Management Science, Innovation, Sustainability and Entrepreneurship (MISE)

The world is becoming richer in data and increasingly complex. Simple cause-and-effect relationships as a basis for management actions are becoming less reliable. We address this in our analytics group through sound data-based analyses and simulations of complex socio-technical systems. Decisions are effectively supported by scientific-statistical but management-oriented visualisation of complex data.

• Modelling and estimating the profitability and general development of performance variables in complex dynamic systems ("Business Dynamics").
• Developing, simulating and validating new (digital) business models
• Analysing business ecosystems and modelling future scenarios
• Reviewing and optimising systems in the operational area
• Topics include drug shortages, sustainability, energy modelling, availability of infrastructures under uncertainty, consumption and recycling of rare resources, acceptance of products in the electricity market, impact analysis of legislative changes on existing systems and business models, risk and customer modelling.

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

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).

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

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

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 (predictive maintenance)? 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