Management Science, Innovation, Sustainability and Entrepreneurship (MISE)

The world is becoming increasingly data-rich, interconnected, and complex. Traditional cause-and-effect models are often no longer sufficient to support well-informed management decisions.

Our analytics group develops data-driven models and digital twins and applies them to digital product passports, lifecycle and transparency analyses, and simulations in order to better understand complex socio-technical systems and support decision-making under uncertainty. By combining statistical methods, simulation, and intuitive visualization, we make complex relationships understandable and actionable for decision-makers.

• Digital Twins and Simulation: Development of digital twins for the analysis and simulation of complex systems. This allows scenarios to be tested and the potential impacts of decisions to be assessed at an early stage.

• Business Dynamics and System Modeling: Modeling and simulation of the economic development and performance of complex dynamic systems.

• Digital Product Passports and Data Ecosystems: Analysis of information architectures and data platforms for digital product passports, as well as their role in transparency, the circular economy, and sustainable value creation.

• Digital Business Models and Information Platforms: Analysis, development, and simulation of data-driven business models and digital platforms.

• Data Analysis and Visualization: Development of scientifically grounded, management-oriented visualization methods to support complex decision-making processes.

To develop a low-carbon, sustainable economy, companies must be able to assess and respond to environmental, economic and social challenges. We offer relevant knowledge and tools that accelerate this transition. This includes advice on topics such as:

• Applying environmental and social impact assessment tools (life-cycle analysis, LCA).
• Assessing sustainability risks
• Mapping multidimensional benefits to achieve sustainable business model innovations
• Developing circular strategies across the value chain (from product design to take-back and remanufacturing), pathways to waste recovery (biomass and industrial residues), energy efficiency and cleantech

MISE: Sustainability and Circular Economy

Due to increasing shares of external value creation and the growing complexity of long supply chains, the holistic design and management of value creation with an end-to-end view is becoming more and more important. While in the past there was a strong focus on cost drivers and efficiency gains, issues of resilience, transparency, sustainability and collaboration in multi-level supply chains need to be addressed equally.

• Analyse the supplier base, increase transparency and assess resilience and supply risks (supply chain risk management).
• Design sustainable supply chains from raw material to consumer
• Optimise collaboration and connectivity with external supply chain partners (suppliers and customers)
• Evaluating and implementing innovative technologies and applications for logistics and supply chain (SupplyChainTech)
• Strengthening and professionalising logistics and purchasing organisations as central "value creation managers" within the company and at the interface with external supply chain partners
• Advising and supporting large-scale procurement projects and investment decisions according to aspects such as total cost of ownership, sustainability and public procurement (BöB/VöB).

MISE: Supply Chain Management and Logistics

Start-ups, entrepreneurship and entrepreneurial action are important impulses in an engineering degree. We promote internal innovation and talent. We provide a range of services for students and employees from the first contact with the subject to the spin-off of the BFH-TI.

• Accompanying innovation projects with tried and tested methods
• Acquisition of entrepreneurship-specific funding or projects
• Accompanying the work of students and employees in the context of entrepreneurship

Increasing competitive pressure forces innovation: New products, services and business models are waiting to be developed. But how exactly to go about it? How to design an innovation process? Which methods to use? Which new product-service-oriented business models should be developed? How to validate the business models with customers? Our group can help you master your innovation tasks with methodological support. As part of Innosuisse projects, we provide external innovation services for your success.

• Analysing competitive situations using innovation management methods
• Developing product-service-oriented business models: Developing, reviewing and implementing new business models in industrial SMEs
• Reviewing and optimising innovation processes
• Consulting on agile innovation methods such as Lean Startup, Design Thinking and other creativity methods
• Establishing cooperation models between established companies and start-ups

New findings in digitalisation and automation that are relevant for production landscapes are emerging almost daily. But when are these useful for an existing system? How can the performance of existing systems be optimised? How should maintenance be carried out? Our group addresses these and other questions about production management.

• Advise on automation projects and feasibility studies, concept design, software implementation
• Calculate the profitability of procurement projects
• Analyse data-based production systems in order to optimise them
• Optimise the maintenance of plants through maintenance strategies (predictive maintenance)
• Simulate logistical systems with the aim of optimising them
• Analyse the integration of industrial robots and collaborative robots into the production process
• Support the evaluation and execution of IoT applications in the digitalised production landscape

MISE: Predictive Maintenance

Organisations generate more data than ever, but turning that data into well-designed, efficient processes remains a challenge. Our group researches and applies methods for process digitalization, automation, and information management along digital value chains.

We help companies and organisations to:

• Analyse, model, and optimise business processes (BPM, BPMN)
• Design and implement automation solutions (RPA, hyperautomation, low-code)
• Manage information flows across complex, multi-tier value chains
• Apply AI-based approaches to process analysis and generation
• Develop maturity and governance models for process digitalization

Our work combines applied research with hands-on practice. The Digital Value Chain Lab (DVC Lab) serves as our living research and teaching environment, using a real coffee roastery to demonstrate end-to-end digitalization from raw material to consumer.