Demand forecasting results in an estimate of future demand and gives an organization a basis for planning and making sound business decisions. Since the future is unknown, it is expected that some errors between a forecast and actual demand will exist, so the goal of a good forecasting technique would be to minimize the difference between the forecast and the actual demand. 

Address the following requirements:

Articulate the difference in short and long-term forecasts, forecasting techniques, and the benefits and challenges of each technique. 

Create a forecast for a situation with which you are familiar (personal or professional) explaining the situation and why you chose the method of forecasting that you did.

• Embed course material concepts, principles, and theories, which require supporting citations along with at least two scholarly, peer-reviewed references in supporting your answer. Keep in mind that these scholarly references can be found in the Saudi Digital Library by conducting an advanced search specific to scholarly references.

 

Demand Forecasting

Demand forecasting is a process which uses historical data to predict and estimate a product’s or service’s future demand (What is demand-driven forecasting? 2015). Demand forecasting is crucial since it helps the business make better decisions based on estimating the total revenues and sales for a certain period.

 Short-term forecasting is different from long-term forecasting. Short-term forecasting mainly predicts the trends in less than one to two years, and it mainly focuses on finding out the features of new products like their style, textile, and color. Contrarily, long-term forecasting predicts the trends in five or more years to come.  According to Insight Software (2020), there are four types of forecasting techniques. The first is the straight-line technique. It is commonly used to measure the constant growth rate, and its benefits are that it is easier to implement and only requires basic Math. However, it is challenging since if one variable is wrong, the entire method is wrong. The other technique is moving average. It involves checking a company’s repeated forecasts. Its benefits are that it makes a firm's performance understandable, making it easy to understand a company’s sales (Insight Software, 2020). The other technique is simple linear regression which compares one independent to a dependent variable.  The method is hard since statistical knowledge is needed, but it is crucial to analyze the relationship between the variables (Insight Software, 2020). The last technique is the multiple linear regression which compares more than one independent variable with a dependent variable.  It is challenging since statistical knowledge is required, but it is beneficial since it helps a company know its costs (Insight Software, 2020).

 My auntie’s grocery store’s annual growth rate has been steady for the past four years, and it has grown by 5%.   The store expects to continue growing for the net years and calculating its new year's growth using the 5% annual growth rate, and the store is expected to make another 5% growth rate the next year. The store can also make more accurate and clear predictions on the number of people it needs, and if there is a need to hire more people, it also understands the added payroll costs for each year. The above is an example of a straight-line forecasting technique. I selected this method since it is simple and only requires basic Math.

 In summation, demand forecasting is important for a business to know the demands for a product or service. The four forecasting techniques include straight line, simple linear, multiple linear, and moving average techniques.