Making Decisions Based on Demand and Forecasting

It is desirable to develop demographic and psychographic profiles of these likely consumers (the target audience).

We have been provided with demand distributions for pizza based on past experience and know that Tom will

The current demand forecasting method is based on qualitative techniques more than quantitative ones. If the forecast is not accurate, the company would carry both inventory and stock out costs. It might lose customers due to shortage of supply or carry additional holding costs due to excess production. If the actual demand doesn’t match the forecast ones, and the forecast was too high, this will result in high inventories, obsolescence, asset disposals, and increased carrying costs. When a forecast is too low, the customer resorts to a competitive product or retailer. A supplier could lose both sales and shelf space at that retail location forever if their predictions continue to be inaccurate. The tolerance level of the average consumer

The Regional Food Manager for Ye Olde FoodKing Company has retained Mark Craig of Blue Steel Consulting to perform a regression analysis to forecast demand of your product. The four characteristics readily available included price, competitors’ price, average income, and market population. The results of each regression analysis are presented at the end of this memo. The remainder of this memo describes the regression analysis used and limitations to the data available. Running a regression provides a statistical procedure to estimate the liner dependency of one or more

II. Explore the supply and demand conditions for your firm’s product. a) Evaluate trends in demand over time, and explain their impact on the industry and the firm. You should consider including annual sales figures for the product your firm sells. b) Analyze information and data related to the demand and supply for your firm’s product(s) to support your recommendation for the firm’s actions. Remember to

In our analysis, we compared the profits earned by 60 Crusty Dough Pizza Company restaurants to factors associated to their menu, amenities, services, and statistics regarding the restaurant communities. The factors that we analyzed are listed in Table 1.

The purpose of this case is to determine which key variables drive Crusty Pizza Restaurant’s monthly profit and then forecast what the monthly profit would be for potential stores. Based off of this information we will be able to make a recommendation to Crusty Dough Pizza Restaurant on which stores they should open and which they avoid. The group was provided 60 restaurants’ data that included monthly profit, student population, advertising expenditures, parking spots, population within 20 miles, pizza varieties, and competitors within 15 miles. For the potential stores we were given all of this

Also, teething problems with marketing, operations etc might not lead to optimum sales. Therefore, we will project only 60% of this figure as first year sales and use the estimated figure as the sales figure for Year 2. Over the planning period, starting from Year 2 onwards, sales are expected to grow at a rate of 3.9% every year, in line with industry estimates of the average growth of the restaurant industry in the US (Source: Mintel International, cited in section 6.0).

The pizza market can be very lucrative, therefore it is very competitive. There are low barriers to entry for this market because there is

The Pizza Delivery Quick (PDQ) Industry service in America is considered to be a very successful market in the quick service restaurant industry. Although the industry success is very appealing, managing the day-to-day operations needs significant planning and a clear tactics to create, implement, execute and have successful results. However, the PDQ last report sales are on the level of 30%, which places the company in a serious difficult position to continue operating competitively.

The sales forecast is based on projected levels of demand. All the numbers are expressed

The market studies consisting of the forecast of the estimated demand show that the pizza

We can analyse from exhibit 13,14 & 15 , that kit has huge potential of attracting customer

Tony has asked you for some assistance in interpreting the data that he has collected. In particular, he needs to know if the true average delivery time for Pronto Pizza is greater than 25 minutes. Use the data in the file PRONTO.XLSX to answer his question. A description of this data set is given in the Data Description section. Also, examine the data for further information that might help Tony in making his decision about the 29-minute delivery guarantee and in improving his pizza delivery service. The Case Questions will assist you in your analysis of the data. Use important details from your analysis to support your recommendations.

Aggregate demand forecasting is used by the company because the business is centered around the custom printing of the