Demand Forecasting and Sales Forecasting are different, and the results of each can have a dramatic impact on your profitability.
There’s a misconception that demand forecasting and sales forecasting are the same. Many people think they’re interchangeable. Actually, there is a big difference that will lead to drastically different accuracy results; even though sales and demand forecasting use both, similar and different data points, to calculate the forecast.
Sales forecasting is generally a prediction of market response and relies on real numbers compared to experience and intuition. It uses mathematical equations and calculations to provide the company with a detailed outlook of anticipated revenue over a specific future time period (typically broken down into short, medium, and long time periods). It also helps to determine financial plans with banks, anticipate sales growth, and allocate resource strategies. Sales forecasting is based off previous revenue and sales figures.
It's simply a guess of how much we will sell this coming year based on:
i) Experience. We sold 100 units last year with 4 salespeople, we hired one more salesperson so we forecast sales of 125 units next year.
ii) Intuition. It’s a startup but everyone is going to want one of our products and there are 100 million people and we expect to 80% would purchase our product so we forecast to sell just about 80 million.
As you can see, Sales Forecast can vary widely depending on what you choose to input.
One form of sales forecasting is micro forecasting. This focuses in to give the business a hard revenue target and determine the market share of a specific product. It then anticipates the market share of that product and how it will adapt over time - shown in the form of a percentage of total sales that product receives in relation to sales revenues of its competitors in a specific market segment.
Demand forecasting relies rather heavily on the economic and consumer conditions in the market place. While it is a type of sales forecasting, its goal is different. It attempts to determine the consumer interest for a product across the entire market place. Essentially, demand forecasting provides critical data about the markets a company currently operates in, and those it hopes to move in to. Without demand forecasting, the business assumes the risk of pursuing and operating in a market that potentially doesn’t have a need for their product.
Demand forecasting gauges the current level of demand for a specific product or service and projects how that demand will shape the future demand curve. It requires accurate current and previous market, sales, and revenue numbers to predict future demand. Without those figures, it becomes much more challenging to make accurate projections, though not impossible.
This type of forecasting is often used in the short term because of the rapid and unforeseen factors that affect and influence demand over time. It is also used more heavily in inventory replenishment.
For example, for a retailer to forecast the demand in June, it would need to know:
i) How much we sold last May vs. what we sold this May?
ii) Annual trend (up 2% or down 5% - whatever)
iii) Sales Orders already in place for June
iv) How many Sales Orders we had in place this time last June?
v) What is current inventory position?
vi) What is current manufacturing/purchasing capacity?
So, the demand forecast is going to use an algorithm to weight and combine all these variables (and probably several more) to project what to buy or make in order to insure we have enough product on hand to meet our demand.
And if you’re Demand Forecast goes wrong, you either end up with too much inventory, which self-corrects the July Demand Forecast or you run out of product, which should bump up the July Demand Forecast so it doesn’t happen again.