Registration is now closed - Sustainability and Digitalization
How sustainability drives the business to build a long-term competitive advantage
21.03.2023 | 9 am to 5 pm
Siemens Arena of Digitalization Bad Neustadt
Sign up now. We look forward to meet you personally at this exclusive event on 21.03.2023 from 9 am to 5 pm in the Siemens Arena of digitalization Bad Neustadt an der Saale.
- Achieving more with less – sustainable innovations in the heavy equipment industry require to rethink the business.
- How can the challenges of sustainability be transformed into new opportunities?
- The approach – achieving tomorrow's sustainability goals with today's technology.
In this event, our experts and customers such as Accenture, Teamviewer, Schaeffler, Siemens Digital Logistics, Siemens Digital Industries and other interesting companies from the heavy equipment industry, will present and discuss how digitization is intelligently used across the entire value chain to become more resource-efficient, reduce emissions and enable a sustainable circular economy.
This day is aimed in particular to all companies in the fields of agricultural technology, material handling as well as construction and heavy machinery.
Transform your business model into a sustainable digital model
Traditional business models usually focus on short-term, financial KPIs and not on creating long-term added values through profitable, sustainable and circular cycles. Hence our thesis: without digital transformation, the sustainability goals cannot be achieved.
Managing the complexity of the ecosystem
A look at the heavy equipment industry shows that many processes still consist of processes, silos and individual tools that lack standardization and are often not connected. Hence our thesis: without the use of a holistic digital twin, no sustainable ecosystem can be built.
From individual data to holistic decisions
Many companies in the heavy equipment industry collect data and unfortunately do not know how to use it effectively to reach their sustainability goals and optimize their operations. Hence our thesis: Without intelligent use of this data, no right decision can be made.