Learn how to prototype an internet startup using the generic business model prototype
This is the fifth post of a series of posts in which I discuss how to use the business model prototyping approach to build a generic business model prototype. In this post we are bringing the generic business model prototype online for the first time and applying it to an internet startup.
The last post prepared the ground and discussed the ideas behind the prototype. Today we are bringing the first, rudimentary version of the the generic business model prototype online – the prototype it is a self contained business simulation built using System Dynamics and the the Stella® modeling environment.
You can access the model online – even though this post contains a lot of screenshots to explain our experiments, it will be more fun if you access the prototype and perform the experiments yourself.
Before I get into the details, let me recall the main objectives of the generic business model prototype:
- The prototype should be as SIMPLE as possible, yet still COMPLETE. We want to create the simplest possible prototype of a „generic“ business – the prototype should be easy to understand and not make any assumptions about a specific business, yet still cover all aspects of a company’s value creation logic.
- The prototype should cover both BUSINESS MODELS and PROTOTYPING. The prototype should help us learn more about business models and also how to prototype different aspects of a business model, using the System Dynamics modelling and simulation approach.
- The prototype should be used as a BUSINESS EXPERIMENTATION LABORATORY. The prototype should allow as to experiment with different business scenarios. The idea here is to use the business prototype as a framework that can quickly be adapted to specific situations – experience shows that it is rarely necessary to model every aspect of a business in detail to answer a given question. So you can use the framework as a basis and elaborate those aspects of the model that are relevant to the problem at hand and thus rapidly create a business simulation.
The generic business prototype is simple, but this does not mean it isn’t powerful – on the contrary: next to covering all aspects of value creation (as discussed in my post on the generic business model blueprint), the prototype also contains all the stocks and flows needed to provide a company’s balance sheet and cash flow statement. So we will be able to assess financial health of the company we are simulating in real time during the simulation.
Needless to say, even though the generic business model prototype is simple, it is still far to extensive to discuss all of its aspects in one blog post. Therefore my plan is to introduce the prototype over a series of posts.
To make the discussion more exciting I will apply the prototype to a simple business case, that of an internet startup. In today’s post I will first introduce the internet startup and then experiment with some basic scenarios.
In my next post in this series I will then investigate the overall model structure; each further post in the series will then cover one particular aspect of this structure in detail and introduce further scenarios.
An Experimentation Laboratory for Internet Startups
To make our experiments meaningful and allow us to calibrate the simulation model, we need to have a specific situation in mind: so let’s imagine we are the founders of an internet startup that is providing an online service to registered customers. We have a small development team and the service we are providing is already online. We even have some initial customers. Today we want to experiment with some simple questions:
- How much money should we be spending on marketing?
- How much capital should the company have initially?
- Will we need debt financing?
- Our company is an internet startup started by two founders who act as managing directors.
- Next to the founders there is a small development team consisting of one product designers, product developer and a product tester. We also two customer service agents who deals with support requests.
- Our development team is capable of delivering twenty-five new features per year. For now, we are happy with this target output, so we don’t expect the development team to grow.
- The number of customer service agents we need depends on the number of customers – the assumption is that every client posts one service request per month and that it takes ca. 10min to deal with a service request. So if we win new customers, the number of service requests will rise and thus the customer service team must grow. When the team grows, we will also need to add team management capacity. Our assumption here is that we need one team leader per thirty customer service agents.
- The number of product designers grows with the number of customers – the assumption is that 1% of all service requests are actually ideas for new features. It takes a product designer 10min to qualify a feature idea. When the team grows, we will also need to add team management capacity. Our assumption here is that we need one team leader per fifteen product designers.
- Our revenue comes from a monthly subscription fee of €20 that each customer pays. We assume the average collection time is two months, i.e. it takes two months until the revenue is collected and the cash arrives in our bank account.
- Our main costs are the wages for the team (€ 3000 each per month) and the two founders (EUR 6000 each per month) and also for the infrastructure equipment we need to deliver the service. We also assume that we will spend EUR 20,000 per month on marketing.
- We assume we will reach 100 customers per euro spent and that 0.01 percent of those will buy our product. So we need to spend around EUR 100 per customer. To keep the discussion simple initially we assume that we don’t loose customers once we have won them.
- Next to our initial shareholder’s stock of EUR 700,000 we assume that we have access to debt financing to keep the operation going. New debts will be added as needed according to our cash coverage policy, to ensure that we have enough cash to cover our payments. Initially the cash coverage policy is set to three months. Debt is repaid monthly over a period of five years at an interest rate of 5% per annum.
- Our simulation will cover a timespan of five years, all calculations will be performed on a monthly basis, the monetary unit in the model is k€ (€1,000). One month is assumed to have 20 workdays.
Let’s examine this graph more closely to make sure we understand this behaviour:
- For the first three months, the cash flow drop fairly strongly. This is because the company incurs expenses (such as marketing expenses) in the first month of operation but does not actually meet its obligations (i.e. pay its bills) until the second month.
- After two months, the cash flow starts improving – this is because we are gaining customers and revenue, without changing our monthly cost.
- After about nine months, our stock of cash is depleted and our cash coverage policy (which is set to two months) kicks in: we start taking up debts in month 10, peaking in month 11, and don’t stop taking on new debt until month 21 – you can see this best if you look at the debt cash flow in the financial statements (see screenshot below)
- Our cash coverage policy then ensures that the cash flow is almost constant, because it ensures the gap in operating cash flow is filled with new debts.
- At last, at month 19 our operating cash flow becomes positive and at month 21 we have accumulated enough cash to stop taking on new debts – the cash flow starts to increase.
- At month 44 our cash flow suddenly drops – this is because our company has to pay tax for the first time.
You may like to take some time to play with the cash coverage policy – if you increase the policy to, say, 6 months, then the basic shape of the cash flow curve remains the same. But we need to take on debt much sooner and it takes longer before cash flow starts rising again. Try and see what happens when you reduce the cash coverage policy to just one month!
Another important influence on our cash flow and our debt financing is the average time it takes to collect revenue: our assumption is that 2 months on average. If you increase this time to 6 months, then the amount of debt you need to finance your company more than doubles!
Note: Despite calibrating the model to a specific situation we need to ensure that we don’t compromise the generality of the model. We will do this by ensuring that we model each aspect in the most generic way – this shouldn’t be too difficult because we are modelling a startup with a simple structure and a single product. Once we have covered all aspects of the prototype we can then calibrate the model to a different kind of business to test whether it is really generic. If yes, all is well. If not, this will be an opportunity to learn something new and improve the model.
We have checked our model and verified that the results match our assumptions using some simple “back of the napkin” calculations. Now it’s time to start experimenting with our internet startup.
Some Concrete Experiments
How much money should we spend on marketing?
The first are we should investigate is marketing after all, this is what is going to bring in the customers. Assuming we want to reach profitability within 5 years, how much money do we really need to spend on marketing?
The KPI to look at hear is the monthly profit before tax. The model contains a graph especially for this – a little experimentation with the target marketing spends setting quickly shows that you need to spend at least € 5,000 per month to reach profitability. The diagram below shows three test runs, with settings for €1,000, €5,000 and €10,000 respectively.
But is it enough to just reach profitability?
A quick look at the earnings retained over the years shows that this clearly is not enough – we don’t just want to be profitable, we want to reach break even – within five years at least, better within three years.
A little further experimentation shows that we need to spend at least €11,000 per month to reach break even within 5 years.
Can we grow even faster?
Before we answer this, let’s take a look at how we financed our marketing: we started with an initial equity of EUR 500,000 (equal to the initial shareholder’s stock). This dips down to EUR 7,000, before rising again to reach EUR 1.15 Mio. after five years.
But if you take a look at the graph showing how we have accumulated debt over the years we see that the amount of debt we have is quite high, peaking around €440,000.
Are our debts too high?
Well, the right KPI to check here is the debt equity ratio. The graph below shows that if we spend EUR 15,000 per month on marketing, then our debt/equity ratio will reach a peak of around 63 at month 26. This means that our startup company will have 63 times as much debt as it has equity. This clearly is not realistic and there is no way a startup will find debt financing for such large amounts. A good rule of thumb is that the debt/equity ratio should not be larger than 2.
Okay – but how can we achieve this?
Well, we could increase the initial shareholder stock by about €140,000 – our debt equity ratio then stays below two throughout the simulation.
Interestingly, there is also the option of spending more money on marketing – if we spend EUR 30,000 on marketing per month our debt/equity ratio goes down to 2 and we reach break even within three years!
This may seem counterintuitive at first – but it is simply due to the fact that spending more money on marketing builds the customer base and thus the revenue stream faster, leading to better results.
Our little experiment with the initial shareholder stock immediately raises the question: how much initial capital do we really need?
How much initial capital do we need?
Our initial assumption was that we had initial shareholder stock of €500,000. Clearly more would be nice – e.g. a quick experiment shows that with an initial stock of €590,000 we could keep our debt equity ratio below 1, which would be really healthy.
But could we do with less? If we check to see how the equity develops, we see that even at its lowest we still have €180,000. Technically, our company will only go bust if equity dips below 0. So we should be able to reduce the initial stock to, say €330,000. A quick run of the model shows that this is ok, at least from the equity perspective.
But unfortunately, our debt/equity ratio then jumps to more than 160, which is simply not feasible.
So it seems that €500,000 is quite a good figure for the capital our startup needs to raise initially.
Do we need debt financing?
Our discussion above shows we will need total debt financing of around €360,000 if we start with an initial stock of €500,000 and initial debts of €150,000. A little experimentation with the model shows that if we increase our initial stock to €700,000 we can avoid increasing our debt altogether. The initial debt was used to buy the infrastructure needed for service delivery – we could also finance this from the inital stock and do away with debt altogether if we increased our stock to €850,000.
Summary and Outlook
Today we took some time to introduce a small internet startup, to make some basic assumptions about its business model and to perform some experiments using the generic business model prototype.
Even though the model is still quite simple, we have learnt quite a lot from it already. Now we are ready to take a look at the prototype in more detail and flesh out the business case.
In my next posts in this series I will give an overview of the generic business model prototypes internal structure and add some new experiments regarding the internet startup case study.
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