The Energy & Utilities companies, operating in a market subject to strong competition, are required to manage their activities in a context increasingly characterized by high competitive pressure, driven by "non-programmable" renewables, new risk factors and new variables. Faced with this reality, digital innovation assumes an increasingly strategic role, providing new forms of knowledge and new tools that increase access to information, precision in identifying market opportunities and threats, in analyzing impacts and in the assessment of consequences.
The key factor underlying this evolution is to be identified in the data driven approach, i.e. in the growing availability of data (in terms of volumes, speed and variety) and in the possibility of having tools and algorithms to process new information. thanks to the help of Machine Learning and Artificial Intelligence techniques that allow companies, which will know how to orient themselves along new lines of innovation, to operate effectively and efficiently in the global energy ecosystem and to improve their performance by drawing on historical data, information already available in the company and new market information that can be more easily integrated than in the past, through the real-time modeling and simulation of new business scenarios, optimizing company performance and supporting strategic planning.
At Power Reply we help companies to implement data-driven solutions by formulating strategies that support the transformation process with Big Data, Machine Learning and AI at the center. From the pilot to the project in production, using a design-oriented methodological approach, we implement innovative strategies able to reconcile business needs and application constraints. We offer consulting and advisory services to support our customers in the design and implementation of Data & Advanced Analytics Platform, in the analysis of Business processes and optimization or forecasting problems whose resolution requires Machine Learning and Artificial Intelligence models, in the creation of Data Labs, in the definition and adoption of a data strategy that embraces technology, methodology, processes, people and corporate culture.