When it comes to starting a business, entrepreneurs face a number of challenges, not least the issue of whether there is actually a demand for their particular product or service. The more unique the concept, the greater the challenge in predicting future sales levels. However, as this article will show, there are a number of methods that can assist you in making better educated guesses when forecasting sales for your goods or service.
Since time immemorial, people have sought to predict the future. Until the emergence of the relatively modern concept of ‘risk’ and the development of probability theory in the 17th century, predictions about the future had traditionally been the preserve of soothsayers such as Nostradamus. However, with probability theory, mathematicians demonstrated that one could use past indicators to make educated guesses as to the expected outcome of a particular set of events, e.g., the roll of a die. All these years later, and despite our progress, we still lack the ability to predict the future. Nevertheless, by considering various risks and probabilities, we can aim to understand some likely future (sales) scenarios to a greater degree.
Naturally, if you run an existing business, you will have a trading history and will be able to use this data to make more informed decisions with regards to future possible outcomes. If you generate strong cash flows and have a stable cost base, you can assess available investment options with more confidence. On the other hand, if you are just about to start up, you obviously lack ‘history’, and while you can make some assessment of the initial monthly outgoings (particularly fixed costs), the real challenge is to accurately predict the likely sales revenues. Breaking revenue down into its constituents (the product price times the quantity sold) gives entrepreneurs the two key figures they need to consider to begin forecasting. Price can be determined by the entrepreneur, while quantity is the variable that is most difficult to predict (notwithstanding the correlation between price and demand).
Why is forecasting important?
Firstly, cash is the lifeblood of any business and is needed to fund working capital to enable a business to run effectively. A large number of business expenses and investments in assets need to be paid for up front, and these obviously have to be paid for out of capital. These outgoings occur against a backdrop of uncertain sales levels and often a delay in receiving cash on those sales (exacerbated if your sales are predominantly on credit). Consequently, companies need to prepare cash flow forecasts to assess what the level of the cash shortfall will be, so they can obtain financial assistance in advance, such as bank overdrafts or loans. Companies can be profitable on paper yet run the risk of falling insolvent if they do not meet their obligations as they fall due. Hence, it is necessary to understand the nuances of cash flow for your particular business from Day 1, as good cash flow management plays a large role in ensuring continued solvency.
Of additional importance, investments in businesses are based on the ability of the firm to generate free cash flows, so as to reward the investor for taking a risk. The amount of cash generated and its timing is of particular interest to investors, who face an array of investment options with various risk / return tradeoffs. Typically, investors will look to review a business plan before they invest and they will pay particular attention to the predicted sales levels and cash generation capability of the company (as detailed in the cash flow forecast). Hence, these two factors underline why accurate forecasting is of vital importance to those setting up in business.
What forces affect demand?
At the start-up stage it is difficult to assess with certainty what you believe the revenue will be for Month 1. Once you have one month of trading, then of course you can use that month’s figures to forecast likely sales levels in subsequent months. As a result, when you draw up your business plan initially, you need to assess the landscape and try to estimate a range for the predicted sales levels.
The following represents a list of some questions about the key external and internal determinants of demand. Answers to these questions will support the entrepreneur in coming up with plausible figures for Month 1/ Year 1.
Does the product or service fulfill an existing need? Has it been produced such that each key feature and resultant benefit is attractive to a commercially viable market segment?
What is the competitive landscape like, i.e., are there barriers to entry/ attractive alternatives? What is the turnover of a close competitor and how profitable are they?
Macro Environmental Trends
How is the product correlated to the external environment? Does demand drop significantly when the economy is struggling? Does the product attract extraordinary taxes or tariffs, e.g., alcohol and tobacco? Will a growing environmental consciousness affect demand levels?
Is the product priced at a level that will attract a sufficient number of customers? Standard demand and supply rules would dictate that the lower the price, the higher the demand for a product. What price level maximizes profitability?
Is there any seasonality or cyclicality element to the product or service?
Are there many attractive substitutes? What are the main bases for differentiation in the market, i.e., price, features, service, etc.?
What is the market demand for the product category (i.e., the size of the prize you are chasing)? Is it growing or is it stagnant?
Is there a marketing plan in place? What are the key marketing activities? Is there sufficient budget to effectively target various segments?
Route to Market
Has the company secured a "route to market"? How will customers access the product?
Having assessed the various determinants of demand, it is now a little easier to hone in on a plausible range of sales forecasts for the months and years ahead.
How do you make a sales forecast?
Once you have considered the context, you are now in a more informed position to consider potential revenue figures.
There are two main elements to forecasting – the use of facts and the use of subjective assessment / judgment. Given the uncertainty, you can aim to identify a range for the sales predictions depending on your assessment of the potential impact on sales of specific conditions, be they environmental or company-specific (or a combination of both). There are numerous determinants of demand, ranging from the performance of the overall economy to whether there is any appetite (demand) for your particular product or service. You need to consider which of these is likely to have the biggest impact on your offering. Ideally, you should be able to obtain a Profit and Loss / Income Statement (facts) for a competitor and you could use that as a reference point to assess likely demand levels for your company (judgment).
Looking for comparable indicators for a service
Not every new company has a directly comparable competitor whose accounts can be scrutinized for sales data. However, no matter how unique your concept is, if you define your market widely enough, it is likely that you can use figures from alternative offerings (facts) to help you assess likely demand levels (judgment). For example, when the Millennium Dome was being launched in London in 2000, they initially targeted 12 million visitors in Year 1. While the actual visitor figures reached an impressive 6.5 million, the huge shortfall in numbers meant that it was not even close to breaking even / financial viability and it ultimately failed as a venture. Had senior management looked closely at visitor figures for the UK’s other top paying attractions, they would have found that Alton Towers was top at 2.65 million visitors closely followed by Madam Tussaud’s and the Tower of London. These proxies would have given them a clearer sense of the range in numbers and a more conservative target within this range would have resulted in a very different proposition / investment structure from Day 1.
If you are looking to set up a local service such as a coffee shop, there are also numerous resources you can use in assessing likely demand. Websites such as www.caci.co.uk/acorn/ and www.upmystreet.com/ enable you to get extensive free demographic data about areas based on post code searches. Profiles available from www.scavenger.net offer an insight into a specific industry and its outlook. Finally, if you want to consider setting up overseas, then websites such as www.cia.gov/cia/publications/factbook/ give an excellent insight into various local conditions in advance of undertaking more localised research.
The facts from these sources need to be backed up by judgment. If, for example, you were looking to open a coffee shop on the Fulham Road, London, you would start with a list of likely costs, ranging from rent through to set-up, etc. Once you had an estimate of the costs, you would then look to work out the revenues. To do this, you could park a car outside of a particular target location for the shop and count “footfall” for the day. You could also obtain average spend per customer, estimate a percentage conversion rate from the footfall and use these figures to assess whether you believed you could break even by relying on passing trade.
You could also drive around the neighbourhood looking at competitive coffee shops and their locations. Hence, by using a number of different data points, you can now make a more informed decision on the financial viability of a proposed coffee shop in Fulham. If you want to get more scientific, you could assess how consumption of coffee is correlated with the economy (i.e., will less be consumed in a down turn) and also whether you needed to stock alternatives to boost average spend e.g. fair trade coffee /non coffee-based alternatives or food. As mentioned previously, there is no exact number – you are merely striving to produce a good educated guess, i.e., a plausible figure that is within a range for a typical company in that field. Product Indicators
There are a number of different methods to try to assess sales levels for a new product. Firstly, by assessing the key benefits of the product, it is possible to understand the core need being fulfilled. This will then help inform you of a category of complements or substitute products it belongs to. More scientific approaches include George Day’s top down and bottom up approaches which seek to assess demand from different sides. The top down approach seeks to drill down from the total population to a final market segment, whereas the bottom up approach looks to generalize from the consumption of individual customers.
Alongside these approaches are more subtle ones, for example, an assessment of demand based upon data from disparate sources such as the Internet. Here are two common tools:
“Key Word Assistant” from Overture http://inventory.uk.overture.com/d/searchinventory/suggestion/ is one such tool. It enables you to enter a search term for your product and it returns the number of searches that were undertaken on that term in the previous month. Invariably searches are attempts to resolve problems or satisfy needs, so the results can give an indication as to likely demand levels.
“eBay Pulse” relies on a similar concept http://pulse.ebay.co.uk/ as it gives an insight into top sellers from the eBay market place. Again, this can help you assess demand for a particular product, determine the category it is best suited to, and even a naming convention (when assessed in conjunction with the Key Word Assistant).
How do you make a more accurate sales forecast?
Having assessed the wider environmental conditions and considered the internal decisions regarding the proposition, it is possible to make more accurate predictions for Month 1. After that, it is a case of extrapolating into the future using a growth factor and flexing for seasonality or cyclical trends. Notwithstanding the difficulties in forecasting for a start-up, the real benefits accrue after a year of successful trading. Once there is an historical record for a year of trading, it is then possible to plan with more certainty through the use of more scientific methods, such as trend analysis and comparison with variables. For example, an ice cream vendor could compare sales of ice cream with an obvious variable – weather temperature – in order to assess the correlation between the two variables. Once a sales forecast has been made, it can then be used for budgeting, allocating resources, managing cash flow, and as a basis to secure investment.
The aim of sales forecasting is to come up with some revenue figures that can be considered to be credible in the wider context. As illustrated above, forecasting is not an exact science but a mix of fact-based analysis and judgment. Placing some rigor around the process of deriving credible revenue figures also serves the entrepreneur by enhancing their awareness of some of the key drivers for revenue growth in their business. It will also help them to produce a more plausible business plan, and ensure that the author is confidently able to answer questions regarding the market opportunity – questions that will top the list of any prospective investor or bank manager.