👇50% off all Financial Modeling Courses this week only.

Theory is great until someone sends you 17 blurry PDFs and says "hey what's our business worth?"

This is the wake-up call that happens in the real world.

Businesses still need cash to operate, and they need profit if they eventually want to sell, but 9 times out of 10 the underlying data is a mess, and the "finance team" isn't sophisticated enough to build a forecast.

That's where YOU come in, right?  Just jump in and "stand up the model."

It's easy enough to understand on paper, but when you open that blank spreadsheet, suddenly, you can just freeze up.

Having spent over 15 years in Private Equity & FP&A, I know exactly how that feels.

When it's just you, some incomplete data, and AI isn't helping at all, how do you move forward?

That's where I can help -- I teach you to build (and own) the financial models that run real companies -- completely from scratch.

(𝘣𝘦𝘤𝘢𝘶𝘴𝘦 𝘵𝘩𝘢𝘵'𝘴 𝘵𝘩𝘦 𝘰𝘯𝘭𝘺 𝘸𝘢𝘺 𝘵𝘰 𝘳𝘦𝘢𝘭𝘭𝘺 𝘭𝘦𝘢𝘳𝘯, especially in an unstructured environment).

This is financial modeling in the real world.

🌐 𝗟𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲 𝗵𝗲𝗿𝗲 👉 https://www.financialmodelingeducation.com/ 


———

𝗥𝗲𝗰𝗼𝗴𝗻𝗶𝘁𝗶𝗼𝗻 𝗶𝗻 𝘁𝗵𝗲 𝗺𝗮𝗿𝗸𝗲𝘁:

🏆 Trusted by over 91,000 students with 4.9/5.0 Star average rating

🏆 Over 100,000 followers on LinkedIn & other social media platforms

🏆 Recognized by Business Insider and Financial Modeling World Cup

🏆 Featured by Wharton Online, Wall Street Prep, & LinkedIn Learning


———

𝗥𝗲𝘃𝗶𝗲𝘄𝘀 𝗳𝗿𝗼𝗺 𝗽𝗿𝗼𝗴𝗿𝗮𝗺 𝗮𝗹𝘂𝗺𝘀:

"𝘛𝘳𝘢𝘪𝘯𝘪𝘯𝘨 𝘪𝘴 𝘧𝘢𝘯𝘵𝘢𝘴𝘵𝘪𝘤..."
⭐⭐⭐⭐⭐

"𝘉𝘦𝘴𝘵 𝘮𝘰𝘯𝘦𝘺 𝘦𝘷𝘦𝘳 𝘴𝘱𝘦𝘯𝘵..."
⭐⭐⭐⭐⭐

"𝘈𝘣𝘴𝘰𝘭𝘶𝘵𝘦 𝘨𝘢𝘮𝘦 𝘤𝘩𝘢𝘯𝘨𝘦𝘳..."
⭐⭐⭐⭐⭐

"𝘉𝘦𝘴𝘵 𝘤𝘰𝘶𝘳𝘴𝘦 𝘐'𝘷𝘦 𝘵𝘢𝘬𝘦𝘯 𝘰𝘯𝘭𝘪𝘯𝘦..."
⭐⭐⭐⭐⭐

"𝘔𝘰𝘴𝘵 𝘤𝘰𝘮𝘱𝘳𝘦𝘩𝘦𝘯𝘴𝘪𝘷𝘦 𝘤𝘰𝘶𝘳𝘴𝘦 𝘐'𝘷𝘦 𝘵𝘢𝘬𝘦𝘯..."
⭐⭐⭐⭐⭐

"𝘐 𝘩𝘢𝘷𝘦 𝘵𝘢𝘬𝘦𝘯 𝘴𝘦𝘷𝘦𝘳𝘢𝘭 𝘮𝘰𝘥𝘦𝘭𝘪𝘯𝘨 𝘤𝘰𝘶𝘳𝘴𝘦𝘴, 𝘵𝘩𝘪𝘴 𝘰𝘯𝘦 𝘪𝘴 𝘵𝘩𝘦 𝘣𝘦𝘴𝘵..."
⭐⭐⭐⭐⭐

🌐 𝗟𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲 𝗵𝗲𝗿𝗲 👉 https://www.financialmodelingeducation.com/

Chris Reilly

How I like to model scenarios without over-complicating the model.

(with template for you) 👇


~~~
📥 𝗧𝗟;𝗗𝗥: Grab the template 👉 https://lnkd.in/ez48VdTi 
~~~


𝗛𝗼𝘄 𝘁𝗼 𝘂𝘀𝗲 𝘁𝗵𝗲 𝘁𝗲𝗺𝗽𝗹𝗮𝘁𝗲:

𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼 𝘀𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻:

We're using the classic Base, Upside, and Downside scenarios here.

The scenarios can be selected in Column B using a drop-down list.

This allows you to build scenarios on a line-by-line basis.


⸻⸻⸻


𝗖𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝘀𝗰𝗲𝗻𝗮𝗿𝗶𝗼 𝗶𝗻𝗽𝘂𝘁𝘀:

You can enter the assumptions for each case on the right side of the sheet.

(The are different sections for Base, Upside, and Downside).

The 𝗽𝘂𝗿𝗽𝗹𝗲 𝗳𝗼𝗿𝗺𝘂𝗹𝗮𝘀 saves this all from becoming a dumpster fire.

This formula checks the drop-down list in Column B.

Then, it pulls the corresponding assumption from one of the three cases.

~~~
💡𝗞𝗲𝘆 𝗣𝗼𝗶𝗻𝘁: Whatever is in purple is the "𝗟𝗜𝗩𝗘 𝗦𝗖𝗘𝗡𝗔𝗥𝗜𝗢."
~~~

Many modelers like to use the =CHOOSE function here.

But for this template, I used a simple IF statement.


⸻⸻⸻


𝗠𝗼𝘀𝘁 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗽𝗮𝗿𝘁: 𝗻𝗼𝘁 𝗺𝗲𝘀𝘀𝗶𝗻𝗴 𝘂𝗽 𝘆𝗼𝘂𝗿 𝗺𝗼𝗱𝗲𝗹

The live scenario "flows down" into the three statement model.

(On a different sheet that isn't included with the template.)

The outputs then 𝘭𝘪𝘯𝘬 𝘣𝘢𝘤𝘬 to my scenario one-pager.

This lets me quickly view the 𝘢𝘯𝘯𝘶𝘢𝘭 impact of my 𝘮𝘰𝘯𝘵𝘩𝘭𝘺 model.

𝗧𝗵𝗶𝘀 𝗺𝗮𝗸𝗲𝘀 𝘁𝗵𝗲 𝗲𝗻𝘁𝗶𝗿𝗲 𝘁𝗵𝗶𝗻𝗴 𝗲𝗮𝘀𝘆 𝘁𝗼 𝗺𝗮𝗻𝗮𝗴𝗲 𝗳𝗿𝗼𝗺 𝗼𝗻𝗲 𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻.

*𝗡𝗼𝘁𝗲 𝟭: Depreciation isn't affected here. I usually model Capex Spend separately, with its own scenarios, and let it flow to this page.

*𝗡𝗼𝘁𝗲 𝟮: I will often allow Debt and Interest Expense to adjust naturally with the other changes to the P&L.


⸻⸻⸻


𝗭𝗼𝗼𝗺𝗶𝗻𝗴 𝗼𝘂𝘁

Of course, scenarios become complex and need details that can't be captured here.

For example, changes in headcount or existing contracts probably can't be modeled at this level without creating a giant mess.

What we're looking at here are big picture changes to kick off a conversation.

(This is the "50,000 foot view" your boss mentioned earlier today).

After we choose a course with this "macro view," we can 𝘵𝘩𝘦𝘯 dive into the details and create something more specific.


⸻⸻⸻

Friendly reminder that...

𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗔𝗜 𝘄𝗼𝗻'𝘁 𝗵𝗲𝗹𝗽 𝘂𝗻𝗹𝗲𝘀𝘀 𝘆𝗼𝘂 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘁𝗵𝗲 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀. 

🎓 Differentiate yourself here 👉 https://bit.ly/FMECourses

Private equity & FP&A veteran that teaches you to build the financial models that run real companies | 🎓 91,000+ students

So Claude has blown me away again.

Here's what it did this time 👇


I received a very thoughtful question from a student in my LBO course, asking for clarification between the total cash flow sweep formula, and the portion that was being swept to the revolver.

At first glance, they didn't understand why the figures were different.


⸻⸻⸻


I thought to myself, 𝘩𝘦𝘺 𝘺𝘢 𝘬𝘯𝘰𝘸 𝘸𝘩𝘢𝘵? 𝘓𝘦𝘵'𝘴 𝘨𝘪𝘷𝘦 𝘊𝘭𝘢𝘶𝘥𝘦 𝘢 𝘤𝘳𝘢𝘤𝘬 𝘢𝘵 𝘵𝘩𝘪𝘴...

I opened the model, clicked on Claude, copied the question, and asked it to audit the model and respond.

𝗜𝘁 𝗴𝗮𝘃𝗲 𝗺𝗲 𝗮 𝘁𝗵𝗼𝗿𝗼𝘂𝗴𝗵 𝗮𝗻𝗱 𝗰𝗼𝗿𝗿𝗲𝗰𝘁 𝗮𝗻𝘀𝘄𝗲𝗿 ✅.

(and this is a big a$$ LBO model)

Once again I'm like... 𝘋𝘈𝘔𝘕 — 𝘵𝘩𝘪𝘴 𝘵𝘩𝘪𝘯𝘨 𝘪𝘴 𝘨𝘰𝘰𝘥.

I reviewed it for accuracy, made some adjustments, and was able to respond.


⸻⸻⸻


Total time spent was probably the same.

But the 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 of answer was probably 𝗯𝗲𝘁𝘁𝗲𝗿 than what I would have come up with on my own.

The walkthrough was succint and provided ample detail to drive the point home.


⸻⸻⸻


This whole thing is starting to feel palatable to me:

As a subject-matter expert, I'm able to use AI to:

   - provide a better experience for my students
   - validate my own learning
   - double-check my work

I'm excited to see what will pop next.


⸻⸻⸻


Still just have to say it.

Modeling with Claude is awesome because I know what I'm doing.

That comes from years of building models the hard way.

Fundamentals first, AI second.

I can teach you the building blocks here 👉 https://bit.ly/FMECourses

Even if you're "good," sometimes it's hard to remember all the pieces of a model.

You can use this checklist as a guideline (↓📥)


~~~
📥 𝗧𝗟;𝗗𝗥: grab the checklist 👉 https://lnkd.in/eVTU67fY 
~~~


🔎 𝗕𝗜𝗚 𝗣𝗜𝗖𝗧𝗨𝗥𝗘

Anytime I build a model I like to map out two things:

1. The data request list (what I'll need from the client), and;
2. The model structure

This checklist is my starting point for both, broken down as follows:


⸻⸻⸻


📂 𝗥𝗔𝗪 𝗗𝗔𝗧𝗔

Typically direct exports from an accounting system.

Call me old school, but I still prefer to copy/paste CSVs into the model so that everything is self-contained.

(or, I'll use PowerQuery to pull CSVs in automatically)


⸻⸻⸻


🧮 𝗦𝗨𝗣𝗣𝗢𝗥𝗧 𝗖𝗔𝗟𝗖𝗨𝗟𝗔𝗧𝗜𝗢𝗡𝗦

Detailed schedules to forecast the "biggest movers" of the business:

   - Revenue
   - Headcount
   - Material OpEx items, etc.


⸻⸻⸻


📊 𝗖𝗢𝗡𝗦𝗢𝗟𝗜𝗗𝗔𝗧𝗜𝗢𝗡

Raw Data and Support Calculations "roll up" here into the Three Statement Model consolidation.


⸻⸻⸻


📄 𝗢𝗨𝗧𝗣𝗨𝗧𝗦

As the name implies → print-friendly outputs that are linked from other places in the model, typically the Consolidation.

You 𝗱𝗼𝗻'𝘁 model here or have them link anywhere else.

They are outputs, should be automated, and left alone.

𝗧𝗵𝗶𝘀 𝗶𝘀 𝗮 𝗴𝗿𝗲𝗮𝘁 𝗽𝗹𝗮𝗰𝗲 𝘁𝗼 𝘂𝘀𝗲 𝗔𝗜.


⸻⸻⸻


⚙️ 𝗔𝗦𝗦𝗨𝗠𝗣𝗧𝗜𝗢𝗡𝗦

A place to enter most of the forecast assumptions.

Some people live and die by the "Assumption Page," but I usually go against best practices here and put my assumptions inside the Support Schedules and Consolidations themselves.

I do this because I like to see the numbers change as I change the assumption.

However, I will do my best to link everything back to an Assumptions page so it's printable and sitting in one place.


⸻⸻⸻


🚨 𝗘𝗥𝗥𝗢𝗥 𝗖𝗛𝗘𝗖𝗞𝗜𝗡𝗚

Despite our best efforts, nearly 90% of spreadsheets contain errors (Google it).

This is the place in the model where I do my best to capture anything that might go wrong so I'm notified immediately.

In my opinion, this is the most important sheet in the entire file, should be reviewed constantly, and is always the last thing you check before you close (and send) the file.

𝗔𝗻𝗼𝘁𝗵𝗲𝗿 𝗔𝗜 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲: ask it to check for errors.  It 𝘸𝘰𝘯'𝘵 be perfect.  The final work product is still on you, but using AI is a good start.


⸻⸻⸻


🔽 𝗜𝗡 𝗦𝗨𝗠𝗠𝗔𝗥𝗬

   ↓ Raw Data
   ↓ Support Calculations
   ↓ Consolidation
   ↓ Outputs
   ↓ Assumptions
   ↓ Error Checking


⸻⸻⸻


𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗔𝗜 𝘄𝗼𝗻'𝘁 𝗵𝗲𝗹𝗽 𝘂𝗻𝗹𝗲𝘀𝘀 𝘆𝗼𝘂 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘁𝗵𝗲 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀.

🎓 Master the judgement AI can't replace 👉 https://bit.ly/FMECourses

How to make this 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝗰𝗮𝗽𝗶𝘁𝗮𝗹 𝗰𝗵𝗮𝗿𝘁 (helpful to know 𝘩𝘰𝘸 before you ask AI to do it, in case you need to fix something) 👇


🎓 𝗡𝗲𝘁 𝗪𝗼𝗿𝗸𝗶𝗻𝗴 𝗖𝗮𝗽𝗶𝘁𝗮𝗹 𝟭𝟬𝟭

NWC = Current Assets - Current Liabilities

Purpose is to see if a company has enough current assets to cover its short-term liabilities, which suggests good financial health.

~~~
📥 𝗕𝘁𝘄: This balance sheet guide can help 👉 https://lnkd.in/ew4nwaVx 
~~~


⸻⸻⸻


👀 𝗦𝗵𝗼𝘄 𝗠𝗲

It's helpful to see it visually for a couple reasons:

   ‣ 1. To identify any trends.

   ‣ 2. To identify any outliers.

   ‣ 3. To see how much "cushion" there is.

That's the purpose of the graph below.

   ‣ Current Assets stack above zero.

   ‣ Current Liabilities stack below zero.

And the 𝗱𝗼𝘁𝘁𝗲𝗱 𝗹𝗶𝗻𝗲 𝗿𝗲𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝘀 𝘁𝗵𝗲 𝗡𝗲𝘁 𝗪𝗼𝗿𝗸𝗶𝗻𝗴 𝗖𝗮𝗽𝗶𝘁𝗮𝗹.

In this example I've included a data table below the graph, as it's helpful to see the numbers in a table alongside an image.


⸻⸻⸻


⚙️ 𝗛𝗼𝘄 𝗧𝗼 𝗠𝗮𝗸𝗲 𝗜𝘁

(yes, still helpful even in the age of AI in case you want to modify things)

As modelers, this is a great chart to add to your monthly reporting pack.

Steps:

   ‣ 1. Start a new section called "Charts"

   ‣ 2. Include the dates along the top

   ‣ 3. Make your Current Assets positive

   ‣ 4. Make your Current Liabilities negative

   ‣ 5. Sum the Net Working Capital at the bottom

   ‣ 6. Create a Stacked Bar Chart

   ‣ 7. Change the chart type for the Net Working Capital figure only to Line Chart

        (leave the rest at Stacked Bar Chart)

   ‣ 8. You can customize and adjust from there


⸻⸻⸻


💬 𝗪𝗵𝗮𝘁 𝗜𝘁 𝗧𝗲𝗹𝗹𝘀 𝗠𝗲

In this example, we have a company that comfortably covers its Current Liabilities with its balance of Current Assets, and doesn't have much seasonality.

𝗕𝗼𝗻𝘂𝘀: can easily be forwarded to your team in a layout they can understand.


⸻⸻⸻


⚠️ 𝗪𝗮𝘁𝗰𝗵 𝗢𝘂𝘁 𝗙𝗼𝗿

Sometimes calculations take on a life of their own, and you can accidentally create misleading representations of your working capital balances.

Those one-offs would stand out immediately on a graph like this.

You can investigate (and fix) from there.

Lastly, assets might be tied up in AR or longer-term projects (which aren't immediately liquid), and this can skew the perceived health of the NWC as well.

So often times it's helpful to include a second layer of detail (like an aging schedule) to get a more complete picture.


⸻⸻⸻


💡 𝗛𝗼𝘄 𝗜 𝗰𝗮𝗻 𝗵𝗲𝗹𝗽:

Working capital is "core stuff" in three statement modeling.

If you're not quite sure how to build it correctly, I can walk you through it.

↳ https://bit.ly/FMECourses

When perfect accuracy isn't always helpful...

How I model Revolvers differently 👇


🏫 𝗥𝗲𝘃𝗼𝗹𝘃𝗲𝗿 𝟭𝟬𝟭

A "Revolver" is just a fancy term for "giant credit card."

If the business doesn't have enough cash, I "draw" on the Revolver.

(↑ this just means I borrow from it, like your credit card)

If the business has too much cash, I will (usually) pay down the Revolver.

(↑ often called a "sweep", the same as paying down your credit card)

~~~
✨ 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲: Model-building Checklist 👉 https://lnkd.in/eVTU67fY 
~~~


⸻⸻⸻


📦 𝗘𝘅𝗰𝗲𝗲𝗱𝗶𝗻𝗴 𝗖𝗮𝗽𝗮𝗰𝗶𝘁𝘆

Just like you have a credit limit, the Revolver has a "capacity,"

meaning you can't borrow more than [$X].

In the picture below it happens to be $10mm (you can see it in the middle).

Now, if I wanted to be perfectly accurate, then...

If I exceed Revolver Capacity, then 𝘵𝘦𝘤𝘩𝘯𝘪𝘤𝘢𝘭𝘭𝘺 the cash in the business should go negative.

But -- this is where we can draw a line in the sand and remember:

𝗧𝗵𝗲 𝗺𝗼𝗱𝗲𝗹 𝗶𝘀 𝗮𝗻 𝗮𝗯𝘀𝘁𝗿𝗮𝗰𝘁 𝗿𝗲𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝘁𝗼 𝗵𝗲𝗹𝗽 𝘂𝘀 𝗺𝗮𝗸𝗲 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀.

(↑ and NOT the business itself)


⸻⸻⸻


✔️ 𝗧𝗵𝗲 "𝗕𝗿𝗼𝗸𝗲𝗻" 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻

Now contrarily,

If I just "let the model run" and allow the Revolver to "draw" (borrow) whatever it needs to,

it helps me communicate something to my team:

✓ I can say, "based on our expected operations this year, I think we will exceed capacity on our Revolver and need to:

   (1) Work on a reforecast
   (2) Ask for a larger Revolver, or
   (3) Both

✓ In addition, 𝘐 𝘬𝘯𝘰𝘸 𝘦𝘹𝘢𝘤𝘵𝘭𝘺 𝘩𝘰𝘸 𝘮𝘶𝘤𝘩 𝘸𝘦'𝘭𝘭 𝘯𝘦𝘦𝘥 because my model tells me.

(↑ I'll round up just a little for room)


⸻⸻⸻


🗨️ 𝗔 𝗖𝗹𝗲𝗮𝗻𝗲𝗿 𝗖𝗵𝗮𝘁

It's a much cleaner conversation than:

Me: "Looks like cash is going negative."

Boss: "Why?"

Me: "I'll check the model. Okay looks like Revolver exceeds capacity."

Boss: "How much are we over?"

Me: "The Revolver capacity plus the negative cash amount."

Boss: "So what do we need?"

Etc., etc., etc...

See what I'm saying?

Making the model perfectly accurate actually slows me down in this instance and creates confusion.

Whereas, if I build checks/indicators around major business issues, it allows the model to provide insight and help us make decisions as a team.


⸻⸻⸻


✅ 𝗧𝗿𝘂𝗲 𝗣𝘂𝗿𝗽𝗼𝘀𝗲

✓ That's the point of the model: just accurate enough that I have some runway to make a decision on what to do next.

I get no prize or bonus points for it being pretty or perfect.

But, I guarantee you we've created value if the model starts a strategic conversation with our lender and we come to terms on a larger Revolver.


⸻⸻⸻

𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗔𝗜 𝗵𝗮𝘀 𝗯𝗲𝗲𝗻 𝗿𝗲𝗮𝗹𝗹𝘆 𝗰𝗼𝗼𝗹.

It helps me b/c I spent 15+ years building from scratch.

So I know what's good and what's not.

I can teach you the fundamentals here 👉 https://bit.ly/FMECourses

I thought AI would make this obsolete but I was wrong.

The most common Excel shortcuts I use when modeling 👇


~~~
📥 𝗧𝗟;𝗗𝗥: Download here 👉 https://lnkd.in/e7DJFDxt 
~~~  


𝗦𝘁𝗶𝗹𝗹 𝗴𝗼𝘁 𝗶𝘁!

This is pretty much it: the 80/20 of all shortcuts I use in Excel.

These have been tried & true for years.

𝗣𝗿𝗼 𝘁𝗶𝗽: add your most used ones to the quick access tool bar.

Example, I use Paste/Special most often.

So, instead of typing "alt + e + s", I added it to my Quick Access Toolbar and just type "alt + 1" instead.

(sounds pointless, but actually lot of time saved).


⸻⸻⸻


𝗪𝗵𝘆 𝗔𝗜 𝗵𝗮𝘀𝗻'𝘁 𝗿𝗲𝗽𝗹𝗮𝗰𝗲𝗱 𝘁𝗵𝗶𝘀 (𝙮𝙚𝙩):

Shortcut keys are fast AF.

So when you know exactly what you need, it's 𝘮𝘶𝘤𝘩 𝘧𝘢𝘴𝘵𝘦𝘳 building the model using memorized shortcuts than it is to:

   - think of the prompt
   - write the prompt
   - wait for the AI
   - audit & understand the output
   - make edits

𝗠𝘆 𝗹𝗶𝘁𝗺𝘂𝘀 𝘁𝗲𝘀𝘁: if it's under 10 minutes and I mostly know what I need -- go old school with shortcut keys.

If it's longer than 10 minutes or previously would have resulted in some kind of Google search to an Excel forum from 2004, bring in AI.

Feel free to print this out and tape it to your desk -- there's no shame in it.

Hope this helps 🙂.


⸻⸻⸻

Needs to be said:

𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗔𝗜 𝘄𝗼𝗻'𝘁 𝗵𝗲𝗹𝗽 𝘂𝗻𝗹𝗲𝘀𝘀 𝘆𝗼𝘂 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘁𝗵𝗲 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀. 

🎓 Master the judgement AI can't replace 👉 https://bit.ly/FMECourses

Back to basics... a 𝗽𝗿𝗶𝘃𝗮𝘁𝗲 𝗲𝗾𝘂𝗶𝘁𝘆 𝘄𝗮𝘁𝗲𝗿𝗳𝗮𝗹𝗹 even kids can understand...

(probably) 👇



(➕) 𝗘𝗡𝗧𝗘𝗥𝗣𝗥𝗜𝗦𝗘 𝗩𝗔𝗟𝗨𝗘

When a company is sold, the 𝗣𝘂𝗿𝗰𝗵𝗮𝘀𝗲 𝗣𝗿𝗶𝗰𝗲 is called the "Enterprise Value."

It's usually calculated as a multiple of EBITDA, for example:

$1mm of EBITDA x 8.0x = $8mm Enterprise Value

This Enterprise Value (plus any cash on the Balance Sheet) is the "Total Proceeds" from the image.

~~~
📚 𝗜𝗳 𝗻𝗲𝗲𝗱𝗲𝗱; 𝗣𝗘 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗴𝘂𝗶𝗱𝗲: https://lnkd.in/ewh-x6_k 
~~~


⸻⸻⸻


(➖) 𝗗𝗘𝗕𝗧

Then, things are paid off in order of priority:

1. First, the Total Proceeds "flow" down the waterfall to first tier, 𝘁𝗵𝗲 𝗗𝗲𝗯𝘁.

The Debt needs to be paid off in full before the waterfall can "flow" to the next tier.

So in this image, the "Debt bucket" is completely full before it overflows and continues down the rocks.


⸻⸻⸻


(➖) 𝗣𝗥𝗘𝗙𝗘𝗥𝗥𝗘𝗗 𝗘𝗤𝗨𝗜𝗧𝗬

2. Then, the Remaining Proceeds "flow" down to the next tier, 𝘁𝗵𝗲 𝗣𝗿𝗲𝗳𝗲𝗿𝗿𝗲𝗱 𝗘𝗾𝘂𝗶𝘁𝘆.

(this is, of course, if the cap table has Preferred Equity, but it's common to see in PE deals)

Just like the "Debt bucket," the "Preferred bucket" needs to be fully repaid as well before the water can flow further.

Normally, the Preferred Equity includes:

   (a) its Return of Capital, plus;
   (b) a "Preferred Dividend" (i.e., 8% of the capital invested)

This dividend is also called the "hurdle rate."

(topic for another day: Participating and non-Participating Preferred)

Once the "Preferred bucket" is completely full, the water overflows and continues down the rocks.


⸻⸻⸻


🟰 𝗖𝗢𝗠𝗠𝗢𝗡 𝗘𝗤𝗨𝗜𝗧𝗬

3. Finally, to the extent there are proceeds leftover, the rest goes to 𝘁𝗵𝗲 𝗖𝗼𝗺𝗺𝗼𝗻 𝗘𝗾𝘂𝗶𝘁𝘆 holders according to their "pro rata" share.

(in other words, how much of the Common Equity they own)

This can be the biggest pool because there's no "bucket" to fill, but the risk is of course that the Common Equity comes last in the waterfall.

Generally speaking, the lower down in the waterfall you are, the higher potential return you can achieve, but it comes with the most risk because everyone else needs to get their money back first.

Also generally speaking, another non-economic benefit of Common Equity is that it typically comes with voting rights about the strategic direction of the company, whereas the Debt and Preferred Equity typically only have economic rights.

Last note, to keep the image simple, I've skipped the "𝗰𝗮𝘁𝗰𝗵-𝘂𝗽 𝗽𝗿𝗼𝘃𝗶𝘀𝗶𝗼𝗻" that often comes right after the Preferred Hurdle is cleared (again, topic for another time).


⸻⸻⸻


Been using AI modeling a ton, it's awesome.

It helps me b/c I've been building by hand for 15+ years.

𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗔𝗜 𝘄𝗼𝗻'𝘁 𝗵𝗲𝗹𝗽 𝘂𝗻𝗹𝗲𝘀𝘀 𝘆𝗼𝘂 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘁𝗵𝗲 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀. 

🎓 Master the judgetment AI can't replace 👉 https://bit.ly/FMECourses

Hey I could really use your input -- if I was going to make a course about financial modeling with AI, what would be most important to you?

Note: this would be focused on people who are often in Excel building models and want an extra edge; it's NOT geared towards re-inventing the FP&A function -- that's beyond my expertise. 

Please leave a comment. All thoughts are good. I'm just in the brainstorming phase right now.

Which one is a Current Asset?

The questions get harder 👉 https://lnkd.in/eccYpT-R

The author can see how you vote. Learn more

Climate Friendly

•	Built detailed financial models and delivered insightful analysis to ﬁnance, commercial, operations, and business development teams.
•	Supported business cases and research of new markets and commercial opportunities.
•	Delivered presentations and analysis of investment opportunities to senior level Executives.

Senior Commercial Analyst

Advanced Analysis Training

Director at Advanced Analysis Training Pty Ltd.

•	Started my own business providing online education and software tools for financial modelling
•	Negotiated and collaborated with software developers to market and sell products on my website
•	Jointly created an online training course in Excel error checking
•	Published around 270 LinkedIn social media posts over 12 months, gaining over 14,000 followers
•	Built and designed my own website using a range of online applications and tools

Small Business Owner

Various short term contract roles

Development Planner
Santos, Brisbane
Feb 2022 - Apr 2022

Key Tasks:
•	Supported the business in planning and reporting of gasfield development
•	Used modelling tools including Enersight and Excel


Finance Planning and Analytics
BHP, Brisbane
July 2021 – Sep 2021
Contract position working in the BMA Met Coal assets within BHP.

Key Tasks:
•	Supporting site operations in the business planning, budgeting, and reporting process.
•	Building models and using analytics to find optimisation and improvement opportunities.
•	Leveraging tools such as SAP Analytics Cloud, Spotfire, Power BI, R Studio, and Excel VBA.


Financial Modeller
Queensland Building and Construction Commission, Brisbane		
Dec 2020 – Apr 2021
Contract position in a fast-paced digital transformation project. Member of the Strategy and Transformation Project team.

Key Tasks:
•	Built a risk-based cost model to evaluate a portfolio of growth and efficiency initiatives supporting QBCC’s goal of becoming an Insights Driven Organisation. 
•	Dynamically modelled the 10-year business plan based on new process improvement initiatives.
•	Led and supported data gathering workshops for the Financial Sustainability workstream.
•	Supported the preparation of the Transformation Strategy & Roadmap for the purpose of building a Business Case for consideration by Queensland Treasury.

Senior Finance Analyst & Advisor

Career Break

Career Break to explore and develop opportunities:

- Developed horse racing data analysis and predictive models using Microsoft Excel and VBA.
- Automated extraction of complex data from websites.
- Used a range of analysis techniques including logistic regression, ratings, and probability.

Sports Analytics and Predictive Models

Arrow Energy Pty Ltd

Arrow Energy is a global joint venture between Shell and CNPC. 

Development Planner. Key role in the Development Planning team. Detailed cost analysis, insights and strategic advice on complex multi-billion dollar upstream gas field development scenarios. Coordinated costs and assumptions for annual business plan and 5-year plan.

Built and maintained an advanced upstream gas development cost model in Microsoft Excel which was used across many parts of the business, including for high value commercial negotiations between the Arrow Joint Venture parties, development scenarios and optimisation, asset impairment tests, annual business plan, and 5-year plan.

Senior Cost Analyst

Gas & Coal Tenure Advisor. Managed external relationships and led co-development negotiations with coal companies over strategic and high value gas tenements. Drafted commercial terms for co-development agreements. 

Built economic models to evaluate business opportunities for acquiring mine gas from underground coal mines in the Bowen Basin. Supported Arrow’s contribution to policy development on overlapping tenures legislation.

Strategic Commercial Advisor and Analyst

QGC - A BG Group Business

Lead Tenure Advisor. Critical role to ensure delivery of commercial agreements in a timely manner so that Petroleum Leases could be granted and allow the multi-billion dollar QCLNG project to progress.

Extensive contract negotiation to secure gas resource and surface access over coal tenure.  Part of a broader team that secured several agreements allowing Petroleum Leases to be granted. Engaged joint venture partners on details of co-development agreements and relevant legislation. Policy development and strategy on overlapping tenures legislation.

Lead Commercial Advisor

Origin Energy

Commercial contract management and negotiation within a multi-billion dollar coal seam gas project.
Supporting financial analysis and business cases.

Senior Commercial Advisor

Commercial:
Contract management and negotiation. Detailed financial modelling and business cases.
Commercial peer reviews with project stakeholders for major projects. Prepared key inputs for annual budget and strategic plan.  

Operations:
Project Engineering role for 12 weeks on a major refinery shutdown in 2008.  Reactive engineer role for 6 months coordinating daily maintenance, plant optimisation, daily production orders, and work permits.

Business Development Analyst

Shell

Various commercial roles in the downstream oil and fuels business, including Shell Aviation.
Commercial Manager: Regional fuel sales and distributors in North Queensland general aviation.
Commercial Advisor: Strategic planning and capex management, Oceania.

Commercial Advisor

Highly skilled in finding insights and carrying out financial modelling across investment opportunities, operational risks, scenarios, and optimisation.

I understand the corporate strategic planning cycle and the importance of building strong relationships across the business to ensure delivery of timely results.

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Chris Reilly

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