Demand Estimation and Forecasting

16/04/2020 0 By indiafreenotes

No business owner has a crystal ball showing what customers will want during the upcoming year and how much of it they will buy. Fortunately, you can forecast demand using tools and information. While your demand estimation is unlikely to ever be completely accurate, it will still provide you with valuable benchmarks to help you plan. You can estimate and forecast demand using sophisticated mathematical tools based on sampling your entire industry, identifying trends and variables, and applying formulas developed by experts. If your business is smaller and you have access to less data, you can still make projections and plan upcoming production based on observations you have made about your own operations and the ways that demand for your product have trended over time.

The Difference between Estimation and Forecasting

Although estimation and forecasting are processes that are often used together, they aren’t the same. Estimation looks for links between data and operations, finding the reasons behind the numbers and using this information to plan for the future. Forecasting is driven by numbers rather than stories. It issues predictions based on past records without necessarily delving into why certain patterns have occurred. An estimation process for a weather dependent business such as a food concession could start with identifying the effects that sun, clouds and rain have on daily sales, and then researching the average number of sunny, cloudy and rainy days per year. A forecasting model could simply look at average sales during a particular month or season over several previous years. It would then factor in developments such as new products being introduced. This information would provide the basis for forecasting sales during an upcoming period.

The Importance of Estimation and Forecasting

Your business will use the information you get from estimation and forecasting to plan production and inventory. This is especially important if your production process requires considerable lead time to obtain parts from manufacturers and perform a series of interdependent tasks. If your estimation is faulty and your forecasting is too high, you may lose money by ending up with excess inventory that you can’t use. If your forecast falls short of demand, you may lose money by receiving orders that you can’t fill. Apart from the immediate sales lost, this situation could also hurt your business by making potential customers reluctant to order from you in the future. A business with a shorter production cycle will be better able to adjust for a shortfall caused by a faulty forecast by scrambling and producing extra, but you’ll probably pay extra for parts ordered in small quantities on short notice. Your payroll may also increase because last minute orders often require overtime hours.

Variables Affecting Demand Forecasting

Although countless variables will affect the demand for your product, you won’t be able to include them all in your forecasting model. Demand for bottled water spikes during natural disasters but these events are notoriously hard to predict. Despite these difficulties, the better you get at identifying trends and correlations that affect consumer demand, the better your estimations and forecasts will be.

Marketing and advertising drive demand. If you’ve conducted successful campaigns in the past and you consistently get a good response to your marketing efforts, it’s reasonably safe to forecast increases in sales to correspond with advertising expenditures. If your business experiences seasonal fluctuations that are weather dependent needs for your products, you can use sales figures from previous years to estimate current demand. If you manufacture windshield ice scrapers, it’s safe to say that you’ll sell more in the winter than in the summer.

Some variables are easier to predict in the short term than in the long term. It’s tricky to try to estimate, based on overall economic climate or fashion trends when you’re looking five years into the future. It’s safer to base longer term forecasts on variables that you can predict and influence, than on global developments that are completely beyond your control.