???????? Hi friends!

Been a busy return to the UK since I got back from my break in the Maldives – from catching up with the team, getting ready for my first live show with Peter Walker (Head of Insights at Carta), to recording three back to back podcasts last week ⚡️ 

Here’s a sneak peek behind the scenes of what, I can assure you, is not the bridge of the Startship Enterprise ???? 

In this weeks Off Balance, I’ll be chatting about:

???? The grey world of fundraising brokerage
???? Financial modelling Part III

Check out this weeks Primer where I sit down with my old friend, Shruti Ajitsaria, Head of Fuse, Allen & Overy’s legal tech incubator where she tells me a bit about how she got to building Fuse, what it does and who it’s for ????????‍????

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Now let’s get into it.

How can did I add value?

I had a chat with someone that had a couple of companies they were involved with that were looking to raise some external capital but didn’t feel like they had the experience or the network to make that happen.

They were essentially looking for a broker that would make a bunch of introductions with a contingent fee in either equity or cash post fundraise.

I have some quite strong feelings on this subject and won’t do ‘introductory / broker’ work which I explained in a fair amount of detail.

Here’s what you need to know:

Brokerage is a ‘grey area’
The FCA in the UK has rules around ‘promotion’, that is, the promotion for sale of financial products (of which equity is one) especially to retail investors. Now the case is often argued that most people investing in early stage businesses are sophisticated investors and should be aware of the risks of investing, but the reality is, if a deal goes south, the ‘broker’ could leave themselves open to issues down the track.

Skin in the Game
I run a team of CFOs that work with venture backed businesses. There is a level of trust that is placed in us as individuals as well as collectively. When we recommend a course of action, implicitly we are putting our name to that action. But in the introductory / brokerage game, you are typically not involved in the business in any kind of deep capacity (financially it would not make sense – see below). What this means is that you are creating reputational risk should things not work out and, as most of you will know, it takes decades to build a reputation and only seconds to demolish it.

Contingency is for suckers
One man’s opinion, but let’s say I get over these issues and spend time understanding the business, refining the model or deck, reaching out to investors, providing updates, following up and all the rest of activities entailed in raising investment. At that point, I’ve put in substantial time and effort into a business which is only going to pay me if I secure them investment. And, whilst the numbers may seem sexy, let’s break it down:

Standard fees in this space are 5%. So let’s say a business is raising $1m, that means you have the potential to earn $50k right? Well kinda.

Firstly, you only earn the $50k if you raise the whole $1m.

Secondly, it can take 6 months+ between starting a fundraise and cash hitting the bank.

Thirdly, only the founder can raise the money (I can make an intro, but it’s the founder that has to sell the opportunity) so I have no control over outcomes.

Fourthly, it’s unlikely that as a broker you raise the full amount, much more likely that you raise a portion of it – and here’s the kicker – it requires just as much time and effort to raise $200k as it does to raise $1m (often more)

Finally, there are enough stories in the market to suggest that it is not uncommon for these agreements to not be honoured.

Founders are the front line
When asked to assist in these situations my first question is why can’t the founder do it themselves? I mean, it’s kinda their job isn’t it?

And the reality is that investors get so much direct deal flow, when they see a broker in the arrangement (especially if they are VC investors) they are likely going to red flag it.

Because the reality is that great founders (and great businesses) get funded – so what does that leave.

Now don’t get me wrong, there may be some legitimate reasons the founder thinks they can’t raise (no access to networks of capital, don’t know how to approach term sheet negotiations) but these are solveable (i.e. just read this newsletter, use LinkedIn or other tools and start building a network).

More likely, it’s that the opportunity is just not interesting enough for people to sit up and want to invest. (As a side note, I get very frustrated when I see people trying to ‘engineer’ FOMO when raising a round – you can’t engineer it, it happens because your product / business / fundraise has momentum).

So, at this stage, I’ve no doubt you’re saying ‘this doesn’t sound particularly helpful Aarish, you’ve just told this person all the reasons why you won’t do it’, and you’d be right.

But I didn’t stop there.

I offered to speak to the founders, review what they’ve done and give them a bit of guidance (pro bono of course) on how they might want to move their fundraise forward.

After all, that’s why I set up my office hours, precisely to help founders like these struggling to figure out a way forward.

So no, I won’t be a broker. But I will try to be helpful. Always 🙂

Off Balance

So in Financial Modelling Parts I and II I gave you an overview into financial modelling it’s value and use to CFOs followed by the core components of a model, from inputs through to calculations and outputs.

Today I’m going to wrap up the topic with some of the best practices as well as common pitfalls I see with financial modelling as well as what’s happening in the software space right now and where I think that’s heading.

Building a Robust Financial Model: Best Practices

Start Simple

The biggest problem I see when people build a financial model is that they overcomplicate them right from the start.

The first thing to do when building one out is to focus on where the business is today, and to understand all the various elements of the business. I would normally do that on a discovery call with the founders and other key internal stakeholders in the business to figure out exactly what the business is, does and how it does it, namely:

Products
What is the product suite of the business? Are you selling one, two or three products? How are they priced? Are these going to change in any way in the period under consideration for the model you’re building?

Business Model
How does the business make money? Is it a SaaS business or a market place? Is it a mobile application or a services led business? Is it mass market or D2C? What, in short, is the business model?

Demand Generation
How does the business find customers? You will have a very different model if the company runs a B2B enterprise SaaS model than if they are a D2C eCommerce brand. Does the business rely on outbound sales activities or is it more reliant on digital acquisition marketing?

Lifetime Value
How long do those customers continue to buy? Is it a one off purchase followed by some repeat rate, or is it an ongoing service with some churn? Will there be the potential for up sell or cross sell of products / services and how does that profile tend to look?

Margin and Contribution
What are the costs associated with servicing that revenue? If it’s a D2C product business this will likely be the cost of purchasing the physical product whilst for a SaaS business this may include elements of hosting costs or client onboarding activities as well as ongoing customer success activities. There may well be delivery costs (of which customer success is one) or actual physical delivery of getting a product from warehouse to customer.

Staffing
Staff costs are important to understand in depth.

One of the biggest failures I see in models is under-assuming the level of staff required to deliver on the business’ objectives. For software businesses, it’s understanding how increases in engineering costs may impact efficiencies in either sales or efficiencies (and hence gross margins). For a physical goods business it may well be the operational staff required to receive, monitor and then deliver the product.

Of course there are other staff that are going to be necessary to deliver on the company’s objectives as well, whether they be finance teams, marketing teams or sales support teams.

Making sure that you neither under-assume who will be required nor over-assume the impact that they will have on growth is essential so understanding when to layer in growth in the team is essential.

One thing worth thinking through is what the additional payroll costs are, but also the costs of hiring new team members, as well as the cash flows that come from paying out wages followed by costs to state and central tax coffers.

Operating Costs
Other opex costs beyond staffing costs are critical; there are other big ticket items it’s always worth looking out for, things like rent which may need to increase as headcount increases (you will rarely pay the same amount on rent for a 10 person team as you do for a 30 person team), marketing costs (outside of direct acquisition) such as brand, content and online presence are often one of the largest ‘discretionary’ areas where cash is spent so it is critical to look at where that money is being spent.

For example, you may found that there are substantial travel costs in the business either as part of business development efforts, operational requirements or even attending conferences and other significant events.

Legal Costs
There are often more legal costs to the business than one would anticipate so understanding both operational as well as extraordinary legal costs is important. For example, there may well be costs associated with fundraising that can be quite substantial, so understanding when these are likely to flow can have a large impact on the overall cash profile of the business.

Debt
If the business has debt, then modelling in repayments of principal as well as interest costs is incredibly important.

Most early stage businesses won’t have these considerations, however as a business scales, the likelihood of having some debt in the capital profile grows and will have substantial impact on the cash flows of the business so it’s worth understanding what plans there are to raise external debt.

Even in smaller businesses today you will find some working capital facilities in place which will impact how the the business is funded as well as the cash profile.

And speaking of working capital, it’s also useful to understand the sort of terms a company works on with both debtors (customers owing money) and creditors (service or product providers to the business to whom you owe money). If you are paying creditors within 30 days but only collecting debts within 45 days, you will have a working capital gap that needs to be modelled in.

The point here is that before you even open your spreadsheet, you will need to know and understand the business in a great deal of detail to be able to model it well. So whilst I’m advocating to start simple, the detail you will need to get into is quite complex.

Use Consistent Assumptions

Once you have gathered information, you need to start thinking through how to build these into assumptions that will then drive the rest of the model.

I always try to break things down into constituent parts and build out the model in a consistent way. This means not changing the way revenue is booked half way through the model (or if you need to, creating a separate revenue calculation for it).

If your model contains inconsistencies, it will be harder for users to ‘audit’ the model and the potential to allow errors to creep in increases with the more complexity you try to build in.

It’s worth using the same periods for each driver in your assumptions so that you’re always changing everything on a monthly or a quarterly basis rather than trying to build revenue on a monthly basis whilst you’re modelling out opex on an annual basis.

The other point here is that however you build your assumptions out should be consistent with how you report your numbers already (assuming you have numbers to report).

For example, you want to be able to look at why your actual performance varies from what you have modelled and if you have not been consistent throughout, you will run into issues in analysis.

Sensitivity Analysis

Wherever possible, you want to build in multiple scenarios into the model so that assumptions can be viewed in a best case / worst case manner. Not only this, but you may want to include things like breakeven analysis (at what level of revenue you are able to cover your costs). Though, admittedly, this is less critical in an early stage business.

The point is always that financial modelling is not an exact science and neither is building a business.

The likelihood that you don’t hit numbers can be quite substantial and so you want to understand what happens when you fall short (or for that matter when you exceed them) as this will impact the range of investment you might look for or indeed how quickly you might hire additional team members.

Regular Updates

At early stages financial models should be dynamic, updated regularly to reflect new data and changing circumstances. They should be reviewed and ‘rolled’ on a regular (at least quarterly) basis to take into account what has changed in the business since the last time the model was reviewed.

This is particularly important in early stage businesses where the things can move quite fast.

In an enterprise SaaS business, just having one client delay by a few months could leave a substantial 6 figure gap in your cash flow which you will need to figure out how to plug. In a D2C business, if you assume a repeat rate of 50% but this actually turns out to be 30%, you could similarly see a substantial hole in your numbers.

The point is that if you are using your model the way it should be, it can provide a really useful map to help you navigate your business as it grows. The more information you capture up front whilst leaving room for adjustment in the future, the more value you will get from it.

Common Pitfalls and How to Avoid Them

Over-Complexity

Whilst a business will likely be complex, it is not wise to transfer that complexity into your model. By this I mean that you cannot replicate the business fully and neither should you try. People often think that it is the complexity of the model that signals its usefulness, instead it is the quality of the output and the ease of adjustability.

While detail is crucial, an overly complex model can be hard to understand and maintain and, in my experience just leads to multiple rounds of rebuilds over time. KISS is your friend (Keep it Smart and Simple).

Static Modelling

A model is not a one off output that should be built, circulated and then left in someone’s inbox.

It should be updated and maintained on a regular basis as I have already argued. Not updating the model regularly can lead to outdated and irrelevant insights.

Tangentially, it is important to avoid hard coding figures into the model. The value is in the ability to test the assumptions, so each element of the Income Statement, Cash Flow and the Balance Sheet should all be traceable back to the assumptions you have made as opposed to being a number that someone has ‘decided’ to enter and hard code for a reason that may have made sense to them, but is unlikely to make sense for anyone else.

Over-Optimism

We’ve all seen the hockey stick models showing revenues climbing from $1m to $100m over a couple of years.

Reality is rarely that good, and all these sorts of models tend to show is naivety in the person building it or signing it off.

Does this mean you shouldn’t be ambitious?

Of course not, especially if the model’s primary purpose is to raise investment you need to show an achievable path to scale. However the point here is to avoid overly optimistic projections that lack a testable and provable grounding in reality.

The Role of Technology in Financial Modelling

Modern Software Solutions

For many finance pros, Excel, and latterly, Google Sheets have been the main tools used in modelling. However with the growth in platforms offering modelling capabilities, I think we’ll see a portion of financial modelling moving over to some of these products.

However, as I have already explained, every business is unique and uniquely complex.

The problem with many of these platforms is that they have been built to abstract away complexity which means that you are unable to achieve the sort of flexibility you can achieve in a spreadsheet.

Conversely, spreadsheets are limited by the users ability to build out formulaic relationships between different dimensions in their assumptions. Productised modelling tools are far more able to cope with these types of complexity.

What I typically see is that for businesses over a certain size with strong FP&A (financial planning and analysis) teams and requirements, these tools are starting to be used more frequently.

One of the reasons they tend to be used in these sorts of businesses is also because they carry a relatively significant cost that most earlier stage businesses cannot support.

Check out my conversation with Julio Martinez, Co-Founder and CEO of Abacum where we explore this in more detail.

 Automation and AI

The explosion of generative AI has led to a lot of companies scrambling to build predictive modelling tools, these tend to be quite expensive and niche however as the cost of building continues to fall, it’s likely we’ll see some really interesting things in this space.

With that said, currently I would say that it is tools that allow you to extract, clean and use data from various systems (accounting platforms, ERPs, CRMs, payment providers, open banking and more) that are providing a lot of value to people focussed on financial modelling – at least in those businesses that have the data to feed into their assumptions.

And that’s it (for now) on financial modelling.

Remember, modelling is not a static. As businesses evolve, so do the tools and methodologies that CFOs like me and my team employ.

Staying updated, embracing technology, and continuous learning are the keys to leveraging financial modelling to its fullest potential.

And if you’re feeling a little like this????️? Just give me a shout ???? 

I hope you found Off Balance #18 useful. As always, I’d love to get your feedback and understand the sort of topics you would love to hear about.

Just hit reply to this mail or drop me a line at hello@emergeone.co.uk and let me know ????

????And that’s a wrap for this edition of Off Balance – I’d appreciate your feedback so just reply to this email if you’ve got something you’d like to say.

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That’s it from me so until next time…

Stay liquid 🙂

Aarish