This really resonated, especially the idea that software just speeds up bad processes, nice perspective Fady. How do you usually get teams to pause and question the process before jumping into building tools?
Before optimizing code, optimize the process
Fady-Desoky-Saeed-Abdelaziz
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— Originally published at dev.to
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Fady-Desoky-Saeed-Abdelaziz
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Thanks Andrew, I really appreciate that.
What usually helps is making the process visible first (simple mapping), then asking uncomfortable questions about waiting time, real value, and which steps could disappear.
Once teams see the workflow clearly, they often start questioning the process itself before jumping to tools, and that’s often where the real optimization begins.
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Cairo, Egypt • linkedin.com/in/fadydesokysaeedabdelaziz
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I am a data analyst with a software engineering background, working across data engineering, system ... Show moreI am a data analyst with a software engineering background, working across data engineering, system optimization, and sustainability analytics.
My work focuses on understanding how systems behave in real-world environments, particularly in terms of performance, scalability, and resource consumption. I am interested in using data-driven approaches and machine learning techniques to analyze system behavior, identify inefficiencies, and support the development of more efficient and sustainable systems.
I have worked on projects related to software energy consumption, urban mobility analytics, and NLP-based systems. These experiences allowed me to explore how data can be used not only to describe systems, but to improve how they operate and scale.
In addition to research-oriented work, I have practical experience with enterprise data systems, including data quality improvement, reporting, and process optimization. This has shaped my approach to problem-solving, combining analytical thinking with an understanding of real-world constraints.
I am particularly interested in building systems that are efficient by design — systems that balance performance, scalability, and resource usage while delivering real-world impact. Show less
My work focuses on understanding how systems behave in real-world environments, particularly in terms of performance, scalability, and resource consumption. I am interested in using data-driven approaches and machine learning techniques to analyze system behavior, identify inefficiencies, and support the development of more efficient and sustainable systems.
I have worked on projects related to software energy consumption, urban mobility analytics, and NLP-based systems. These experiences allowed me to explore how data can be used not only to describe systems, but to improve how they operate and scale.
In addition to research-oriented work, I have practical experience with enterprise data systems, including data quality improvement, reporting, and process optimization. This has shaped my approach to problem-solving, combining analytical thinking with an understanding of real-world constraints.
I am particularly interested in building systems that are efficient by design — systems that balance performance, scalability, and resource usage while delivering real-world impact. Show less
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