Hard Rock Cafe - Term Paper Example

?Running Head: Hard Rock Cafe (Operations Management) Hard Rock Cafe (Operations Management) Hard Rock Cafe (Operations Management) Executive summary Forecasting involves predicting future events and outcomes of a business. Mostly, it is used as a planning and decision making tool. Hard Rock Cafe uses forecasting in sales analysis. It uses various applications as its forecasting strategy apart from sales. Forecasting is one method that has led to the success of the restaurant. With forecasting, the management can analyze the forces of demand and supply and make reasonable decisions. They can also determine the point where profits will be maximized. However, forecasting is not realistic as it can be affected by economic changes due to the cyclical nature of the market (Evans 2002). The actual results might differ from the forecasted data giving rise to risk. Therefore, it important to ensure that proper forecasting is done using reliable data and models. Introduction Hard Rock Cafe has grown at a very fast rate from a one pub in 1979 to cafe having 129 branches in over 40 countries internationally. With such growth, the Cafe has been successful in delivering quality services and ensuring maximum customer satisfaction. Nowadays, the hospitality industry is growing drastically. For this reason, the hotels require consistent progress to attain a competitive edge. Operations management is important to ensure that daily activities of an organization are achieved efficiently. This report will analyze the operation management of Hard Rock Cafe with regard to its forecasting strategy. The current forecasting strategy of the Restaurant will be analyzed and suggestions on other possible strategies with regard to sales will be discussed. In order to assess the future perspectives, it is important to analyze the current situation first. 1. Hard Rock Cafe’s forecasting strategy There are different forecasting applications at Hard Rock Cafe. The forecasts relate to the long-run, intermediate and short run. Long run forecasting methods are used in establishing a better capacity plan. Intermediate forecasting methods are used when Hard Rock Cafe aims at establishing good contracts with its main suppliers. The method is used to forecast on revenues using the pricing and costing information in respect of every cafe. Short term forecasting is used on daily sales and takes into account variables such as events. The point of sale (POS) system is used in forecasting sales. The POS captures daily sales for each customer in all its cafes around the world. All daily sales are transmitted to the headquarters database electronically. From there, the financial team uses the data for forecasting purpose. In forecasting any anticipated events that might impact sales forecasts are taken into account. Such events might include sporting events or concerts to be performed anywhere near the cafes. The daily forecasts are further broken down to hourly sales which are used for employee scheduling purposes. Another forecasting strategy is Cafe’s menu planning which is done using multiple regressions. Multiple regression analysis helps the managers determine the degree of responsiveness on the quantity demanded to changes in price. Forecasting is also used in reorganizing the menu. This is because it measures the domino effect it would have on the menu items. Forecasting is also used in evaluating the performance of managers and setting rewards such as bonuses. Hard Rock Cafe uses a 3 year weighted moving average on cafe sales for this purpose. Bonuses are awarded when managers exceed their targets. Finally, forecasting is used in staff recruitment and management. Future demand is calculated and used to determine the period when to hire more staff or manage its staff in each department of the restaurant. Hard Rock Cafe can also use forecasting in the following areas: Establishing new outlets Determining future market changes by analysis the economic factors New products and its impact to the customers. 2. The role of the Point of sale system (POS) The POS captures daily sales at the point of sale in each cafe. With POS system, the management is able to analyze the buying trends of its customers around the world. It will as well analyze the tastes and preferences of their customers in each branch. The analysis helps the management redesign its operations with the aim of providing services that meet customer’s expectations and needs. Customer satisfaction is vital in every business which aims at achieving a competitive edge (Lowson, 2002). The vast database also reflects the performance of the cafe. Customers are able to get a global view of the cafe and make comparisons with the other cafes in the market. Managers can also determine the point at which profits are maximized for each cafe using the data they get on a daily basis with regard to sales. It is vital to have staffs that have experience and knowledge on the POS system in order to ensure efficiency in operation. 3. The weighing system The weighting average method makes use of time series which relies on historical data (Evans, 2002). The main assumption is that the future resembles the past. Therefore, the method expects the managers of Hard Rock Cafe to maximize their results for both the present and future. The results here mean the annual bonuses for the local managers and the benefits for the company. The concept of the annual bonuses requires an analysis of economic data of the last 3 years as shown below: The year before: 40% 2 years before: 40% 3 years before: 20% In order to get the bonuses, the local managers have to be efficient continuously to ensure better results always. In case the results don’t match the expectations meaning that the forecasted sales are less than the actual, the managers might not qualify for the bonuses. 4. Variables that can be used in predicting daily sales for each Cafe The variables that Hard Rock Cafe is currently using are the prior year’s sales for that day and additional information regarding upcoming special event. The weight of data information of prior year’s sales for that day is 40/40/20 (last year: 40 %, two years ago: 40 %, three years ago: 20 %). Additional information on any upcoming events is obtained directly from the chamber of commerce and the Tourist Board. special events include concerts, sport events and conventions. Other useful variables include: Weather conditions for a particular day. The condition can be predicted and if results indicate that at a particular day the weather will be favorable, then more customers should be expected as well as high sales. Vacation time around the restaurants and in other regions. If it is predicted that there will be vacations at a particular period, sales will be expected to be less since people will be in transit for their holidays. The cost of living. When a high cost of living is anticipated, peoples’ purchasing powers lowers and as a result sales revenue falls. Increased competition. Other restaurants may be offering special offer at lower prices than what Hard Rock Cafe is offering. This leads to increased competition and customers might go to competitors. When customers are lost, sales revenue also decreases. Income. Dates when people receive salaries or bonuses like Christmas festive can be used as variable for forecasting sales. At such times, there is much disposable income and as a result, sales should be expected to be high. 5. Recommendations It is vital for Hard Rock Cafe to do proper forecasting first before launching the advertising campaign. This is to minimize costs and time spent on the advertising campaign in case the market fails. The least squares linear regression method assumes that there is a dependent (y) and independent variable (x) (Yan 2009). We want to determine how the new advertising campaign by Hard Rock will affect the number of guests. The number of guest is the dependent variable Y while the cost of advertising is the independent variable X. the workings are shown below. Appendix 1   y x           Month Guest Count Advertising(000) (x-x) (y-y) (x-x)(y-y) (x-x)2 Y=1+x 1 21 14 -22.6 -16.6 375.16 510.76 15 2 24 17 17 24 408 289 18 3 27 25 25 27 675 625 26 4 32 25 25 32 800 625 26 5 29 35 35 29 1015 1225 36 6 37 35 35 37 1295 1225 36 7 43 45 45 43 1935 2025 46 8 43 50 50 43 2150 2500 51 9 54 60 60 54 3240 3600 61 10 66 60 60 66 3960 3600 61 Totals 376 366 329.40 338.40 15,853.16 16,224.76 376.00 Mean 37.6 36.6                   b = 15853   16225 b = 1     37.6= a + 1(36.6) 37.6= a+36.6 a= 1     y= 1+x Based on the working above in appendix 1, the forecast shows that there will be no change on the guest count if the advertising campaign is launched. Therefore, the manager should not go ahead with the advertising campaign. References Evans, M. K. (2002). Practical Business Forecasting. Wiley Publishers. Lowson R, (2002). Strategic Operations Management: The New Competitive Advantage. Routeledge. Yan, X, (2009). Linear Regression Analysis: Theory and Computing. World Scientific. Read More