Changing a business process isn’t just a matter of picking new software or tweaking workflows—it’s a decision that ripples across people, data, and systems. That’s why I take a methodical approach: analyzing existing tools, studying how others have solved similar problems, and mapping the right path forward. Over time, I’ve developed a repeatable process that helps me avoid reinventing the wheel and deliver solutions that fit the business as it really operates—not just how it looks on a whiteboard. Here’s how I approach a new custom software need, from initial spark to execution planning.
1. Look for Prior Work
The first step in any new project is humility: chances are, someone has tried something similar before. I dig into open-source repositories, published case studies, academic research, and commercial tools—anything that gives me a sense of how the problem has been tackled before. My goal isn’t to copy, but to learn.
2. Review and Curate
From what I find, I narrow the field to one or two high-quality implementations. These are typically well-maintained, have good documentation, or simply show signs of thoughtful architecture. I compare them side-by-side, paying attention to both what they do well and where they fall short.
3. Read the Source, Reverse the Method
This is where things get technical. I dive into the code to reverse-engineer the core methodology. I ask key questions like:
- How does it process data?
- What assumptions does it make?
- Where does it start?
- What outputs does it drive toward?
Reading the source isn’t just about understanding function—it’s about uncovering intent.
4. Identify the Right Starting Point
With a good understanding of the underlying logic, I can determine where my solution should begin. Sometimes that’s the same as the reference point; other times, my use case demands a shift. Either way, this step anchors the project in solid reasoning, not guesswork.
5. Analyze the Data
Even the best design won’t work if the data doesn’t line up. I perform a data analysis pass—mapping the real-world inputs I expect to collect to the outputs the system needs to produce. This step confirms feasibility and ensures my assumptions are grounded in actual data behavior.
Why This Matters
Many software projects stumble because they start with enthusiasm and vision but lack a clear bridge from idea to implementation. By rooting each step in review, comparison, and validation, I avoid wasting time on dead ends and build from a position of clarity. Whether the end result is an internal tool, a client-facing platform, or a new product entirely, this process keeps me focused on what matters: solving the right problem in the right way.
If you’re considering a change in process or exploring how your workflows could evolve, contact us to talk through where you are today and where you want to go.