What are the best ways to stay organized in Operations Research?

Understand the game mechanics of the system you are interceding to optimize and exactly which metric you initially believe(hypothesis) you are maximizing or minimizing. For example, if you look at the fertilizer industry, you have to understand the volatility and supply chain of natural gas as all of the world's fertilizer is produced from ~5% of the world's natural gas production. The "game mechanics" are often amorphous and often entail taxonomy and schema discovery as you start mapping the problem and its variables. Define the metrics you think matter most, but be willing to abandon them completely as you will find new conflicting data to your thesis on any worthwhile problem.

Systematic Approach: Begin with expert interviews for domain understanding. Dive deep into data for comprehensive insights. Conduct a thorough literature review of existing approaches. 360-Degree Review: Propose solutions and undergo a comprehensive review. Seek feedback from business leaders, domain experts, and peers. Continuous Learning: Stay updated on emerging trends and methodologies. Keep a cheatsheet of proven tricks to enhance model performance. By following this systematic process and maintaining continuous learning, you ensure a well-organized and effective approach to Operations Research.

Like any other project, agility is very important due to the drift in business, project goals, and the market. Implement an agile process and use tools that will allow agility.

99% of the issues as it relates to operations research are: a. Modeling the problem b. Framing it within the context of defined measures (ex. kwh/mile etc...) c. Making sure you have the paranoia of knowing the latest technology stack in the target industry where you are optimizing things. "Only the paranoid survive." - Andras Grof d. Solving the problem is easy if you have done a-c properly. "A measure of Reality" is a must read book by any engineer who is worth their salt.

It is important to understand all types and classes of tasks in order to effectively solve optimization problems. To do this, it is necessary to study the relevant materials and have practice.

Information Organization: Develop a data management system: Choose a reliable platform to store, categorize, and easily access your data, including datasets, models, and research papers. Consider cloud-based storage for better accessibility and collaboration. Adopt efficient note-taking methods: Use digital notebooks like Evernote or OneNote to organize notes, formulas, and findings from papers and lectures. Employ clear titles, tags, and search features for easy retrieval. Maintain consistent file naming conventions: This simplifies searching and avoids confusion, especially when collaborating with others.

Collaboration and Communication: Effectively communicate your work: Use presentations, visualizations, and reports to explain complex OR concepts to stakeholders and team members. Consider collaborative tools like Google Docs or shared notebooks for joint projects. Establish regular check-ins: Schedule meetings or discussions with colleagues and supervisors to share progress, address challenges, and ensure alignment. Seek feedback and learn from others: Encourage open communication and actively seek feedback on your work to identify areas for improvement and stay up-to-date with new research and best practices.

Automate repetitive tasks: Utilize scripts or tools to automate tedious tasks like data cleaning or basic coding, freeing up time for more creative and strategic work. Maintain a physical workspace: If you work in a physical space, organize your desk, whiteboard, and materials to minimize distractions and optimize workflow. Review and optimize your system regularly: Reflect on your organization methods and adjust them as needed to adapt to changing projects and learning styles.