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Leasing Budget Automation

Why I built leasing forecast pipeline - reducing turnaround time from 3 weeks to 10 minutes

Posted by Kevin Cho on July 13, 2025

Python

🏗️ Why I Built It: From Chaos to Clarity

Leasing budget season meant 3 weeks of manual entry by 7 accountants — every year — just to get rent assumptions into Yardi’s ABF system. The process was labor-intensive, error-prone, and disconnected from upstream leasing inputs.

I knew we could do better.

What started as an experiment to automate rent projection with Python became a full-stack solution integrating SQL (Athena), Excel (via xlwings), and leasing team inputs. The result? A 10-minute turnaround — from input to reforecast report — replacing 200+ hours of work.

See detail for the project: 

https://databykevin.com/projects/budget-reforecast/leasing


⚙️ What I Built: Rent Reforecast Automation Engine

I designed a fully automated workflow that:

  • Pulls 7-year in-place rent data from Yardi via SQL Athena

  • Consolidates leasing assumptions from the leasing team

  • Read these two sources of information to Python VSC for reprocessing the data

  • Detects overlaps, handles rent steps, and calculates GLA/monthly rent

  • Outputs validated projections and dashboards in Excel

The entire system updates with a click — no copy-pasting, no version mismatches, no ambiguity.


📈 The Impact: Beyond Just Time Savings

  • ✅ Replaced manual Excel/Yardi entry with a single Python script

  • ✅ Created a “source of truth” for rent assumptions

  • ✅ Reduced turnaround time from 3 weeks to 10 minutes

  • ✅ Earned trust and buy-in from both leasing and accounting teams


🚧 The Caveat: Competing with Forecast Manager

Yardi has released a Forecast Manager module — a powerful, integrated budgeting engine. If adopted, it could replace much of what I built.

But here's the truth: this project wasn't just about the tool. It was about leveling up my skills — learning Python, SQL, and real-world ETL — while solving a real problem at scale.


🧠 What I Learned

  • Domain expertise matters: understanding leasing mechanics made the automation relevant

  • SQL + Python + Excel = unmatched agility in finance workflows

  • Impact isn’t about code — it’s about adoption, trust, and timing


🏁 Looking Ahead

Whether or not Forecast Manager becomes the standard, this project proves that finance professionals can be builders. My focus now is scaling up and streamling the process — tackling larger, smarter projects that blend automation with insight, bridging strategy and technology.

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