The pasage below require analyis and indept breakdown

When it comes to introducing a new product in a company it takes a lot of thought to make it a reality. In this instance, introducing a new hot breakfast cereal it would be no different. With that in mind we will have to consider the how when it comes to minimal preparation time for the consumer. Forecasting will have to be used throughout the process to ensure steps are taken properly and data is analyzed for decision making. Demand forecasting uses both qualitative and quantitative methods and is used to make educated guesses on the future demand of a product or in this case: hot breakfast cereal. (Jacobs & Chase, 2020) Id like to note that every business/organization would benefit from forecasting the demand of their product(s) especially since a new product being launched is not always guaranteed success. That being said, it is a useful tool for determining the success of a new hot breakfast cereal.

Two methods that I find useful in this situation are the Delphi Method and Time Series Method. The Delphi method is a forecasting process framework based on the results of multiple rounds of questionnaires sent to a panel of experts. Several rounds of questionnaires are sent out to the group of experts, and the anonymous responses are aggregated and shared with the group after each round. The experts are allowed to adjust their answers in subsequent rounds, based on how they interpret the "group response" that has been provided to them. (Twin, 2020) This method addresses qualitative techniques which allows us to look at the data to forecast our cereal product. Whereas A time series is a sequence of numerical data points in successive order. In investing, a time series tracks the movement of the chosen data points, such as a securitys price, over a specified period of time with data points recorded at regular intervals. There is no minimum or maximum amount of time that must be included, allowing the data to be gathered in a way that provides the information being sought by the investor or analyst examining the activity. (Kenton, 2020) This is beneficial for us after the product is launched as it allows us to observe in real time and gather data for future product endeavors.