Interview with Stefano Prosseda from Würth Italia

In each MODERATE project newsletter, we’re interviewing one of the project partners to get to know more about them and their role within the project. This time we’re having an interview with Stefano Prosseda, Innovation Manager at Würth Italy who are one of our key industry partners involved in testing and providing feedback to the data-driven services of the MODERATE platform for monitoring building performance. Their expertise as a leading provider of construction products is essential to ensure our solutions meet industry needs. We’re discussing their role in the project, contributions, and how the data-driven services from MODERATE can meet the industry needs.

Download the interview on pdf here

  • Thank you for taking the time to speak with us. Could you please provide us with some background on Würth Italy and explain your company’s role within the MODERATE project?

 

SP: The Würth Group is the global market leader in the development, production, and sale of fastening and assembly materials. More than 400 companies operating over 2,500 branch offices and shops in more than 80 countries form part of this global family business, which hails from the German town of Künzelsau. Würth Italy is the Italian subsidiary, and also the biggest one after Germany, serving 300.000 customers in Italy across 8 market sectors, reaching about 800M€ turnover. Würth Italy has a specific domotic and building automation product line, where we directly develop new products, which we also use on our premises to efficiently manage energy consumption and comfort. Our role in Moderate is to provide smart-building-related data from 20 out our +200 Retail shops, in different climatic zone, to train algorithms, dashboards and explore data marketplace opportunities.

 

  • How does Würth Italy see the role of data-driven solutions evolving in the construction industry, and what impact do you think they will have in the coming years? How do you think MODERATE can further enable this?

 

SP: All our R&D projects on the smart building topic always include a very extensive part on data management and in the development of data-driven applications, KPI or Proptech solutions. We expect the market will soon shift its interest more on value-added services than on mere hardware, which however will always need to meet high expectations in terms of reliability, quality and ease-of-installation. MODERATE will support a very important acceleration on data-driven solutions, by focusing on al the interoperability challenges, including GDPR-related complexities, and also extensively exploring « data cooperation » between many stakeholders and related opportunities.

 

  • As a marketplace for building datasets and open-source data-driven services, the MODERATE project offers a unique opportunity for innovation in building performance monitoring through data-driven solutions. From Würth Italy’s perspective, what do you see as the most important innovation that the project will offer? Additionally, which data-driven service are you most excited about implementing in your business beyond the project?

 

SP: Synthetic data is one of the main innovative topics MODERATE is focusing on, which is of high interest as a general « unlocking » technology to extract value from data in respect of GDPR. We are also very excited to test data-driven applications, such as predictive analytics, because the knowledge-mix of all the MODERATE partners will provide a state-of-the-art KPIs which we will integrate in our future devices, for the benefits of our customers, as well for the energy efficiency of our +200 stores in Italy.

 

  • What makes MODERATE unique according to you?

 

SP: We think MODERATE perfectly represents a next-generation Horizon project « model », where attention on data interoperability and data value exploitation will be the key in every technology is going to be developed in the smart building and generally IoT sector. We think there should be a « small MODERATE » project in every future Horizon project on data-driven topics.


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