Forecasting at Hard Rock
1. List and discuss at least two tactics implemented by management in order to become more competitive and world-class in their operations.
Hard Rock Café has clearly made great strides in modernizing their business venue by utilizing sophisticated POS systems with the latest forecasting trends. Some tactics they have implemented include an extensive Point-of-sale system (POS), which captures transaction data on nearly every person who walks through a cafe's door. The sale of each entrée represents one customer. They forecast monthly guest counts, retail sales, banquet sales, and concert sales (if applicable) at each café. In order to evaluate management, a 3-year weighted moving average is applied to cafe sales. As the text described, the most recent two years are weighted 40% each while the third prior year is weighted at 20%. If cafe general managers exceed their targets, a bonus is computed. By having a sophisticated evaluation scale, the company in addition to the employees that had the greatest results will be rewarded. This motivates all employees to strive for their best.
2. Using regression to predict crossover from one menu item to another due to price sensitivity is not a time series problem, but an associative or causal approach. Please discuss how this technique is different than traditional time-series modeling. Do you think it is a good or bad measure of productivity? Please explain you answer.
Using multiple regressions, managers can compute the impact on demand of other menu items if the price of one item is changed. Unlike time series forecasting, associative forecasting models usually consider several variables that are related to the quantity being predicted. Once these related variables have been found, a statistical model is built and used to forecast the item of interest. Therefore, an associative or casual approach is a better indicator than the time series methods that use only the historical values for the forecasted
Hard Rock Café has clearly made great strides in modernizing their business venue by utilizing sophisticated POS systems with the latest forecasting trends. Some tactics they have implemented include an extensive Point-of-sale system (POS), which captures transaction data on nearly every person who walks through a cafe's door. The sale of each entrée represents one customer. They forecast monthly guest counts, retail sales, banquet sales, and concert sales (if applicable) at each café. In order to evaluate management, a 3-year weighted moving average is applied to cafe sales. As the text described, the most recent two years are weighted 40% each while the third prior year is weighted at 20%. If cafe general managers exceed their targets, a bonus is computed. By having a sophisticated evaluation scale, the company in addition to the employees that had the greatest results will be rewarded. This motivates all employees to strive for their best.
2. Using regression to predict crossover from one menu item to another due to price sensitivity is not a time series problem, but an associative or causal approach. Please discuss how this technique is different than traditional time-series modeling. Do you think it is a good or bad measure of productivity? Please explain you answer.
Using multiple regressions, managers can compute the impact on demand of other menu items if the price of one item is changed. Unlike time series forecasting, associative forecasting models usually consider several variables that are related to the quantity being predicted. Once these related variables have been found, a statistical model is built and used to forecast the item of interest. Therefore, an associative or casual approach is a better indicator than the time series methods that use only the historical values for the forecasted