Modeling Rigor across Firms

All - 

I'm currently a second-year associate at a middle market shop (~$15-25B AUM). While I'm on track for promo, I find myself on the fence about whether this firm is the right one for me long-term (due to industry focus and geo) and considering re-recruiting. One thing that's been on my mind as it relates to a transition to another fund is modeling intensity.

Where I currently am, we take a lighter touch approach to modeling. Obviously we invest a significant amount of time in building out an operating model and backing up assumptions, however we rarely model out the balance sheet and often take a lighter approach to NWC as well. Wondering how common / uncommon this is across other firms? 

While I don't have any doubt I could sail through a modeling test, I'm not sure how much this would be a drawback upon starting up at another firm at the Senior Associate / VP level given my lack of reps 

Appreciate any perspectives on my situation and how to think about it

 

Alt+A+W+T

How are your fund's returns? That'll give you a good indication of how effective your fund's "modeling" is.

I'm sure others have their own perspectives, but I quite candidly think most models are BS and end up giving you the same answer as a simple 30 min-1hr LBO anyways. With that in mind, I don't think modeling intensity is correlated with returns

To answer your question though, the returns over the past 3 vintages have been top quartile and fund size has grown quite significantly over the past few years in line with the broader industry. Don't plan on saying much more to preserve anonymity 

Lastly, I'm not asking for a perspective on whether my current fund knows what they're doing or not. I'm hoping to understand what a transition for myself might look like based on this experience 

 

Which is my point. Seems pretty effective if not at least conservative.

You can develop modeling rigor all you want with public resources, but at the end of the day, it’s a means to an end.

My view is some of the best investments my fund has made were pretty obvious from the outset and could’ve been modeled on a single sheet of excel. The bells and whistles are just a means to conveying how good a deal / biz it is, but not to be confused as everything.

Don't break yourself on the way to making yourself
 
Most Helpful

At a MF ($20bn+ fund) and similar to your experience we spend a lot of time building out the operating model but when it comes to the actual LBO (debt paydown, B/S) we make sure that it makes sense but don't put too much effort into it. 

For every hour I spend on the operating model I probably spend around 10 minutes on the other stuff such as the balance sheet, debt paydown assumptions, etc.

Honestly, anything above that is probably false precision and will lead to +/- 1% IRR based on the half dozens of deals I've ran hard at 

 

At a large cap firm (PE AUM >$50bn) and like one of the posters above, I spend the majority of time on the operating model and the below-the-line items are modeled with much less (false) precision. The amount of modeling rigor will be impacted by the core industry verticals the firm specializes in, but overall I think you’ll be fine. The VP role is still fairly in-the-weeds but hopefully wherever you end up, you get good associates that will do good work as a start.

 

We (>$40b AUM) go arbitrarily deep on the operating model/P&L/cash-flow (including monthly cash-flow modelling for turnaround cases) but never do this BS crap as it doesn’t really drive returns

 

Anecdotally - 

Have worked on a $500M+ EV buyout. Got IC approval plus a good amount of co-invest, all off of an annual model without full 3 statements. Just dug into top-line drivers as well as % of revenue / % of growth for key line items. Then just all the things that drive FCF. Capex, WC, taxes, interest, etc. and covenants.

Have also worked on smaller buyouts. Full 3 statements with monthly builds, except top-line less precise given level of info. Good to drive down to seasonality in cash flows. Even if it's as simple as X% annual growth but then seasonally adjusted (e.g. $100M going to $105M but 15% of that $105M in January, 7% in February, etc.). Alternatively, X% growth year-on-year every month. Gets you to the same answer. Don't think full 3 statements was completely necessary.  

Looking back, a mix of both approaches probably works best. Monthly, but no 3 statements. Just FCF to build debt schedule and returns. Focus on the true drivers. If it's a manufacturing business - Price x Volume with capex driving additional capacity. If it's a service business - drill down to unit level economics (blue-collar crews drive $X revenue and costs $Y for labor, materials, etc. or hiring an additional salesperson drives $Z revenue). 

In my opinion, a model needs at most 2-3 tabs. One for the P&L drivers and however granular you want, and then the model tab with the other items described above. Maybe another one for something else. In complex models, the level of false precision and granularity is frustrating if you have to audit it. If you truly understand the business and its drivers, it's easy to capture 80% of what you want with 20% of the effort. *Note this does not apply to very modeling heavy industries like energy and power. 

 

Interesting, thanks. 

We only build annual models so I'm actually curious what you think the monthly build gets you? No doubt that understanding seasonality can be critical during diligence, but we typically handle that as a part of diligence cuts rather than incorporating into the model (since at the end of the day, like you said, you'll likely grow annual revenue by a certain clip and then spread that across the months in a predetermined manner)

Agree on a model only needing a couple sheets (P&L or operating model depending on what your firm calls it + the actual transaction model with entry / exit / debt / returns).. Anything else is just ancillary (SOFR curves, output worksheets, etc.) 

Just to compound on your statement, we similarly look at pretty sizable deals (a couple recently in the $2-4B TEV range) with the benefit of coinvest and never build out a balance sheet   

 

It's really just to understand when/if cash flow might be tight. Kind of a "good to know" thing to watch out for after the deal closes. If your Q1/Q2 cash flows are tight, but that is also when you need to pay your excess cash flow sweep (which would be based on the previous year), that wouldn't be captured in an annual model. In that model, any cash shortfalls would theoretically get picked up by a revolver and MAYBE gets paid down throughout the year such that in your model periods, there is zero revolver draw. But reality would have some tightness within the year.  

 

3 statement model is so unnecessary in PE complete waste of time…just the basics like FCF/debt schedule/returns calculation etc is needed tbh

 

Since when is a $15-25B fund considered "middle market"? And to answer your question, plenty if not most funds take a similar approach to modeling.

 

That’s a summation of the last few funds. Current fund we’re investing out of is $5-8B.

I mainly said middle market because my fund never comes up when people typically list the mega funds / upper middle markets on this forum.

I’ve also honestly lost track of how to define these different categories with dry powder increasing so dramatically in recent years

 

Operating model has more granular detail of the income statement. Like revenue as sale price x volume and COGS as material cost x volume, etc. all the way down to EBITDA or net income. Three statement is the income statement, balance sheet, and cash flow statement. Those three are fairly standardized and most people can build those out quickly and across industries. The operating model is more specific to company/industry.

 

I haven't done a full balance sheet nor spent any time on NWC. What I *have* burned is an unbelievable amount of time on projecting out line by line customers and contract waterfalls and a ridiculous amount of nuance to get to the same damn answer as my prelim model (which we were trying to solve for $xx of EBITDA anyways). So basically I wasted weeks of my life just to have a completely made up model to act as some sort of evidence we had done our diligence and that our numbers were defensible (hint: they weren't). Just so partner could close a deal since he hadn't for a while. End rant.

Super anecdotal and a little off topic. But that sums up what modeling looks like at my firm. Obviously punch line is I believe intensity of modeling can have absolutely zero correlation with being successful (as a firm or as an individual).

 

Based off my previous experience, modelling "intensity" really depends on the industry of the targetco itself.

Some industry/sector really don't need that much modelling as the outcome is pretty much known (such as natural resources) or the exact opposite (highly sensitive to pricing/subject to 1 critical factor). Back then we only model out complete 3S model + LBO + valuation etc etc when we were part of a consortium or there are some contingent scenarios that would need to be researched beforehand.

Any seasoned Principal would've had a 80-90% accuracy on how the investment would go (in terms of returns), usually the last 10-20% are just scenarios when some uncontrollable factors were to happen. So i think regardless on how good your modelling is, having reps regarding industry knowledge is IMO far more important than "modelling it out".

My former MD used to say "If you have to create a (detailed) model out for every investment opportunity, then you will lose the opportunity."   

 

Can only speak for infra. I have worked in a few funds of varying size (currently UMM/MF). Obviously the industry lends itself to granular modelling, but it's not always painful. Here is my anecdotal experience:

MM: granular models, associate/VPs grinding on it incessantly themselves, running thousands of useless scenarios, basically completely and utterly miserable

UMM/MF: associate/VPs "own" the model, but bigger funds = bigger tickets = bigger DD budgets, so now we push most of the granular model build outs to banks. MUCH better (and the models are better lol)

 

Slightly off topic, but I am curious as to the modelling approach you / your firm  generally takes.

Do you model out a CIM case (upside), Base case and a Downside case? 

The most interesting being the Base case (and arguable the downside case). Curious to know which steps you take to set up the operating Base case model (might be just a discounted / less bullish version of the CIM case). 

 

Varies for me by deal. 

Sometimes we build in management case, sometimes we don't 

Over the past few years, there was always a downside case due to concerns about recession / consumer pullback, or just to pressure test a concern related to the Company (e.g., prices revert to pre-COVID levels) 

Every once in a while, we'll show upside cases but really don't spend too much time on them. Our IC typically doesn't really care about this as they anchor on our base case assumptions 

For the operating model, sometimes we'll recreate what the bankers sent over (don't just input our assumptions into their build for fear of any mistakes / busts). Other times, we'll create a much simpler version to focus on the few key drivers that'll actually matter and end up in our sensitivities 

 

Doloribus libero totam aut id fuga voluptatibus. Quas esse dicta laborum aspernatur porro.

 

Neque omnis veniam dicta voluptate sit. Laboriosam ut dolor corporis eum et. Nesciunt impedit incidunt ut dolorem minima.

Et laborum iusto voluptatem. Fuga quae aspernatur impedit dolorem. Rerum quisquam voluptas atque. Sequi occaecati illum necessitatibus mollitia dicta sint impedit.

Consequuntur nihil molestiae voluptas distinctio et distinctio id. Perspiciatis qui unde inventore voluptates temporibus.

Consequuntur id ut rerum enim dicta. Rem impedit ducimus voluptatem tempore maiores mollitia.

Career Advancement Opportunities

March 2024 Private Equity

  • The Riverside Company 99.5%
  • Warburg Pincus 99.0%
  • Blackstone Group 98.4%
  • KKR (Kohlberg Kravis Roberts) 97.9%
  • Bain Capital 97.4%

Overall Employee Satisfaction

March 2024 Private Equity

  • The Riverside Company 99.5%
  • Blackstone Group 98.9%
  • KKR (Kohlberg Kravis Roberts) 98.4%
  • Ardian 97.9%
  • Bain Capital 97.4%

Professional Growth Opportunities

March 2024 Private Equity

  • The Riverside Company 99.5%
  • Bain Capital 99.0%
  • Blackstone Group 98.4%
  • Warburg Pincus 97.9%
  • Starwood Capital Group 97.4%

Total Avg Compensation

March 2024 Private Equity

  • Principal (9) $653
  • Director/MD (21) $586
  • Vice President (90) $363
  • 3rd+ Year Associate (88) $280
  • 2nd Year Associate (204) $268
  • 1st Year Associate (384) $228
  • 3rd+ Year Analyst (28) $157
  • 2nd Year Analyst (83) $134
  • 1st Year Analyst (245) $122
  • Intern/Summer Associate (32) $82
  • Intern/Summer Analyst (312) $59
notes
16 IB Interviews Notes

“... there’s no excuse to not take advantage of the resources out there available to you. Best value for your $ are the...”

Leaderboard

success
From 10 rejections to 1 dream investment banking internship

“... I believe it was the single biggest reason why I ended up with an offer...”