How to Create an Effective Financial Forecast With No Historical Data
Companies who’ve been established in a market for a long time have it easy (relatively) when it comes to conducting a financial forecast.
They often have years of recorded sales results to reference. With this deep history, they can project numbers reliably that stand a good chance of hitting the mark.
What if you’re only just launching your business idea, or in the early stages of growth? Or, perhaps you are an established business but are launching a brand new product line.
There is so much uncertainty in these situations and it makes creating a meaningful financial forecast really difficult.
Without an archive of data to reference and extrapolate, how do you actually make something useful that isn’t just guesswork?
When I talk to people about financial planning for startups, some people think you just can’t do anything about this!
‘But you can’t predict the numbers behind startups, anything could happen!’
Similar messages have come out of the popular ‘Lean startup’ movement. If you aren’t familiar, the lean methodology is an effective guide for finding your product/market fit really quickly.
Part of lean thinking is that all you have when you launch a new product or business is a set of untested assumptions.
Creating a financial forecast without having first proven your assumptions in the field is just a waste of time (or so they tell you).
That’s not always particularly helpful advice though.
The problem is, investors will still ask you for a long term financial plan. And, if you’re putting your own money in, you’ll want to know the risk and long term prognosis too.
If you don’t have confidence in these numbers, you may never even launch your startup.
You’ve got to create some kind of financial forecast to try and answer these questions. So, how do you do this without any (or with limited) historical data – with only untested assumptions?
In this article, I’ll demonstrate how to go about this process. You’ll see it’s not only possible but actually a crucial part of planning your startup.
Some parts of your business are easier to predict that others
First of all, there are always areas of your financials that are predictable. Fixed costs that you pay regularly can be planned out ahead very reliably.
Even if you plan on taking on more costs in the coming months and years, this is still under your control. You can choose when to take on more employees or move to a larger premises.
Sure, a lot of these might be dependant on hitting certain revenue milestones but you can plan scenarios around this.
It’s the sales themselves (and their associated direct costs) that you have less control over.
Marketing and sales costs may fluctuate as you change your tactics and search for the most effective methods. I’m going to focus on this side of your business, where the unpredictability is at its highest for a fresh startup.
- Recommended Reading: 6 ways financial forecasting isn’t what you think it is
- Recommended Reading: The Advantages of Financial Forecasting
Creating sales projections with no data
So, this is where it gets interesting. Is there truly no way of telling whether you will make 10 sales or 10,000 sales?
Of course not.
You’ll likely know whether the product your launching will be moving units in the 10s or in the 10s of thousands.
That’s because you do have some knowledge, some data. It might not be a 3 year record of historical sales but you’ve got a mixture of common sense and business experience. You’re an entrepreneur, your business instincts are one of your greatest strengths!
Combining these instincts with market research and the simple process I outline below will mean you can make very robust projections. The process looks like this:
- Identify the key metrics that drive your sales
- Research industry benchmarks
- Work out your confidence levels
- Plan realistic scenarios
1) Identify the key metrics that drive your sales
The first task is to look at which key metrics are responsible for driving your sales. If you’ve created a marketing and sales plan for your startup, you’ll find a lot of the information there.
These metrics, the things which drive your sales, are the key performance indicators (KPIs) for your specific business.
For an e-commerce website they might look like this:
- The cost of driving website traffic (adverts/SEO/digital marketing/print materials/etc)
- Number of website visitors (organic/paid/referrals/social medial/etc)
- % of these visitors who purchase
- Average order value per visitor
Whichever industry you are in, you’ll be able to find equivalents to these. Retail stores will be looking at footfall for their immediate area. Consultancy firms might look at the number of phone calls that can be made to generate leads.
Think about all the links in the chain, from awareness to actually making a purchase. What are the factors that move a person from the top of your marketing funnel to the bottom?
Articulating this in a simple formula is the first step in creating a useful forecast:
Revenue calculation: Website visitors x Conversion Rate x Avg. Order value
You can add complications to this basic starting point too. You could split this formula out into different marketing channels if you see them having different conversion rates:
Revenue line 1: Organic visitors x Conversion Rate x Avg. Order value
Revenue line 2: Facebook advert visitors x Conversion Rate x Avg. Order value
Revenue line 3: Google advert visitors x Conversion Rate x Avg. Order value
Your marketing costs and other variable costs (like the material costs) will be directly related to these results. You’ll often be able to see the exact sales impact coming from digital marketing activities allowing you to tie the costs and revenue together.
Splitting your income lines into different marketing channels is a useful additional level of detail. Eventually, you’ll roll these into complete financial reports of your business, like a Cash Flow Statement or a Profit & Loss statement.
If you are trying to persuade investors to back you, it really helps if you can clearly demonstrate sound thinking behind your numbers. Being able to point to a number and quickly and confidently explain its origins is a great way to impress.
Read our beginner’s guide to the key financial statements if you need to know more about their format and usage.
2) Research industry benchmarks
Ok, so you’ve got some basic metrics responsible for driving sales. What numbers do you start plugging into this formula?
Without historical data, you’ll be completely reliant on market research and the industry benchmarks for each of your metrics.
Benchmarking is about finding the average performance for a metric across all businesses in your particular category.
Finding this information might take some digging around:
- Free internet industry benchmark resources
- Purchased from an industry researcher
- Consulting with industry experts
- Contacting local business groups or organisations
- Advertising platforms (providers of advertising space will have historical performance results)
You’ll want to try and find the average performance as well as the top performance possible in your industry.
If you know what the best possible result is, it stops you making unrealistic predictions. You are very likely to be well below the best in the industry, at least to start with!
Some of these metrics will be harder to work out than others. Average order value will be very specific to your business with the variety of products or services you provide. You’ll have to put your best thoughts forward and be ready to adjust your financial forecast when your first figures start coming in. It’s better to start with some assumptions, than no assumptions.
The next piece of the puzzle is to understand how confident you are in achieving good performance.
3) Work out your confidence levels
Confidence levels can be used to judge how close to the industry benchmarks you think you’ll be. This task is somewhat subjective and it’ll put your business experience and intuition to the test.
One of the key metrics we looked at earlier is the percentage of visitors who make a purchase.
A major factor here is how good your e-commerce website is at driving conversions. How good is the layout, the navigation, the presentation of products, the calls to action etc?
If you are building this website yourself and you have never made one before then your confidence levels for conversion rates might need to be low.
If you are paying a quality web development team with 10 years of experience building high conversion websites for businesses in your industry then your confidence levels might be a lot higher!
What do these different confidence levels mean for your sales forecast?
In the low confidence scenario, you might accept that you’ll launch with conversion rates lower than the industry average benchmark you’ve researched.
You might then start to bake in a growth assumption that over the first 6 months of operations you’ll be actively learning and making changes to your website in order to close in on that industry average.
Perhaps you’ll hit the benchmark in 3 months, perhaps 6 months or perhaps 12 months. You can create best and worst-case scenarios around the speed at which you improve these conversion rates.
You’ll need to explore your confidence levels around all the important factors in your business.
Obviously one of the main drivers is how good your product or service is. Your levels of confidence here will be based on the feedback you’ve had:
- How positive was your feedback?
- How large was the sample size?
- Did people understand the product?
- Did you test your pricing as well?
Again, the results of your customer research here will influence your confidence levels and impact how close you’ll be to the industry performance benchmarks.
Are Facebook ads a key part of your marketing strategy? Are you doing it yourself for the first time or are you working with an experienced digital marketing agency? More factors. More information that can be used to judge what the right numbers are.
Putting these somewhat subjective confidence levels within the framework of objective industry benchmarks provides you with a structured way for gauging your future success.
Confidence levels are subjective though. We are dealing with an uncertain future and we are dealing with assumptions, not reality.
This means that your financial forecast is never expected to be accurate. This is why we also need the final element of this process. We need to model several scenarios to give you a range of potential results, not just one forecast which will definitely be wrong.
It’s this range of potential results (that are all actually realistic) that provides you with the picture you need to make informed decisions about the business.
Remember the people who say ‘you can’t predict the numbers behind startup because anything could happen!’.
Well, we’re finally arriving at the answer. The statement that ‘anything’ can happen is where the falsehood lies.
They are right that you can’t predict the one true result that will happen. What you can predict is a range of realistic results. You can predict that the future of your business lies somewhere within these upper and lower boundaries.
And, knowing this, you can ensure you are prepared for the consequences of whichever real result actually happens.
4) Plan realistic scenarios
You may have heard of creating base, best and worst case scenarios.
A base scenario is intended to be a realistic, middle of the road average. Not too optimistic, not too pessimistic.
From this base case, you move into making adjustments for different scenarios, different possible outcomes.
A worst case scenario can show the effect on the business where everything that can go badly, does go badly. The best case is the opposite, it all goes perfectly.
To be useful though, it’s good to explore best and worst case scenarios that are also realistic.
It’s likely that something will go wrong. It’s conceivable that several things could go wrong.
However, if you’re putting care, effort and attention into your business (and why wouldn’t you be) then it’s unlikely that everything that can go wrong, will go wrong. This just doesn’t seem realistic.
You might create this ultimate worst case scenario to assess the risk and danger in the business. An exercise in due diligence.
However, a slightly more optimistic worst case scenario will be useful for general decision making though.
Likewise, a more pessimistic best case scenario is better than looking at a situation where absolutely everything goes perfectly.
That’s also not a likely outcome.
With these scenarios, we are trying to identify a likely range of results that reality can fall into.
When we talk about what can go well or badly, we are actually talking about the KPI metrics you identified earlier.
Your confidence levels will help identify the base case for these KPIs, your best stab at what you think will actually happen.
The industry research conducted will help constrain your best and worst case scenarios within the boundaries of reality. There is no point in making a scenario where you immediately beat the industry best!
Work on modelling common sense scenarios, grounded in reality, research and qualified by your business experience.
Remember to factor in seasonality, local events and any other market factors you can think of.
If you genuinely don’t know what could happen for a specific activity, go on gut instinct but make sure you make a note of these areas. You’ll need to go back and refine them later as numbers do start to come in.
Using these scenarios to plan all areas of your business
These scenarios aren’t just about variations in sales.
Each scenario should contain the financial forecast for every area of your business. There are a number of common costs that will stay the same across each scenario.
However, once you can see the realistic range of sales in each scenario, other areas of your business will be impacted.
In the worst case scenario, additional spending might be kept at a minimum. However, in your base case and best case you’ll likely be planning the expansion of your business over time.
When you can predict likely revenue milestones, you can begin looking at the timing of employing new staff or purchasing new equipment for example.
No data, no problem
Remember, you won’t be without historical data for your financial forecast forever! Once you start gathering data, it can be used to confirm or debunk your assumptions.
If you follow this whole process carefully, you’ll find that your actual numbers will fit somewhere within these scenarios.
Making multiple realistic scenarios is the secret to making an effective financial forecast without any historical data.
They’ll help you make sound business decisions that aren’t just based on guesswork.
