to accurately estimate future energy requirements. This process combines a data warehouse for storage, analytical software for statistical analysis, and a user interface application tailored to the client's needs so  the client can model and visualize potential future outcomes.



Deloitte tailors each quantitative analytic model according to each particular business case. These models can be implemented either in a client's system or delivered as an automated report. Once active the model is easily adjusted as a client's needs or business requirements change.

99% Deviation penalty reduction Large railway company, 2014


Filip Trojan

Filip Trojan

Senior Manager

Filip is a Senior Manager in the Advanced Analytics deparment. He has over 15 years of experience in analytics, machine learning, mathematical optimisation and data science. He has an extensive variet... More

Veronika Počerová

Veronika Počerová


Veronika is a manager in the Advanced Analytics department. She specialises mainly in analytical end-to-end solutions for clients from the finance, energy and retail industries. She focuses on predict... More

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