Nelson Mandela University Lecture Notes on Food Production

Lecture 21 to 23 Chapter 8 Production  Lecture objectives Introduction After completion of this lecture, students should be able to: Main objectives  Plan and evaluate food and food preparation techniques  Manage the production of...

Lecture 21 to 23 Chapter 8 Production  Lecture objectives Introduction After completion of this lecture, students should be able to: Main objectives  Plan and evaluate food and food preparation techniques  Manage the production of food in large quantities  Perform basic preparation of a range of food on large scale.  Lecture objectives Introduction Discuss the objectives of cooking in food production Explain the use of administrative tools in production scheduling and planning Standardize and adjust recipes Discuss the reasons for forecasting Use forecasting and apply various methods and models  Production p.216  Complex transformation of ingredients to final product.  Preparation of menu items in the needed quantity and quality.  Quantity: large quantities in comparison to home/family preparation  Quality: food must be appealing, safe and nutritionally sound.  The transformation of raw or processed foods into an acceptable finished product, ready for service, is an essential function in any foodservice system.  Production p. 217  Production planning and scheduling are vital to the production of high quality food and are important management responsibilities.  If you have planned correctly, food will be:  Appealing to the customer  Prepared in appropriate quantity  Microbiologically safe  Within budgetary constraints  Production  The extent of actual preparation and cooking done on the premises depends on the type of foodservice system.  Food quantity = complexity  Foodservice managers should thus be knowledgeable on basic cooking skills, time- temperature relationships AND quality control challenges. Objectives of Cooking Enhance aesthetic appeal of raw food Destroy harmful organisms Improve digestibility and maximise nutrient retention Administrative tools for food production  Standardized recipes  Recipe Adjustment  Forecasting  Calculation of quantities of food to produce  Standardized Recipe  Definition: a recipe that has been tested and adapted to the requirements of a specific foodservice operation.  These requirements include:  Customer expectations,  Efficient and effective use of available resources, that includes: personnel, equipment and money.  The format of a recipe is an orderly arrangement of the recipe information that should be developed. Advantages of Standardized Recipe  Consistency in quality (flavour, texture, portion size, nutrient composition).  Simplifies planning, purchasing, forecasting, recipe costing and pricing.  Minimises effect of staff turnover on food quality.  Simplifies training of staff.  Important in centralized ingredient assembly.  Save money by controlling overproduction.  Procedures Directions for preparation should be listed in logical steps. Timing should be provided for some procedures. The recipe should be tested before being served to customers. Quality standards are measurable statements of the aesthetic characteristics of food items, and they serve as the basis for sensory analyses of the prepared product. (example on page 225). Forecasting  Goal: Estimate future demand using past data.  Why forecasting?  = to predict the food needs for a day or for a specific time period. Forecasting  Reasons for forecasting  Purchaser needs to know how much to order and when.  Minimizes chance of over- or under production.  Improved customer satisfaction.  Controlling labour costs. Collection of data Historical data: Historical data or past data are used to determine needs and to establish trends in all forecasting methods. - Data should be consistent and accurately recorded.  Categories of data to collect vary depending on the type of foodservice organization,  scope of services provided and  whether customers are allowed to select menu items. Historical data continues…… Examples of data categories for various organizations: Restaurants/cafeterias → Customers served per meal Menu items sold per meal period Beverage sales (types and amounts) Historical data continues…… Examples of data categories for various organizations: Schools → Student enrollment Student purchasing (receiving) full or partial meal Teachers and staff purchasing meals Historical data continues…… Examples of data categories for various organizations: Hospitals → Daily patient census Patients on therapeutic diets Daily patient admissions and discharges Historical data continues…… Examples of data categories for various organizations: Vending services → Product placed in machine at each fill Total cash removed Food remaining in machine at each refill. Historical data continues…… Meals served per unit, left overs or shortages must be documented. Over time, a pattern of menu item demand or total meals served will emerge from the recorded data. This pattern, along with knowledge of pattern variance, will assist the production planner in making a valid estimate of future menu demand. Patterns influencing pattern variance include public holidays, weather conditions, and special events. Criteria for selecting a forecasting method To select the most suitable forecasting model for a foodservice unit requires careful planning and evaluation. Whether you choose a computerized or manual method of forecasting, there are several factors that should be considered before deciding on a forecasting system: Criteria for selecting a forecasting method Factors:  Cost  Accuracy  Relevancy  Lead time  Pattern of food selection  Ease of use  Level of detail  Responsiveness to changes  (Table 8.9). Forecast models  Moving average  Exponential smoothing  Regression  Autoregressive moving average → These models are mathematical descriptions of meals served or of menu item selection behaviour. → The information for the mathematical models is based on historical data and is expressed as an average of past service or selection behaviour. Forecast models 1. Moving average model - Referred to as a time series method of forecasting and is easy to use. - Using records from the past, a group of data is averaged and used as the first forecast. - The next forecast is calculated by dropping the first number and adding the next. - This process continues for all data available. - Best for everyday, stable items e.g. coffee, bread, common sides etc Forecast models  Exponential smoothing model - Another time series model. - Similar to the moving average technique except that it accounts for seasonality of data and adjusts for forecast error. - This results in a higher level of forecast accuracy. - The simple exponential smoothing model predicts the next demand by weighting the data; more recent data are weighted more heavily than older data. - Best suitable for gradually trending items e.g. new sandwiches, desserts gaining popularity Forecast models  Exponential smoothing model continues….. - The factor used to weigh the data is referred to as alpha. - Alpha is determined statistically and in foodservice forecasting, is generally valued at 0.3. Can be higher for items affected by short term changes e.g. daily specials, or new menu item promotions. - The purpose of alpha is to adjust any errors in previous forecasts. Forecast models  Exponential smoothing model continues….. - St​ =α⋅X t​ +(1−α)⋅S t−1​ - Where:𝑆𝑆𝑡𝑡​ is the smoothed value for the current period. - 𝑋𝑋𝑡𝑡​ is the actual value for the current period. - 𝑆𝑆𝑡𝑡−1​ is the smoothed value for the previous period. - 𝛼𝛼 is the smoothing factor (between 0 and 1). Forecast models  Regression model and Autoregressive integrated moving average model - Sophisticated statistical methods in which past data are analyzed to determine the best mathematical approach to forecasting. - These methods generally require the assistance of a statistician and are used with computer – assisted forecasting systems. Forecast models  Regression model Can forecast demand by considering multiple variables that affect sales, such as price changes, promotions, weather, or customer demographics. Best suitable for menu items influenced by multiple factors (promotions, pricing, events). Forecast models Autoregressive integrated moving average (ARIMA) model - A powerful forecasting model that incorporates trends, seasonality, and past values to provide a dynamic and accurate forecast. - Best suitable for complex items with both long-term trends and seasonality (trend- driven meals, fast-growing popular items)  Determination of Quantities to Produce  The forecast is the basis for estimating quantities in advance  Needed for both quantities to produce and quantities to purchase for stores  Forecasts sometimes need to be adjusted at time of production due to unforeseen circumstances.  E.g. cold and flu in schools.  Determination of Quantities to Produce  The actual amount of food to be prepared is based on:  The number of persons to be served  Portion size  Amount of wastage and shrinkage loss of foods This information is acquired through the recipe adjustment according to the required number of meals to be served.  Quantities to produce 1. Determine the portion size in grams (g) 2. Multiply the portion size by the estimated number to be served and convert to kilogram (EP) EP (kg) = g x number of portions 1000 3. Yield%= Edible portion/Purchase Weight *100 4. Divide the EP weight by the yield percentage Amount to order = EP weight Yield% 4. Convert the amount needed to the most appropriate purchase unit Edible Portion (EP) is the amount of the food item needed after trimming or cooking (what will be consumed). Yield Percentage is the percentage of the item that remains after trimming or cooking. Purchase weight (AP) is the amount of food to be purchased to get the required edible portion Example:  Calculate the amount of carrots needed for 50 people.  1 portion edible weight pp = 80g  Purchase weight = 150g  Available in packets of 500g Example: EP = 80 g x 50 people = 4000 g/1000 = 4 kg Yield % = Edible portion/Purchase Weight *100 (80 g / 150 g)*100 = 53% Amount to order: 4 kg / 53% =7.5 kg How many 500 g bags? 15 bags  Production scheduling A decision-making and communication process whereby the production staff is informed of how the actual activity of food preparation is to take place over a specified period of time.  Production scheduling  Work to be done (specific menu items to be produced within a defined time period)  Who is to perform the specific tasks.  Amounts of individual items to produce.  Source recipe, identified by name and code number.  Standard portion sizes and variations for specific modified diets.  Target completion times.  Production scheduling  Production schedules A detailed document used to communicate with/to the production staff the work that needs to be done for specified period of time.  Production meetings A meeting with the production staff to discuss the menu and production plans.  Production control  Ingredient assembly Central assembly of ingredients for food production has been found to be cost effective in many operations.  Personnel and equipment Personnel assigned to the ingredient room must be able to read, write, and perform simple maths. Safety precautions and sanitation standards should be stressed. Portion control…..  Portion control Standardized portions are important to control cost, and to create and maintain customer satisfaction. Employees should know the number of servings expected from a certain batch size and be familiar with the size of the portion.  Product evaluation  This is part of the initial testing phase of a new recipe and important for quality control.  Many foodservice organizations conduct sensory analysis just prior to meal service. Sensory analysis form – pg. 238 Sensory analysis form – pg. 238 Sensory analysis form – pg. 238 Sensory analysis form – pg. 238 Class Activity 1. You need to standardise a recipe for a carrot cake. What are the advantages of a standardise recipe? (6) 2. A recipe for Chicken-Broccoli Stir Fry is being standardise for use in a nursing home. In writing the cooking procedures, list and discuss at least FOUR objectives that should be considered. (12) 3. You are preparing a chicken stew for 1200 meals in the hospital. Complete the following table using the factor method. (8) Ingredients As purchased Edible portion AP for 1200 EP for 1200 (AP) for 4 (EP) for 4 portions portions portions portions Frozen 600g 210g chicken Carrots 160g 125g Tomatoes 220g 200g Onions 140g 112g 4. How many packets of chicken needs to be purchased if one packet weights 500 grams? (show calculation) (2) 5. Calculate the inedible portion for each of the ingredients (show calculation)(8) 6. What is the goal of forecasting? (1) 7. List the reasons for forecasting (4) 8. Discuss the different type of forecast models (9) mandela.ac.za