Lessons today from our financial modeling workshop.
Building models is not enough, we also have to calibrate them to ensure that they behave well under a range of assumptions.
Relationships between model drivers are often set in a superficial manner. Which leads to challenges.
Give your self time to test and calibrate models.
Plug in extreme values to see if the model holds.
Identify expected behavior for a multiple data points and see if your model reproduces that when fed the right data.
User expectations also need to be calibrated.
Educate users on model behavior so they know that it can be broken, that it doesn't always give the right answers.
Walk them through anticipated results so you can also calibrate their expectations.
Modeling free cash is a 6 step process
1. Add back adjustments 2. Estimate operating cash 3. Add investing and financing cash flows 4. Calculate change in cash for year 5. Plug change in cash back in balance sheet. 6. Cross check expected cash against model change in cash.
When modeling working capital for cash flow statements watch out for those sign changes.
Building a dynamic model requires effort. Limit the dynamism to a select few variables.
Stress test the dynamic variables against two or three key metrics that track what you want to measure, the questions you want to answer through your model.
A financial model is only as good as the questions you design it to answer.
Make sure you pick the right ones.
Add cross checks for cash, retained earnings, equity and net assets.
Make sure you are calculating them and not using them as balancing items to balance your balance sheet.
Next available workshop slots 14th-19th June 2021.
Data Tables are really powerful tool that give you birds eye view of summarized scenarios in a few minutes.
To use them correctly you must be clear about what metrics to focus on, identify the most sensitive variables that impact model output and realistic ranges for both.
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Here is what we are doing on 2nd Jun in Financial Modeling for Founders Workshop.
Day 1. Session 1.
Maya's Closet. Case Study.
Analyzing Growth in the middle of a pandemic Validating assumptions
Modeling growth
Dry run of Maya expansion model
Modeling downside.
Day 2. Session 2.
Maya continued.
Adding complexity and sophistication
Revenue drivers for an e-commerce business
Stress testing and scenario analysis
Using the distribution for stress scenarios
Founder models meet banking models.
Day 3. Session 3.
GEMS School Systems. A private equity case study.
The questions you want to answer?
Modeling GEMS's outlook
Sophisticated drivers, sophisticated models.
Modeling Debt Schedules. Fixed Asset Schedules.
Thou Shall not do? Rules to live by.
What does it take to run the mile in less than 9 minutes?
Not a lot if you are a fit 30 year old runner or fitness professional. Malcolm Gladwell the 57 year old author of Outliers ran it in 5:15 earlier this week beating out a much younger field.
One would think it's easy?
That depends on what your comparative peer group is? 50 year old Pakistani men?
60 year Boston Qualifier who have run the Boston Marathon every year for the last few years?
The models we build depend on the stories we want to tell and the questions we want to answer.
The most important of building the model is figuring out the question we are trying to answer.
Do that first before you start with Excel.
Our ability to generate scenarios for stress testing and sensitivity analysis is limited by acceptable and common ranges.
Understanding the distribution of drivers we are modeling can lead to richer and far more appropriate scenarios.
While most model builders are comfortable with putting together a balance sheet and income statement, quite a few struggle with statement of cash flows. If they can or could, they would skip it.
You can't balance your balance sheet or pass model cross checks without one.