Nowadays organisations in every sector need to develop effective strategies for real-life problems arising in dynamic and complex systems under various uncertainties. Practitioners apply OR to transform complex challenges into business opportunities. In this process, various OR methods in conjunction with data analytics can be used to help organisations for making "better decisions" at strategic, tactical, and operational levels by using real/raw data (as supposed to intuition, artificial or observation).
Moreover, potential effects of these decisions on their own business operations need to be analysed to reduce impact of uncertain factors, and consequently to increase revenue and resource utilisation. To achieve business goals and increase their market share, organisations do not only invest on OR analytics and put more efforts on data collection/storage, but also become critical consumers of OR as they intend to effectively utilize data and explore how to apply decision-making tools for improving operations.
The special interest group 'OR in Practice' aims to create a platform to disseminate knowledge and understanding of OR approaches to structure business problems, develop models and propose solutions for real-life decision-making problems of complex business systems. The ORP network will support OR practitioners and academics from public and private institutions to collaborate, share experiences and help to learn from each other.
We intend to build bridges between academics and practitioners from different industries, as well as to foster collaborative research among different groups within the OR community with industry. Thus, the ORP platform aims to help OR practitioners and academics to make further impact for a better world.
For those applying operational research in real settings, OR68 offers a place to share what works, what doesn’t, and why. The conference brings together practitioners and researchers to discuss practical methods, implementation challenges, and lessons learned from turning analysis into decisions that hold up in the real world.
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