How to review Excel Models for errors?

Hey everyone,

I did two banking internships and then moved to big tech. I cover revenue reporting, but it's 99% SQL & Python. I have a new manager that did 5 years at a top IB, and has no clue about SQL/Python but is very strong in Excel. As a result, all of the current infrastructure needs to have an Excel version to check outputs. Senior leadership loves this (as they also don't know tech skills beyond Excel), so politically I can't push back against this. These Excel models are relatively swanky, and cover things like sales target setting.

My problem is that I am not that great at reviewing work in Excel. I've created or updated models now twice where she would find a few formulae that don't tie or go down all the way. This is obviously no bueno. Does anyone have a structure or approach to review new models, or updated models for errors? I need to get up to speed very rapidly.

11 Comments
 
Most Helpful

I have to review a bunch of god-forsaken, unwieldly 50-tab models from client companies relatively often. A few tips:

  1. Start at the output: If the final output is an income statement, I’ll start there and trace back until I reach hardcodes. That tells me the basic logic of the model. From there you can look across the rows and columns to figure out any discrepancies in formulas.
  2. Pay attention to the little green corners on some cells: These denote inconsistencies in formulas, so always audit these to see if there are issues.
  3. Ctrl+F for “.xls”: This helps you find external links that might be broken or incorrectly linking to another excel file because someone haphazardly copy and pasted a sheet from another excel file.
  4. Do manual re-calculations to check common line items: If a line for “revenue” appears across multiple tabs, make check rows comparing this across tabs and investigate discrepancies.
  5. Read any in-cell comments (the red corners of cells): May have helpful notes from prior users.
  6. Compare outputs in powerpoint: If it is a model frequently updated, output the old version on a powerpoint. Then, output the new version on another slide. Quickly flip back and forth to see changes and investigate.
hardstuck in IB
 

Very good methods mentioned above.

I would just add to #6 that another method is to have the old values copy and pasted as values in cells nearby and set up to calculate the delta between the new and old as well, assuming you have some white space in the tab, so you can visually see what the old, new, and the delta between the two are.

Get Jiggy With It
 

As a banker (hopefully getting out soon) who is proficient in SQL and somewhat proficient in Python, I think the following applies:

If you are creating financial models, then Excel is more powerful because Excel is made to build financial models, including revenue build-up.

If you are dealing with data, any kind of data, Python + SQL is simply better than Excel. Most IB people are reluctant to learn new skills. 

 

+1, and a lot of the regular updates where data is pulled from somewhere else should at least use BigQuery import/SQL something to get the data in a decent format, and then the QUERY function to structure stuff. There is so much to automate.

If you're passionate about this, give me a DM!

 

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