...The business development of the construction industry depends not only on the ability to optimize operations within industry, adapt to external conditions, but also on the country's economic development, the situation in the market. The Manpower forecasting model. The Estimated Manpower Forecast Model is designed to capture the future labour requirements of the engineering construction industry by key sectors. Manpower is undoubtedly a valuable asset upon which the construction industry depends. However, rapid changes of the economy, working arrangements, and technology in construction advocate reliable estimations of manpower demand to lessen future skills imbalance. The aim of this research is to develop advanced manpower demand forecasting models, at both project and industry levels, to facilitate manpower planning for the construction industry. At the project level, statistical models for forecasting the demand of labour demand for a construction project were developed using multiple regression analysis. Results reveal that project cost and project type play an important role in determining the project labour requirements. The forecasting models could serve as practical tools for contractors and government to predict the labour requirements and number of jobs created at an early outset, thus enabling proper human resources planning and budgeting. At the industry level, co-integration analysis was applied to develop a long-term relationship between aggregate construction...
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...based on forecasts. Every decision becomes operational at some point in the future, so it should be based on forecasts of future conditions. Forecasts are needed throughout an organization -- and they should certainly not be produced by an isolated group of forecasters. Neither is forecasting ever "finished". Forecasts are needed continually, and as time moves on, the impact of the forecasts on actual performance is measured; original forecasts are updated; and decisions are modified, and so on. For example, many inventory systems cater for uncertain demand. The inventory parameters in these systems require estimates of the demand and forecast error distributions. The two stages of these systems, forecasting and inventory control, are often examined independently. Most studies tend to look at demand forecasting as if this were an end in itself, or at stock control models as if there were no preceding stages of computation. Nevertheless, it is important to understand the interaction between demand forecasting and inventory control since this influences the performance of the inventory system. This integrated process is shown in the following figure: The decision-maker uses forecasting models to assist him or her in decision-making process. The decision-making often uses the modeling process to investigate the impact of different courses of action retrospectively; that is, "as if" the decision has already been made under a course of action. That is why the sequence of steps...
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...Choose one of the forecasting methods and explain the rationale behind using it in real life. I would choose to use the exponential smoothing forecast method because it weighs the most recent past data more strongly than more distant past data. This makes it so that the forecast will react more strongly to immediate changes in the data. This is good to examine when dealing with seasonal patterns and trends that may be taking place. I would find this information very useful when examining the increased production of a product that appears to be in higher demand in recent times than past. Describe how a domestic fast food chain with plans for expanding into China would be able to use a forecasting model. By looking at the data of other companies the fast food chain would be able to put together a forecast to determine if their business venture was viable. They could examine the sales data and determine through a exponential smoothing forecast if it made sense for them to enter into the market. This would show the trends and changes in the data more recently rather than in past time. What is the difference between a causal model and a time- series model? Give an example of when each would be used. The time–series model is based on using historical data to predict future behavior. This method could be used by a retail store, fast food restaurant or clothing manufacturer to predict sales for an upcoming season change. The causal model uses a mathematical correlation...
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...BU3315 Unit 4 Research Paper 2 Forecasting Model in Use For this research paper I used a study done by Sprint for forecasting usage costs and computer capacity required for their network and cell phone towers. The use of data related to transactions collected from computing devices in their facilities was used to calculate a forecast of usage at peak hours. This study was done in the early stages of Sprint becoming a cell phone company and it is still used today to help upgrade and maintain their network. This helped Sprint determine a forecast of data usage on customer cell phones so they could determine the type and amount of equipment needed to get ample coverage and network bandwidth to provide their cell phone service to the customers. The methods they used were 5 variables used in their forecasting model; 1. First span of time comprises usage in seconds, minutes, hours, days, months and years. 2. Computing device comprises at least one of a server, telecommunications switch and computer 3. Data collection of computing software processes, computer programs used, business logic model, and software usage (apps) 4. Software usage at server farms 5. Threshold percentage representing actual customer airtime usage By doing this Sprint was able to determine the demand that customers would be putting on their networks and the bandwidth being used. The first inclination was to build a massive network of coverage all across America to stake claim to...
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...Forecasting Methods Genius forecasting - This method is based on a combination of intuition, insight, and luck. Psychics and crystal ball readers are the most extreme case of genius forecasting. Their forecasts are based exclusively on intuition. Science fiction writers have sometimes described new technologies with uncanny accuracy. There are many examples where men and women have been remarkable successful at predicting the future. There are also many examples of wrong forecasts. The weakness in genius forecasting is that its impossible to recognize a good forecast until the forecast has come to pass. Some psychic individuals are capable of producing consistently accurate forecasts. Mainstream science generally ignores this fact because the implications are simply to difficult to accept. Our current understanding of reality is not adequate to explain this phenomena. Trend extrapolation - These methods examine trends and cycles in historical data, and then use mathematical techniques to extrapolate to the future. The assumption of all these techniques is that the forces responsible for creating the past, will continue to operate in the future. This is often a valid assumption when forecasting short term horizons, but it falls short when creating medium and long term forecasts. The further out we attempt to forecast, the less certain we become of the forecast. The stability of the environment is the key factor in determining whether trend extrapolation is an appropriate forecasting...
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...Introduction to Management Science, 10e (Taylor) Chapter 15 Forecasting 1) A trend is a gradual, long-term, up or down movement of demand. Answer Diff: 1 Page Ref: 682 Main Heading: Forecasting Components Key words: trend, forecasting components 2) A seasonal pattern is an up-and-down repetitive movement within a trend occurring periodically. Answer Diff: 2 Page Ref: 682 Main Heading: Forecasting Components Key words: seasonal pattern, forecasting components 3) Random variations are movements that are not predictable and follow no pattern. Answer Diff: 2 Page Ref: 682 Main Heading: Forecasting Components Key words: random variations, forecasting components 4) The basic types of forecasting methods include time series, regression, and qualitative methods. Answer Diff: 2 Page Ref: 683 Main Heading: Forecasting Components Key words: types of forecasting methods 5) Time series is a category of statistical techniques that uses historical data to predict future behavior. Answer Diff: 1 Page Ref: 683 Main Heading: Forecasting Components Key words: time series analysis 6) Regression methods attempt to develop a mathematical relationship between the item being forecast and factors that cause it to behave the way it does. Answer Diff: 2 Page Ref: 683 Main Heading: Forecasting Components Key words: regression methods 7) Qualitative methods use management judgment, expertise, and opinion...
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...Sample questions 1. Time-series forecasting models: a. | are useful whenever changes occur rapidly and wildly | b. | are more effective in making long-run forecasts than short-run forecasts | c. | are based solely on historical observations of the values of the variable being forecasted | d. | attempt to explain the underlying causal relationships which produce the observed outcome | e. | none of the above | 2. The forecasting technique which attempts to forecast short-run changes and makes use of economic indicators known as leading, coincident or lagging indicators is known as: a. | econometric technique | b. | time-series forecasting | c. | opinion polling | d. | barometric technique | e. | judgment forecasting | 3. The use of quarterly data to develop the forecasting model Yt = a +bYt1 is an example of which forecasting technique? a. | Barometric forecasting | b. | Time-series forecasting | c. | Survey and opinion | d. | Econometric methods based on an understanding of the underlying economic variables involved | e. | Input-output analysis | 4. The variation in an economic time-series which is caused by major expansions or contractions usually of greater than a year in duration is known as: a. | secular trend | b. | cyclical variation | c. | seasonal effect | d. | unpredictable random factor | e. | none of the above | 5. The type of economic indicator that can best be used for business forecasting is the: a. | leading indicator |...
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...PRODUCTION AND OPERATIONS MANAGEMENT BUS3020 COURSE CONTENT WEEK THREE TOPIC: FORECASTING • Different Methods of Forecasting – Formal and Informal, • Qualitative and Quantitative Methods • Causal methods auto projection methods of forecasting. What is forecasting? Forecasting is the art and science of predicting future events. As a science it uses historical data and projects them into the future using mathematical models. As an art it uses intuition or judgment to predict the future. Why forecast? Done to minimize uncertainty and evaluate risk relating to future events caused by dynamism of the environment within which organizations operate. Such dynamisms includes: a) Changes in legislation b) Stiff competition c) Demographic changes. Forecasting is important for planning and control of functional areas such as; marketing, finance, operations e.t.c.In the public sector, forecasts are used to plan on: Health, Education, Social services e.t.c. Types of forecasts • Demand forecasts – projections of demand for a company’s products or services. • Economic forecasts – predicts inflation rates, money supplies e.t.c • Technological forecasts.- concerned with the rate of technological progress. Forecasting Horizons a) Short – range forecasts: Covers from a few days to 6 months. It concerns issues like purchase forecasts, job scheduling, workforce levels, job assignments, production levels e.t.c. b) Medium range forecasts: Covers usually from 3 months...
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...TOPIC 1. FUNDAMENTALS OF ECONOMIC FORECASTING TOPIC I TOPIC I. FUNDAMENTALS OF ECONOMIC FORECASTING Contents 1. Meaning of forecasting 2. Features, importance and limitations of forecasting 3. Forecast types 1. Meaning of forecasting Forecast is a likely, scientifically well-grounded opinion about the possible state of the events, objects or processes in the future. Forecasting is a process of making statements about events whose actual outcomes (typically) have not yet been observed. Forecasting is a process of predicting or estimating the future based on past and present data. Economic Forecasting is a process of making forecasts based on analysis of past trends and regularities of the economic processes. Economic forecasts can be carried out at a high level of aggregation – for example for GDP, inflation, unemployment or the fiscal deficit – or at a more disaggregated level, for specific sectors of the economy or even specific companies. Economic forecasting provides information about the potential future events and their consequences for the organization. It may not reduce the complications and uncertainty of the future. However, it increases the confidence of the management to make important decisions. Economic forecasting includes the following steps: 1. Identifying items to be forecast. The items of socio-economic forecasting are the economic processes (for example, inflation, demand, supply), any indicator describing the company activity (for example...
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...how my chosen corporation American Express applies some of the forecasting techniques to better develop the company. There will also be the analysis of production plans, master production schedules, and carrying inventory and how it relates to the overall American Express budget. Along with all the above we will also compare and contrast how planning usage differentiates between a service organization such as American Express and a manufacturing organization. Lastly we will also compare and contrast the use of material requirements planning system concepts. When it comes to forecasting it is first important to determine the different types of forecasting and how they are classified. In forecasting there are four basic types which are qualitative, time series analysis, casual relationship, and simulation. The first forecasting type qualitative is "subjective or judgmental and are based on estimates and opinions", (Chase, Jacobs, & Aquilano, 2006). Some of the main characteristics of qualitative forecasting are market research which is encompassed by collecting data by surveys and interviews which help determine market hypothesis. This research is most commonly used for long range and new product sales. This would be a great description as to when American Express uses surveys to improve on new production of invoicing and reporting tools to provide to our clients. Another characteristic to qualitative forecasting is historical analogy. This is the one characteristic that would...
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...easily, such as how long a trip would last or how many people were coming. Some things, however, needed a forecast. Was it likely to rain? What would we do if it did rain? The best plans had two essential ingredients: First, everyone worked to the same plan; second, all pertinent information was included in that plan. In the business world, there are many methods of forecasting product demand, and they must include all known information. Extrinsic forecasting methods involve factors such as economic conditions, market trends, competition, government regulations, or the sale of related goods. These techniques look for patterns or correlations linking product demand with these outside factors. Qualitative forecasting techniques most often are used for extrinsic forecasting. They are employed by senior managers and involve using good judgment, intuition, and informal opinions. Qualitative forecasting is necessary for products where no previous sales data exist. Intrinsic forecasting, on the other hand, uses data from previous sales, and the forecast is developed using that sales history. This quantitative forecasting is done by most members of a supply chain, especially those near the final consumer. Many factors can be included in the forecast along with traditional methods to improve forecast reliability. Principle 2: Forecasts must include some measure of error. The forecast is going to be wrong—but by how much? Estimates of forecast error can be made by studying past performance...
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...CHAPTER SEVEN Discussion Questions 1. What role does forecasting play in the supply chain of a build-to-order manufacturer such as Dell? Although Dell builds to order, they obtain PC components in anticipation of customer orders and therefore they rely on forecasting. This forecast is used to predict future demand, which determines the quantity of each component needed to assemble a PC and the plant capacity required to perform the assembly. 2. How could Dell use collaborative forecasting with its suppliers to improve its supply chain? Collaborative forecasting requires all supply chain partners to share information regarding parameters that might affect demand, such as the timing and magnitude of promotions. Dell could share with their components suppliers all of the promotions, e.g., holiday, back-to-school, etc., they have planned. These suppliers could, in turn, notify their suppliers of discrete components that a spike in demand is anticipated. These demand forecasts for end items determine the demand for components and coupled with knowledge of fabrication times, allows all members of the supply chain to provide the right quantity at the right time to their customers. 3. What role does forecasting play in the supply chain of a mail order firm such as LL Bean? LL Bean has historically operated almost exclusively in a make-to-stock mode and with very few exceptions, stocked products that did not go out of style as rapidly as many other clothing...
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...Construction plc. 4a) A marketing model is a procedure for making marketing decisions in a scientific manner. The decision that needs to be made is whether or not to enter the rental market. When using the marketing model Wilfred Constructions’ decisions will be well thought through, therefore the idea will be more planned out and there is a decreased probability of any problems. The marketing director had previously conducted some market research about the state of the rental market by gathering data from local estate agents, the benefit of doing this is to find out about the market. I.e. Rental prices, current demand for luxury flats and suitability of locations. Further market research will be beneficial in finding out more background information. This is step 2 of the marketing model. Wilfred Construction will now be able to form hypotheses on the data they have gathered the benefit of this is that they can analyse the potential profits or losses in entering the rental market. The fourth step is to test the options, which Wilfred Constructions can do by testing the market. One way they can test the market is to produce brochures with both rental price and sales price and gauging the reaction of potential buyers or renters. With the use of brochures Wilfred’s Construction will then be able to complete step five of the model, control and review as they will get feedback from the customers as to which they prefer. 4b) Forecasting involves attempting to estimate the future...
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...The Accuracy of Demand Forecasting Between Point of Sale and Order History Supply Chain Management TBS908 Table of Contents 1. Executive Summary 4 2. Company Profile 4 3. Demand 5 3.1 Demand Forecasting 6 3.2 Demand Forecasting Methods 6 3.2.1 Opinion Polling / Qualitative Method (subjective): 6 3.2.2 Statistical Methods/Quantitative Approach (objective): 6 4. Order History Vs. Point-of-sale 8 5. Planning Promotions 8 5.1 Promotion Planning and Supply Chain Contracting in a High-Low Pricing Environment 9 5.1.1 Basic Household Inventory Model: 9 6. Types of demand forecast in GCC and UAE 10 7. Objective 10 8. Methodology 11 Table 3 13 Figure 1 13 9. Result 14 10. Recommendations 14 11. Conclusion: 15 11. References 16 12. Appendixes 17 Appendix I 17 Appendix II 19 1. Executive Summary Demand forecasting is essentially anticipating future prospects by reviewing historical data in the most calculated way in an uncontrollable environment. Foreseeing what and when buyers will purchase has never been a simple procedure for producers or retailers. Troubled by the overwhelming undertaking of correctly coordinating supply with interest, makers are always enhancing procedures to accomplish the most noteworthy estimate exactness that will guarantee when the customer enters a store, the item they are searching for is on the rack. This is getting significantly tricky as the uncertainty level increase. In the below report the demand...
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...NOVA SOUTHEASTERN UNIVERSITY The Wayne Huizenga Graduate School of Business and Entrepreneurship-Master's ProgramS Assignment for Course: QNT 5040- Business Modeling Submitted to: Dr. Tom Griffin Submitted by: Prince A. Storr ps44@nova.edu Date of Course Meeting: November 18, 2011 Date of Submission: November 18, 2011 Title of Assignment: Greaves Brewery: 10 Month Forecasting CERTIFICATION OF AUTHORSHIP: I certify that I am the author of this paper and any assistance that I received in its preparation is fully acknowledged and disclosed in the paper. I have also cited any sources from which I used data, ideas, or words, either quoted directly or paraphrased. I also certify that this paper was prepared by me specifically for this course. Student Signature: Prince A Storr Instructor(s Grade on Assignment: Instructor(s Comments: Greaves Brewery: Ten Month Sales Forecasting Case Synopsis Alex Benson, purchasing manager for Greaves Brewery in Trinidad was faced with a dilemma in early 2004. He encountered difficulty in forecasting sales for 2004; particularly because of the 2003 slump, government excise taxes and other factors such as decreased numbers in both tourist arrivals to the Caribbean island and beer exports to the U.S. As purchasing manager, Benson’s prime responsibility was maintaining adequate inventory levels for all goods and materials used in the company’s production processes, including the purchase of new bottles and...
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