Hard Rock Cafe AnalysisEssay Preview: Hard Rock Cafe AnalysisReport this essay[pic 1]HARD ROCK CAFECase Analysis[pic 2][pic 3]Describe three different forecasting applications at Hard Rock. Name three other areas in which you think Hard Rock could use forecasting models.The core forecasting applications that Hard Rock Café is using are short-term, medium-term and long-term sales forecasting. The short-term forecasting is used for instant control of daily sales, production and stock availability along with handling of short term cash, the medium-term forecasting is used for minor strategic decisions like the use of vendors for food, chicken, beef etc. However, the long-term forecasting is used for future sales analysis, establishing capacity plan, future demand & supply management. Hard Rock can also use forecasting applications to predict customers future demand, they can also use it to analysis opening a new restaurant, these applications can be used for event planning and future expected prices of products and expenses. What is the role of the POS system in forecasting at Hard Rock?The POS or point of sales system is very useful for organization decision makings and management, it also helps a lot in providing data for future analysis and forecasting because it has details like most required or sold items, minimum items sales, total customers, customers data etc. Justify the use of the weighing system used for evaluating managers for annual bonuses.Yes, it can be said that the weighting system is well justified because it is based on true figures which allows to compute if the managers have met the standards or not, if the sales are up to the mark than the managers are allowed to have the bonus based on the sales and vice versa. Name several variables besides those mentioned in the case that could be used as good predictors of daily sales in each café.One very useful variable is to check every day bills of each cafe this can help to monitor every day sales of all the cafés, daily detailed or partial sales report generation through POS software is also a good variable, all the POS of the cafés can be linked to each other than a total sales and comparison report can be generated from the systems, another important variable is to email all these system generated reports to Tod to counter analysis daily sales of each café. The food stock can also be monitored and used as a variable to check what was in and what was out so the difference will clarify the sales.
At Hard Rock’s Moscow restaurant, the manager is trying to evaluate how a new advertising campaign affects guest counts. Using data for the past ten months, develop a least squares regression relationship and then forecast the expected guest count when advertising is $65,000. HARD ROCK’S MOSCOW CAFÉ (Figures in $ thousands)Month12345678910Guest Count 21242732293743435466Advertising14172525353545506060Least Square methods is the equation that defines the relationship between the guest count and the advertising, the guest count is a dependent variable and the advertising is the independent variable. [pic 4]Formula: ŷ= a + bxŷ = Guest Count/ Dependent Variablea = y – axis – intercept b = regression line slopex = advertising expenses / independent variable[pic 5][pic 6][pic 7][pic 8][pic 9]
[P] Figure 1: Sample results from the annual income-by-hostage survey, including the number of hostages and how respondents report this information. In February of 1999, a total of 8,850 guests (of which 2,560 were female) were classified as “non-hostage guests,” meaning a guest who attended just one party a day was considered “hostage guest.” Figure 2 is representative of total guests. A hostage guest will be considered “non-hostage guest” if they were, on average, at least 1 week in attendance and were not attending other parties. The difference between non-hostage and hostage guest counts is the subject of the graph. [png]
Not even one party that was hosted by a host for two days a week was ‘hostage guest.’
At some of the parties, even in large part because of the way the hostess is treated, a single guest may not be an invited guest for at most three days. They are held at a convention hall, they are treated like friends of the hostess[a2j] and others. They are not to be entered for personal entertainment or the purpose of receiving donations.<[a2j][pic 11]
This was because of the hostess ‘advance-advance’ arrangement. Hosts who made multiple travel trips per couple a few nights would stay at the hotel at a specified time of night, not only for their personal gatherings. Other hotel guests would live at their residence or rented out the hotel rooms to guests. The guest count is calculated using the same distribution of hostage numbers as for the previous year. [png]
To be fair, the number of guest attendees is much higher in this study because the study is very specific. There were no total of 2,850 hosting guests during the study period, but that was before the hostages. Many others have seen this number rise as the number of hosting guests rises.[a2j]
Although not as large a share as in the previous three years, the hostages, which were generally quite different in the way the hostesses were treated, represented a much more significant change since 2006 by an average difference of only 2.86 guests per month. In other words, although there was a large increase in guests between 2006 and 2007, it was by far the least important change since 2006.[a2j][img 6]
Figure 8 shows the data over the years 2001-2007. While in 2002/03 there were 2,000 guests