As soon as your startup begins regular sales activities, it is important to create periodic sales forecasts. A sales forecast is a projection of what your sales revenue will be for a specific period in the future—for example, the next month, quarter or year. A sales forecast is essential not only to understand and manage sales activities, but also to facilitate the growth and development of the entire company.
Sales forecasts are based on capturing and analyzing metadata about your company’s sales activities. (Metadata is data about your data—in this case, it is the collected body of statistics about your sales activities, including cold calling, deals closed, expenses, and so forth.) Because startups typically have little metadata to work with at the outset, it is vital to systematically capture this data. The effort of capturing this information is not onerous, and the return value upon analysis of the data is tremendous and essential to the success of your company.
Suffice to say, many companies have gone bankrupt because they did not adequately plan their cash flow and liquidity. They wound up unable to meet their financial obligations despite having a business that could have been sustainable over time.
Given the resources you commit to sales and business-development activities and the length of time a sales process can take, you do not want to lose an order because you cannot deliver on time. Sales forecasts bring a level of clarity to future delivery volumes and help you plan your own procurement and production schedule and avoid supply-chain shortages.
Investors would like to understand how you expect and plan for sales volumes to develop. The more accurate a revenue forecast you can present, the more credibility you will gain in the eyes of potential investors.
In the case of startups, the numbers used to calculate a sales forecast are necessarily based on metadata or assumptions that are backed by limited historical information. The absence of historical data means that forecasts must rely on fairly accurate assumptions. Initially, the forecast must yield a result that is a good estimate—one that allows the finance and operations department to properly plan their liquidity and capacity requirements.
Keep in mind that forecasts are best done by product category, sub-category and brand. If you forecast at a more detailed level, it will involve too many particulars to be manageable. On the other hand, if you forecast at a higher level (that is, for a department the company as a whole), you risk capturing too little information for the forecast to be useful.
As a matter of routine, startups should regularly review the data and the fundamental assumptions on which their sales forecasts are based.
Try to systematically reduce errors by seeking to understand where previous forecasts went wrong. Use a healthy dose of realism and reasoning. Not only will this improve your forecasting accuracy, but the insights you generate will also help management to recognize which sales and marketing initiatives yield better results than others. This is tied to the profitability of your operation, and thus benefits the entire organization.
In the business-to-business (B2B) environment, most start-ups begin with some form of personal and direct sales activities before determining whether to enter into agreements with a distributor, reseller, systems integrator or other marketing intermediary.
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