Ipad’s Integrated Marketing Communications Report

Table of Contents Introduction1 Apple’s Integrated Marketing Communications Programme for iPad. 2 Brand Positioning2 Target Audience3 Target market and segments4 Evaluation of the products’ Integrated Marketing Communications plan:4 Conclusion7 Recommendations7 Bibliography8 Introduction This report will discuss Apple’s Integrated Marketing Communications (IMC) Programme for their iPad product and how this is coordinated to communicate the iPad’s product positioning strategy.Apple’s iPad is a tablet computer adding a new genre to their mobile devices. The report will discuss the brand positioning and any recommendations for future IMC planning. Apple’s corporate headquarters are based in California in the US in the heart of the Hi-tech industry. They are global in terms of computer electronic consumable sales. Apple position themselves as a top of the range brand with pioneering innovations and consumer needs and wants in mind.Steve Jobs, for mer co-founder, chairman and CEO of Apple Inc. , made a compelling positioning statement during his introduction of the iPad at a conference in January 2010, he stated that the iPad is â€Å"so much more intimate than a laptop, and it’s so much more capable than a smartphone with its gorgeous screen† (STONE, 2010). Apple is committed to remaining in the forefront of innovation and quality, and therefore will sustain their competitive advantage in a rapidly evolving market.This report will also highlight the importance of media for Apple’s brand and how Apple have used this to reach its’ target audience and increase brand awareness. It will also question if Apple is focusing on the Marketing Communications Mix or are they relying more on the desire of the ‘brand’? The theory behind IMC is to use all aspects of marketing communication such as Advertising, Public Relations, Direct marketing and Personal selling to attain and sustain long-term cu stomer relationships while strengthening brand awareness and increasing profits.Apple’s use and effectiveness of the IMC campaign and their success from it will be discussed further in this report along with what message Apple are trying to deliver in their advertising of the iPad. Apple’s Integrated Marketing Communications Programme for iPad. The Apple brand is instantly recognisable throughout the world due to the company’s positioning strategy of their product line by way of product features, quality and ease of use to name a few. Their leadership in innovation gives the brand competitive advantage and this has fed the want and desire for the brand by consumers.Therefore the iPad having the Apple brand already created a certain am The Apple brand is instantly recognisable throughout the world due to the company’s positioning strategy of their product line by way of product features, quality and ease of use to name a few. Their leadership in innovation gives the brand competitive advantage and this has fed the want and desire for the brand by consumers. Therefore the iPad having the Apple brand already created a certain am Apple is no different to most organisations for using promotional and advertising tools to gain customers’ interest and the desire for their products.However, their marketing on innovation and design of the iPad also catches the attention of new potential consumers. To many the technology was not totally new, but the concept was and Apple focussed on that. Previous products from Apple put their brand in the limelight and made any new product launch a much anticipated one. amount of reputation, awareness and prominence in the marketplace before it was even launched. So how is Apple’s Integrated Marketing Communications organised to communicate the iPad’s positioning strategy? Firstly, we should look at the brand positioning and how the iPad fits in.Brand Positioning Brands and the management of brands have become very important elements of culture and the economy. A brand can increase the product's perceived value and therefore brand management and the marketing techniques used are seen as vital to increase brand equity and the positioning of their products. Marketers see a brand as an implied promise of the level of quality consumers have come to expect from the brands’ products and that future products will meet those expectations. Apple is seen as an ‘iconic brand that delivers revolutionary, beautifully designed and incredibly profitable products. (Daye, 2012). The ‘Apple’ brand is in fact Number 1 in brand value according to Forbes, saying it is worth $87. 1 billion, up 52% from two years ago (Forbes, 2012). The master of the Apple brand was Steve Jobs who was an excellent brand marketer and core to what Apple is today. He saw the future for Apple which was going beyond computers, therefore his first step was to remove the word ‘Com puter’ from their logo. Doing this allowed the company to diversify and expand into the world of mobile devices and more. Doing this allowed the company to diversify and expand into the world of mobile devices and more.Just as the products are very important for competitiveness, the brand is too, and the Apple brand certainly has succeeded in building up a very valuable good: an instantly recognizable and universally respected brand. This makes it easier to promote and sell the iPad. In fact, some brands over time become cult brands: consumers become passionate about the brand and levels of loyalty go beyond reason (Roberts, 2004) and Apple has become a cult brand in some respects. As mentioned in Steve Jobs’ compelling positioning statement in the introduction, he made two important statements about the product.They were that the iPad was between two already highly successful mobile devices, the laptop and the smartphone, and very importantly that the iPad had competi tive advantages over each. Apple brand followers were instantly excited and could not wait for the release of the iPad so they could be the first to have it, whether they needed such a device or not! The iPad was a game-changer in the tech world when released in April of 2010 and some believe it may end the personal computer era such is the strength of the brand. Target AudienceThe iPad’s target audience is not as clear as one would think, it turns out that it is very broad. The initial thought on the iPad by the media was that it was just a big iPhone that could not be used for regular phone calls, so who would want something like that? Apple believed, like for the iPod, that the iPad was for everyone. They got this perception when a year after the iPod was released many consumers still believed the device was for ‘techies and celebrities’. The task, therefore, was to use communications to inform world audiences that the iPod (and now the iPad) was for everyone, not just a select few (Fill, 2009).The fact that many features and programs on the iPad were inherited from the iPod and iPhone it meant that users would be familiar with the devices’ capabilities and have the advantage of mobile computing too. The iPad had the potential to target music lovers of all ages and denominations, it was a learning tool for both students and professionals with the addition of thousands of applications (apps) available. The variety of apps could attract consumers who love to read, share photographs, stay in touch through forms of email, forums, virtual meetings, social media and Apples’ ‘Facetime’ to name a few.This made the iPads’ audience vast and diverse. Target market and segments Segmentation is necessary because a single product is unlikely to meet the needs of all customers in a mass market (Fill, 2009). This should be the case for most products, however the iPad is satisfying many needs and desires. For example, du e to the variety of applications available, the iPad becomes an educational tool, a recreational tool, a business tool and a communication tool, all of which the iPad was designed for. It is clear the device is equally good for home use as well as business for both genders.But the competitiveness of the product is strengthened by Apple’s award winning dedicated music store, iTunes, which delivers seamless downloading of not just music, but books and movies too, which widens the target market and covers several market segments. The need to communicate through channels such as social media, example is Facebook, and websites specifically designed for mobile devices such as iVillage for women, make the iPad a very attractive device as it is stylish, light weight and now trendy to own one.Consumers of all ages and backgrounds can potentially own one as the price of the base model is relatively acceptable in terms of technical devices is concerned. Because of the potential to incre ase productivity businesses are scrambling to purchase the iPad, students and colleges want them, and they are seen being used by news broadcasters and presenters not to mention government representatives. Apple do not appear to target markets like other companies do, they tend to target people.They use elements of IMC and AIDA (Attention, Interest, Desire, and Action) to achieve and maintain customer loyalty and increase brand awareness. They managed to present complex technology in an easy, user friendly and fun way, a key to their success in many markets. Evaluation of the products’ Integrated Marketing Communications plan: Apple continued on the successes of previous products when launching their iPad product, using images and reminders of what those previous products have done for the world. Their marketing communications for the iPad very much focused on what the company has done and what they are best at.In the keynote presentation of the iPad, the company reminded us that in October 2001, Apple revolutionised the way people listen to music with the iPod, in April 2003 Apple revolutionised the way people buy music, videos and games with iTunes. In October 2007, they revolutionised the world of mobile communications with the iPhone, and now with the iPad, Apple will ‘revolutionise’ the world again. Steve Jobs’ enthusiastic description of the device during his Keynote in January 2010 makes the individual user feel that it was made for them, that they will â€Å"hold the internet in their hands and it is an incredible experience. Steve Jobs on many occasions has stated that he loves Apple products and their customers. This shows in the customer support Apple has invested in. The company internally is well briefed on how Apple wants to be perceived, again this shows in how secrecy shrouds products prior to their launch. Their communication mix is very much audience focused and always consistent. The message for iPad is clear, it is a device for the individual who could personalise it and bring it anywhere. Apples’ marketing objectives were quite simple for the iPad.Their approach has always been the same, but different to other organisations, their introduction was somewhat spectacular due to the fact that products prior to launch were always successfully kept a secret. This made Apple brand fans excited and other consumers intrigued. Apples’ marketing strategy is â€Å"It’s better to be simple† and it shows in their marketing communications as they keep their advertising minimalistic and product information in simple language. The main forms they use are social media, online advertising, presentation keynotes and sometimes viral marketing!Either way, the message is clear and simple; the product is exciting, fun and easy to use. This is unusual, as traditionally, technical products were always described by their systems’ statistics and technical terminology which the avera ge consumer does not understand. Brand awareness is increased because of the hype. The communication mix or marketing mix involves the implementation of a marketing plan consisting of: i) Promotion, ii) Product, iii) Price and iv) Place. The Apple brand is an incredibly strong brand hence ‘Promotion’ is mentioned first.Apple, surprisingly, do not spend as much on advertising as one would think. Media such as television and magazines are their main choice but what Apple did and did best were product launch press releases. As mentioned before, keynote presentations were what Apples’ former CEO was extraordinary at. And people who mattered most to promote and place the new product in the media through public relations press releases, were present at these presentations. Secrecy of a product generated interest and added to that the Apple brand which created hype, resulted in enthusiastic anticipation of the iPad launch.Commercials were simplistic but visually pleasin g and this enhanced the beauty and simplicity of the design and features of the iPad, exactly what Steve Jobs himself loved about Apple products. This is also mirrored in their shop designs featuring simple but sophisticated look just displaying the Apple products promoting their features. More recently, the iPad has been placed in most good computer electronic stores around the world and of course Apples’ own e-commerce website. It is now as easy to purchase the iPad as it is to buy shoes.The iPad, like other Apple products, is designed and manufactured to the highest standards as always maintained by the former CEO Steve Jobs. The Product is probably Apples’ most important ‘P’ in the communication mix as they believe they have the most a product can offer. â€Å"Apple is committed to bringing the best personal computing experience to students, educators, creative professionals and consumers around the world through its innovative hardware, software and Internet offerings. † (Apple, 2004). The products and the brand will push the other ‘Ps’ of the mix for Apple.Price was not as important for Apple as their products. With their iPad they have competitive advantage with innovation, they also have control with materials, such as touch screens and flash memory to keep costs down over their competitors. Most electronic goods’ prices generally fall as the product nears the end of its PLC, (Product Life Cycle). Not so much with Apple products. Apple manages to get people hooked on their products from an early age. The iPad, like other Apple mobile devices, are very easy and fun to use and have the capability of adapting to the user by means of applications and personalisation.Therefore, as the user grows older the device can contain more ‘mature’ applications. For example, games and early learning apps can entertain children while music and movies are a must for adolescences, and productivity and new s may be important for adults. Today we cannot live without social networking and weather information! This is a very clever way of reaching a varied target audience that is not confined to gender, demographics, interests, or even age and Apple use ‘apps’ to promote the iPad.The effectiveness of the IMC campaign is hard to measure for the iPad as an individual Apple product, as much of the interest is down to the loyalty of the brand also. Critics will always point to the negatives, but there is without doubt, evidence to show the iPad is a huge success. Promoting the iPad to young users, for example, in schools and colleges and images of celebrities and peers using them means it generates the desire to own one. Apple can also lock the consumer into the brand by linking their products and services so that they continue to use the brand through life.Conclusion Their advertising and in-store presentation of the iPad gives the product a prestigious image, but the ability t o allow the consumer to try it or ‘play’ with it in their stores shows the confidence the company has for their products’ capabilities and quality, and that is what consumers inevitably pick up on. For effective marketing there needs to be effective communication of the information of the product. Apple does it well, but they do it simply and that seems to work. The desire they have generated for the consumer to want a fun and productive device is unquenchable.Apple may not follow all the rules of Integrated Marketing Communications, but they are careful in the planning of a product entry into the market. Secrecy, hype, presentations and image are key to their success it seems and the Apple brand remains powerful and resilient. Recommendations Apple as a company must be transparent to remain credible and sustainable in today’s business climate. This will also aid in the expansion into emerging markets. The success of the iPad has been a cornerstone for the company roven by sales of nearly 40 million iPads at the end of 2011, according to Forbes, and they expect 73 million in sales by the end of 2012. This can be over confident and risky as they lack new innovation since the iPad 2 launch. To continue growth into 2013 Apple’s marketing strategy will need to focus on brand positioning, promotion, customer service and estimate a competitive price of iPad with additional features linking to research and analysis of the environmental forces to compete in the global market. A continual S. W. O. T. analysis would benefit to understand the company’s position.Promotion development and strategies can be extremely effective if Apple continues to focus on its strategic human resource management and by making consistent attempts to remodel its marketing plan to continue successfully. Bibliography Apple, 2004. Apple Press Info. [Online] Available at: http://www. apple. com/pr/library/2004/01/08HP-and-Apple-Partner-to-Deliver-Digital- Music-Player-and-iTunes-to-HP-Customers. html [Accessed 27th March 2013]. Daye, D. , 2012. Weakness In The Apple Brand?. [Online] Available at: http://www. brandingstrategyinsider. com/2012/12/crunch-time-for-the-apple-brand. html#. US860jAqyCl [Accessed 28th Feb 2013].Fill, C. , 2009. Marketing Communications. Fifth Edition ed. Harlow: Pearson Education Limited. Forbes, 2012. Apple Tops List Of The World's Most Powerful Brands. [Online] Available at: http://www. forbes. com/sites/kurtbadenhausen/2012/10/02/apple-tops-list-of-the-worlds-most-powerful-brands/ [Accessed 24th March 2013]. Roberts, K. , 2004. The Future Beyond Brands: Lovemarks. New York: Powerhouse Books. STONE, B. , 2010. New York Times. Inside Technology. [Online] Available at: http://www. nytimes. com/2010/01/28/technology/companies/28apple. html? _r=0 [Accessed 12 Feb 2013]. ——————————————–

Om Heizer Om10 Ism 04

Chapter FORECASTING Discussion Questions 1.? Qualitative models incorporate subjective factors into the forecasting model. Qualitative models are useful when subjective factors are important. When quantitative data are difficult to obtain, qualitative models may be appropriate. 2.? Approaches are qualitative and quantitative. Qualitative is relatively subjective; quantitative uses numeric models. 3.? Short-range (under 3 months), medium-range (3 months to 3 years), and long-range (over 3 years). 4.? The steps that should be used to develop a forecasting system are: (a)?Determine the purpose and use of the forecast (b)? Select the item or quantities that are to be forecasted (c)? Determine the time horizon of the forecast (d)? Select the type of forecasting model to be used (e)? Gather the necessary data (f)? Validate the forecasting model (g)? Make the forecast (h)? Implement and evaluate the results 5.? Any three of: sales planning, production planning and budgeting, cash budgeting, analyzing various operating plans. 6.? There is no mechanism for growth in these models; they are built exclusively from historical demand values. Such methods will always lag trends. .? Exponential smoothing is a weighted moving average where all previous values are weighted with a set of weights that decline exponentially. 8.? MAD, MSE, and MAPE are common measures of forecast accuracy. To find the more accurate forecasting model, forecast with each tool for several periods where the demand outcome is known, and calculate MSE, MAPE, or MAD for each. The smaller error indicates the better forecast. 9.? The Delphi technique involves: (a)? Assembling a group of experts in such a manner as to preclude direct communication between identifiable members of the group (b)?Assembling the responses of each expert to the questions or problems of interest (c)? Summarizing these responses (d)? Providing each expert with the summary of all responses (e)? Asking each expert to study the summary of the responses and respond again to the questions or problems of interest. (f)? Repeating steps (b) through (e) several times as necessary to obtain convergence in responses. If convergence has not been obtained by the end of the fourth cycle, the responses at that time should probably be accepted and the process terminated—little additional convergence is likely if the process is continued. 0.? A time series model predicts on the basis of the assumption that the future is a function of the past, whereas an associative model incorporates into the model the variables of factors that might influence the quantity being forecast. 11.? A time series is a sequence of evenly spaced data points with the four components of trend, seasonality, cyclical, and random variation. 12.? When the smoothing constant, (, is large (close to 1. 0), more weight is given to recent data; when ( is low (close to 0. 0), more weight is given to past data. 13.? Seasonal patterns are of fixed duration a nd repeat regularly.Cycles vary in length and regularity. Seasonal indices allow â€Å"generic† forecasts to be made specific to the month, week, etc. , of the application. 14.? Exponential smoothing weighs all previous values with a set of weights that decline exponentially. It can place a full weight on the most recent period (with an alpha of 1. 0). This, in effect, is the naive approach, which places all its emphasis on last period’s actual demand. 15.? Adaptive forecasting refers to computer monitoring of tracking signals and self-adjustment if a signal passes its present limit. 16.?Tracking signals alert the user of a forecasting tool to periods in which the forecast was in significant error. 17.? The correlation coefficient measures the degree to which the independent and dependent variables move together. A negative value would mean that as X increases, Y tends to fall. The variables move together, but move in opposite directions. 18.? Independent variable (x) is said to explain variations in the dependent variable (y). 19.? Nearly every industry has seasonality. The seasonality must be filtered out for good medium-range planning (of production and inventory) and performance evaluation. 20.? There are many examples.Demand for raw materials and component parts such as steel or tires is a function of demand for goods such as automobiles. 21.? Obviously, as we go farther into the future, it becomes more difficult to make forecasts, and we must diminish our reliance on the forecasts. Ethical Dilemma This exercise, derived from an actual situation, deals as much with ethics as with forecasting. Here are a few points to consider:  ¦ No one likes a system they don’t understand, and most college presidents would feel uncomfortable with this one. It does offer the advantage of depoliticizing the funds al- location if used wisely and fairly.But to do so means all parties must have input to the process (such as smoothing constants) and all data need to be open to everyone.  ¦ The smoothing constants could be selected by an agreed-upon criteria (such as lowest MAD) or could be based on input from experts on the board as well as the college.  ¦ Abuse of the system is tied to assigning alphas based on what results they yield, rather than what alphas make the most sense.  ¦ Regression is open to abuse as well. Models can use many years of data yielding one result or few years yielding a totally different forecast.Selection of associative variables can have a major impact on results as well. Active Model Exercises* ACTIVE MODEL 4. 1: Moving Averages 1.? What does the graph look like when n = 1? The forecast graph mirrors the data graph but one period later. 2.? What happens to the graph as the number of periods in the moving average increases? The forecast graph becomes shorter and smoother. 3.? What value for n minimizes the MAD for this data? n = 1 (a naive forecast) ACTIVE MODEL 4. 2: Exponential Smoothing 1.? Wha t happens to the graph when alpha equals zero? The graph is a straight line.The forecast is the same in each period. 2.? What happens to the graph when alpha equals one? The forecast follows the same pattern as the demand (except for the first forecast) but is offset by one period. This is a naive forecast. 3.? Generalize what happens to a forecast as alpha increases. As alpha increases the forecast is more sensitive to changes in demand. *Active Models 4. 1, 4. 2, 4. 3, and 4. 4 appear on our Web site, www. pearsonhighered. com/heizer. 4.? At what level of alpha is the mean absolute deviation (MAD) minimized? alpha = . 16 ACTIVE MODEL 4. 3: Exponential Smoothing with Trend Adjustment .? Scroll through different values for alpha and beta. Which smoothing constant appears to have the greater effect on the graph? alpha 2.? With beta set to zero, find the best alpha and observe the MAD. Now find the best beta. Observe the MAD. Does the addition of a trend improve the forecast? alpha = . 11, MAD = 2. 59; beta above . 6 changes the MAD (by a little) to 2. 54. ACTIVE MODEL 4. 4: Trend Projections 1.? What is the annual trend in the data? 10. 54 2.? Use the scrollbars for the slope and intercept to determine the values that minimize the MAD. Are these the same values that regression yields?No, they are not the same values. For example, an intercept of 57. 81 with a slope of 9. 44 yields a MAD of 7. 17. End-of-Chapter Problems [pic] (b) | | |Weighted | |Week of |Pints Used |Moving Average | |August 31 |360 | | |September 7 |389 |381 ( . 1 = ? 38. 1 | |September 14 |410 |368 ( . 3 = 110. 4 | |September 21 |381 |374 ( . 6 = 224. 4 | |September 28 |368 |372. | |October 5 |374 | | | |Forecast 372. 9 | | (c) | | | |Forecasting | Error | | |Week of |Pints |Forecast |Error |( . 20 |Forecast| |August 31 |360 |360 |0 |0 |360 | |September 7 |389 |360 |29 |5. 8 |365. 8 | |September 14 |410 |365. 8 |44. 2 |8. 84 |374. 64 | |September 21 |381 |374. 64 |6. 36 |1. 272 |375. 12 | |Se ptember 28 |368 |375. 912 |–7. 912 |–1. 5824 |374. 3296| |October 5 |374 |374. 3296 |–. 3296 |–. 06592 |374. 2636| The forecast is 374. 26. (d)? The three-year moving average appears to give better results. [pic] [pic] Naive tracks the ups and downs best but lags the data by one period. Exponential smoothing is probably better because it smoothes the data and does not have as much variation. TEACHING NOTE: Notice how well exponential smoothing forecasts the naive. [pic] (c)? The banking industry has a great deal of seasonality in its processing requirements [pic] b) | | |Two-Year | | | |Year |Mileage |Moving Average |Error ||Error| | |1 |3,000 | | | | | |2 |4,000 | | | | | |3 |3,400 |3,500 |–100 | |100 | |4 |3,800 |3,700 |100 | |100 | |5 |3,700 |3,600 |100 | |100 | | | |Totals| |100 | | |300 | | [pic] 4. 5? (c)? Weighted 2 year M. A. ith . 6 weight for most recent year. |Year |Mileage |Forecast |Error ||Error| | |1 |3,000 | | | | |2 |4,000 | | | | |3 |3,400 |3,600 |–200 |200 | |4 |3,800 |3,640 |160 |160 | |5 |3,700 |3,640 |60 |60 | | | | | | | 420 | | Forecast for year 6 is 3,740 miles. [pic] 4. 5? (d) | | |Forecast |Error ( |New | |Year |Mileage |Forecast |Error |( = . 50 |Forecast | |1 |3,000 |3,000 | ?0 | 0 |3,000 | |2 |4,000 |3,000 |1,000 |500 |3,500 | |3 |3,400 |3,500 | –100 |–50 |3,450 | |4 |3,800 |3,450 | 350 |175 |3,625 | |5 |3,700 |3,625 | 75 |? 38 |3,663 | | | |Total |1,325| | | | The forecast is 3,663 miles. 4. 6 |Y Sales |X Period |X2 |XY | |January |20 |1 |1 |20 | |February |21 |2 |4 |42 | |March |15 |3 |9 |45 | |April |14 |4 |16 |56 | |May |13 |5 |25 |65 | |June |16 |6 |36 |96 | |July |17 |7 |49 |119 | |August |18 |8 |64 |144 | |September |20 |9 |81 |180 | |October |20 |10 |100 |200 | |November |21 |11 |121 |231 | |December |23 |12 |144 |276 | |Sum | 18 |78 |650 |1,474 | |Average |? 18. 2 | 6. 5 | | | (a) [pic] (b)? [i]? NaiveThe coming January = December = 23 [ii]? 3-month moving (20 + 21 + 23)/3 = 21. 33 [iii]? 6-month weighted [(0. 1 ( 17) + (. 1 ( 18) + (0. 1 ( 20) + (0. 2 ( 20) + (0. 2 ( 21) + (0. 3 ( 23)]/1. 0 = 20. 6 [iv]? Exponential smoothing with alpha = 0. 3 [pic] [v]? Trend? [pic] [pic] Forecast = 15. 73? +?. 38(13) = 20. 67, where next January is the 13th month. (c)? Only trend provides an equation that can extend beyond one month 4. 7? Present = Period (week) 6. a) So: where [pic] )If the weights are 20, 15, 15, and 10, there will be no change in the forecast because these are the same relative weights as in part (a), i. e. , 20/60, 15/60, 15/60, and 10/60. c)If the weights are 0. 4, 0. 3, 0. 2, and 0. 1, then the forecast becomes 56. 3, or 56 patients. [pic] [pic] |Temperature |2 day M. A. | |Error||(Error)2| Absolute |% Error | |93 |— | — |— |— | |94 |— | — |— |— | |93 |93. 5 | 0. 5 |? 0. 25| 100(. 5/93) | = 0. 54% | |95 |93. 5 | 1. 5 | ? 2. 25| 100(1. 5/95) | = 1. 58% | |96 |94. 0 | 2. 0 |? 4. 0 0| 100(2/96) | = 2. 08% | |88 |95. 5 | 7. | 56. 25| 100(7. 5/88) | = 8. 52% | |90 |92. 0 | 2. 0 |? 4. 00| 100(2/90) | = 2. 22% | | | | |13. 5| | | 66. 75 | | |14. 94% | MAD = 13. 5/5 = 2. 7 (d)? MSE = 66. 75/5 = 13. 35 (e)? MAPE = 14. 94%/5 = 2. 99% 4. 9? (a, b) The computations for both the two- and three-month averages appear in the table; the results appear in the figure below. [pic] (c)? MAD (two-month moving average) = . 750/10 = . 075 MAD (three-month moving average) = . 793/9 = . 088 Therefore, the two-month moving average seems to have performed better. [pic] (c)? The forecasts are about the same. [pic] 4. 12? t |Day |Actual |Forecast | | | | |Demand |Demand | | |1 |Monday |88 |88 | | |2 |Tuesday |72 |88 | | |3 |Wednesday |68 |84 | | |4 |Thursday |48 |80 | | |5 |Friday | |72 |( Answer | Ft = Ft–1 + ((At–1 – Ft–1) Let ( = . 25. Let Monday forecast demand = 88 F2 = 88 + . 25(88 – 88) = 88 + 0 = 88 F3 = 88 + . 25(72 – 88) = 88 – 4 = 84 F4 = 84 + . 25(68 – 84) = 84 – 4 = 80 F5 = 80 + . 25(48 – 80) = 80 – 8 = 72 4. 13? (a)? Exponential smoothing, ( = 0. 6: | | |Exponential |Absolute | |Year |Demand |Smoothing ( = 0. |Deviation | |1 |45 |41 |4. 0 | |2 |50 |41. 0 + 0. 6(45–41) = 43. 4 |6. 6 | |3 |52 |43. 4 + 0. 6(50–43. 4) = 47. 4 |4. 6 | |4 |56 |47. 4 + 0. 6(52–47. 4) = 50. 2 |5. 8 | |5 |58 |50. 2 + 0. 6(56–50. 2) = 53. 7 |4. 3 | |6 |? |53. 7 + 0. 6(58–53. 7) = 56. 3 | | ( = 25. 3 MAD = 5. 06 Exponential smoothing, ( = 0. 9: | | |Exponential |Absolute | |Year |Demand |Smoothing ( = 0. |Deviation | |1 |45 |41 |4. 0 | |2 |50 |41. 0 + 0. 9(45–41) = 44. 6 |5. 4 | |3 |52 |44. 6 + 0. 9(50–44. 6 ) = 49. 5 |2. 5 | |4 |56 |49. 5 + 0. 9(52–49. 5) = 51. 8 |4. 2 | |5 |58 |51. 8 + 0. 9(56–51. 8) = 55. 6 |2. 4 | |6 |? |55. 6 + 0. 9(58–55. 6) = 57. 8 | | ( = 18. 5 MAD = 3. 7 (b)? 3-year moving average: | | |Three-Year |Absolute | |Year |Demand |Moving Average |Deviation | |1 45 | | | |2 |50 | | | |3 |52 | | | |4 |56 |(45 + 50 + 52)/3 = 49 |7 | |5 |58 | (50 + 52 + 56)/3 = 52. 7 |5. 3 | |6 |? | (52 + 56 + 58)/3 = 55. 3 | | ( = 12. 3 MAD = 6. 2 (c)? Trend projection: | | | |Absolute | |Year |Demand |Trend Projection |Deviation | |1 |45 |42. 6 + 3. 2 ( 1 = 45. 8 |0. 8 | |2 |50 |42. 6 + 3. 2 ( 2 = 49. 0 |1. 0 | |3 |52 |42. 6 + 3. 2 ( 3 = 52. 2 |0. 2 | |4 |56 |42. 6 + 3. 2 ( 4 = 55. 4 |0. | |5 |58 |42. 6 + 3. 2 ( 5 = 58. 6 |0. 6 | |6 |? |42. 6 + 3. 2 ( 6 = 61. 8 | | ( = 3. 2 MAD = 0. 64 [pic] | X |Y |XY |X2 | | 1 |45 | 45 | 1 | | 2 |50 |100 | 4 | | 3 |52 |156 | 9 | | 4 |56 |224 |16 | | 5 |58 |290 |25 | Then: (X = 15, (Y = 261, (XY = 815, (X2 = 55, [pic]= 3, [pic]= 52. 2 Therefore: [pic] (d)? Comparing the results of the forecasting methodologies for parts (a), (b), and (c). |Forecast Methodology |MAD | |Exponential smoothing, ( = 0. |5. 06 | |Exponential smoothing, ( = 0. 9 |3. 7 | |3-year moving average |6. 2 | |Trend projection |0. 64 | Based on a mean absolute deviation criterion, the trend projection is to be preferred over the exponential smoothing with ( = 0. 6, exponential smoothing with ( = 0. 9, or the 3-year moving average forecast methodologies. 4. 14 Method 1:MAD: (0. 20 + 0. 05 + 0. 05 + 0. 20)/4 = . 125 ( better MSE : (0. 04 + 0. 0025 + 0. 0025 + 0. 04)/4 = . 021 Method 2:MAD: (0. 1 + 0. 20 + 0. 10 + 0. 11) / 4 = . 1275 MSE : (0. 01 + 0. 04 + 0. 01 + 0. 0121) / 4 = . 018 ( better 4. 15 | |Forecast Three-Year |Absolute | |Year |Sales |Moving Average |Deviation | |2005 |450 | | | |2006 |495 | | | |2007 |518 | | | |2008 |563 |(450 + 495 + 518)/3 = 487. 7 |75. 3 | |2009 |584 |(495 + 518 + 563)/3 = 525. 3 |58. 7 | |2010 | |(518 + 563 + 584)/3 = 555. 0 | | | | | ( = 134 | | | | MAD = 67 | 4. 16 Year |Time Period X |Sales Y |X2 |XY | |2005 |1 |450 | 1 |450 | |2006 |2 |495 | 4 |990 | |2007 |3 |518 | 9 |1554 | |2008 |4 |563 |16 |2252 | |2009 |5 |584 |25 |2920 | | | | ( = 2610| |( = 55 | |( = 8166 | [pic] [pic] |Year |Sales |Forecast Trend |Absolute Deviation | |2005 |450 |454. 8 |4. 8 | |2006 |495 |488. 4 |6. | |2007 |518 |522. 0 |4. 0 | |2008 |563 |555. 6 |7. 4 | |2009 |584 |589. 2 |5. 2 | |2010 | |622. 8 | | | | | | ( = 28 | | | | | MAD = 5. 6 | 4. 17 | | |Forecast Exponential |Absolute | |Year |Sales |Smoothing ( = 0. 6 |Deviation | |2005 |450 |410. 0 |40. | |2006 |495 |410 + 0. 6(450 – 410) = 434. 0 |61. 0 | |2007 |518 |434 + 0. 6(495 – 434) = 470. 6 |47. 4 | |2008 |563 |470. 6 + 0. 6(518 – 470. 6) = 499. 0 |64. 0 | |2009 |584 |499 + 0. 6(563 – 499) = 537. 4 |46. 6 | |2010 | |537. 4 + 0. 6(584 – 537. 4) = 565. 6 | | | | | ( = 259 | | | | MAD = 51. 8 | | | |Forecast Exponential |Absolute | |Year |Sales |Smoothing ( = 0. |Deviation | |2005 |450 |410. 0 |40. 0 | |2006 |495 |410 + 0. 9(450 – 410) = 446. 0 |49. 0 | |2007 |518 |446 + 0. 9(495 – 446) = 490. 1 |27. 9 | |2008 |563 |490. 1 + 0. 9(518 – 490. 1) = 515. 2 |47. 8 | |2009 |584 |515. 2 + 0. 9(563 – 515. 2) = 558. 2 |25. 8 | |2010 | |558. 2 + 0. 9(584 – 558. 2) = 581. 4 | | | | |( = 190. 5 | | | |MAD = 38. 1 | (Refer to Solved Problem 4. 1)For ( = 0. 3, absolute deviations for 2005–2009 are 40. 0, 73. 0, 74. 1, 96. 9, 88. 8, respectively. So the MAD = 372. 8/5 = 74. 6. [pic] Because it gives the lowest MAD, the smoothing constant of ( = 0. 9 gives the most accurate forecast. 4. 18? We need to find the smoothing constant (. We know in general that Ft = Ft–1 + ((At–1 – Ft–1); t = 2, 3, 4. Choose either t = 3 or t = 4 (t = 2 won’t let us find ( because F2 = 50 = 50 + ((50 – 50) holds for any (). Let’s pick t = 3. Then F3 = 48 = 50 + ((42 – 50) or 48 = 50 + 42( – 50( or –2 = –8( So, . 25 = ( Now we can find F5 : F5 = 50 + ((46 – 50)F5 = 50 + 46( – 50( = 50 – 4( For ( = . 25, F5 = 50 – 4(. 25) = 49 The forecast for time period 5 = 49 units. 4. 19? Trend adjusted exponential smoothing: ( = 0. 1, ( = 0. 2 | | |Unadjusted | |Adjusted | | | |Month |Income |Forecast |Trend |Forecast ||Error||Error2 | |February |70. 0 | 65. 0 | 0. 0 | 65 |? 5. 0 |? 25. 0 | |March |68. 5 | 65. 5 | 0. 1 | 65. 6 |? 2. 9 |? 8. 4 | |April |64. 8 | 65. 9 | 0. 16 |66. 05 |? 1. 2 |? 1. 6 | |May |71. 7 | 65. 92 | 0. 13 |66. 06 |? 5. 6 |? 31. 9 | |June |71. | 66. 62 | 0. 25 |66. 87 |? 4. 4 |? 19. 7 | |July |72. 8 | 67. 31 | 0. 33 |67. 64 |? 5. 2 |? 26. 6 | |August | | 68. 16 | |68. 60 | |24. 3| | |113. 2| | MAD = 24. 3/6 = 4. 05, MSE = 113. 2/6 = 18. 87. Note that all numbers are rounded. Note: To use POM for Windows to solve this problem, a period 0, which contains the initial forecast and initial trend, must be added. 4. 20? Trend adjusted exponential smoothing: ( = 0. 1, ( = 0. 8 [pic] [pic] [pic] [pic] [pic] [pic] [pic] [pic] [pic] [pic] [pic] [pic] 4. 23? Students must determine the naive forecast for the four months .The naive forecast for March is the February actual of 83, etc. |(a) | |Actual |Forecast ||Error| ||% Error| | | |March |101 |120 |19 |100 (19/101) = 18. 81% | | |April |? 96 |114 |18 |100 (18/96) ? = 18. 75% | | |May |? 89 |110 |21 |100 (21/89) ? = 23. 60% | | |June |108 |108 |? 0 |100 (0/108) ? = 0% | | | | | | |58 | | | 61. 16% | [pic] |(b)| |Actual |Naive ||Error| ||% Error| | | |March |101 |? 83 |18 |100 (18/101) = 17. 82% | | |April |? 96 |101 |? |100 (5/96) ? = 5. 21% | | |May |? 89 |? 96 |? 7 |100 (7/89) ? =? 7. 87% | | |June |108 |? 89 |19 |100 (19/108) = 17. 59% | | | | | | |49| | |48. 49% | | [pic] Naive outperforms management. (c)? MAD for the manager’s technique is 14. 5, while MAD for the naive forecast is only 12. 25. MAPEs are 15. 29% and 12. 12%, respectively. So the naive method is better. 4. 24? (a)? Graph of demand The observations obviously do not form a straight line but do tend to cluster about a straight line over the range shown. (b)? Least-squares regression: [pic] Assume Appearances X |Demand Y |X2 |Y2 |XY | |3 | 3 | 9 | 9 | 9 | |4 | 6 |16 | 36 |24 | |7 | 7 |49 | 49 |49 | |6 | 5 |36 | 25 |30 | |8 |10 |64 |100 |80 | |5 | 7 |25 | 49 |35 | |9 | ? | | | | (X = 33, (Y = 38, (XY = 227, (X2 = 199, [pic]= 5. 5, [pic]= 6. 33. Therefore: [pic] The following figure shows both the data and the resulting equation: [pic] (c) If there are nine performances by Stone Temple Pilots, the estimated sales are: (d) R = . 82 is the correlation coefficient, and R2 = . 68 means 68% of the variation in sales can be explained by TV appearances. 4. 25? |Number of | | | | | |Accidents | | | | |Month |(y) |x |xy |x2 | |January | 30 | 1 | 30 | 1 | |February | 40 | 2 | 80 | 4 | |March | 60 | 3 |180 | 9 | |April | 90 | 4 |360 |16 | |? Totals | |220 | | | [pic] The regression line is y = 5 + 20x. The forecast for May (x = 5) is y = 5 + 20(5) = 105. 4. 26 |Season |Year1 |Year2 |Average |Average |Seasonal |Year3 | | |Demand |Demand |Year1(Year2 |Season |Index |Demand | | | | |Demand |Demand | | | |Fall |200 |250 |225. 0 |250 |0. 90 |270 | |Winter |350 |300 |325. |250 |1. 30 |390 | |Spring |150 |165 |157. 5 |250 |0. 63 |189 | |Summer |300 |285 |292. 5 |250 |1. 17 |351 | 4. 27 | | Winter |Spring |Summer |Fall | |2006 |1,400 |1,500 |1,000 |600 | |2007 |1,200 |1,400 |2,100 |750 | |2008 |1,000 |1,600 |2,000 |650 | |2009 | 900 |1,500 |1,900 | 500 | | |4,500 |6,000 |7,000 |2,500 | 4. 28 | | | | |Average | | | | | | |Average |Quarterly |Seasonal | |Quarter |2007 |2008 |2009 |Demand |Demand |Index | |Winter | 73 | 65 | 89 | 75. 67 |106. 67 |0. 709 | |Spring |104 | 82 |146 |110. 67 |106. 67 |1. 037 | |Summer |168 |124 |205 |165. 67 |106. 67 |1. 553 | |Fall | 74 | 52 | 98 | 74. 67 |106. 67 |0. 700 | 4. 29? 2011 is 25 years beyond 1986. Therefore, the 2011 quarter numbers are 101 through 104. | | | | |(5) | | |(2) |(3) |(4) |Adjusted | |(1) |Quarter |Forecast |Seasonal |Forecast | |Quarter |Number |(77 + . 3Q) |Factor |[(3) ( (4)] | |Winter |101 |12 0. 43 | . 8 | 96. 344 | |Spring |102 |120. 86 |1. 1 |132. 946 | |Summer |103 |121. 29 |1. 4 |169. 806 | |Fall |104 |121. 72 | . 7 | 85. 204 | 4. 30? Given Y = 36 + 4. 3X (a) Y = 36 + 4. 3(70) = 337 (b) Y = 36 + 4. 3(80) = 380 (c) Y = 36 + 4. 3(90) = 423 4. 31 4. 33? (a)? See the table below. For next year (x = 6), the number of transistors (in millions) is forecasted as y = 126 + 18(6) = 126 + 108 = 234. Then y = a + bx, where y = number sold, x = price, and |4. 32? a) | x |y |xy |x2 | | | 16 | 330 | 5,280 |256 | | | 12 | 270 | 3,240 |144 | | | 18 | 380 | 6,840 |324 | | | 14 | 300 | 4,200 |196 | | | 60 |1,280 |19,560 |920 | So at x = 2. 80, y = 1,454. 6 – 277. 6($2. 80) = 677. 32. Now round to the nearest integer: Answer: 677 lattes. [pic] (b)? If the forecast is for 20 guests, the bar sales forecast is 50 + 18(20) = $410. Each guest accounts for an additional $18 in bar sales. |Table for Problem 4. 33 | | | | | |Year |Transistors | | | | | | | |(x) |(y) |xy |x2 |126 + 18x |E rror |Error2 ||% Error| | | |? 1 |140 |? 140 |? 1 |144 |–4 |? 16 |100 (4/140)? = 2. 86% | | |? 2 |160 |? 320 |? 4 |162 |–2 | 4 |100 (2/160)? = 1. 25% | | |? 3 |190 |? 570 |? 9 |180 |10 |100 |100 (10/190) = 5. 26% | | |? 4 |200 |? 800 |16 |198 |? 2 | 4 |100 (2/200) = 1. 00% | | |? |210 |1,050 |25 |216 |–6 |? 36 |100 (6/210)? = 2. 86% | |Totals |15 | | |900 | | |2,800 | | (b)? MSE = 160/5 = 32 (c)? MAPE = 13. 23%/5 = 2. 65% 4. 34? Y = 7. 5 + 3. 5X1 + 4. 5X2 + 2. 5X3 (a)? 28 (b)? 43 (c)? 58 4. 35? (a)? [pic] = 13,473 + 37. 65(1860) = 83,502 (b)? The predicted selling price is $83,502, but this is the average price for a house of this size. There are other factors besides square footage that will impact the selling price of a house. If such a house sold for $95,000, then these other factors could be contributing to the additional value. (c)?Some other quantitative variables would be age of the house, number of bedrooms, size of the lot, and size of the garage, etc. (d)? Coefficient of determination = (0. 63)2 = 0. 397. This means that only about 39. 7% of the variability in the sales price of a house is explained by this regression model that only includes square footage as the explanatory variable. 4. 36? (a)? Given: Y = 90 + 48. 5X1 + 0. 4X2 where: [pic] If: Number of days on the road ( X1 = 5 and distance traveled ( X2 = 300 then: Y = 90 + 48. 5 ( 5 + 0. 4 ( 300 = 90 + 242. 5 + 120 = 452. 5 Therefore, the expected cost of the trip is $452. 50. (b)? The reimbursement request is much higher than predicted by the model. This request should probably be questioned by the accountant. (c)?A number of other variables should be included, such as: 1.? the type of travel (air or car) 2.? conference fees, if any 3.? costs of entertaining customers 4.? other transportation costs—cab, limousine, special tolls, or parking In addition, the correlation coefficient of 0. 68 is not exceptionally high. It indicates that the model explains approximately 46% of the overall variation in trip cost. This correlation coefficient would suggest that the model is not a particularly good one. 4. 37? (a, b) |Period |Demand |Forecast |Error |Running sum ||error| | | 1 |20 |20 |0. 00 |0. 00 |0. 00 | | 2 |21 |20 |1. 00 |1. 0 |1. 00 | | 3 |28 |20. 5 |7. 50 |8. 50 |7. 50 | | 4 |37 |24. 25 |12. 75 |21. 25 |12. 75 | | 5 |25 |30. 63 |–5. 63 |15. 63 |5. 63 | | 6 |29 |27. 81 |1. 19 |16. 82 |1. 19 | | 7 |36 |28. 41 |7. 59 |24. 41 |7. 59 | | 8 |22 |32. 20 |–10. 20 |14. 21 |10. 20 | | 9 |25 |27. 11 |–2. 10 |12. 10 |2. 10 | |10 |28 |26. 05 | 1. 95 |14. 05 | | | | | | |1. 95 | | | | | | | | | | | | | | | |MAD[pic]5. 00 | Cumulative error = 14. 05; MAD = 5? Tracking = 14. 05/5 ( 2. 82 4. 38? (a)? least squares equation: Y = –0. 158 + 0. 1308X (b)? Y = –0. 158 + 0. 1308(22) = 2. 719 million (c)? coefficient of correlation = r = 0. 966 coefficient of determination = r2 = 0. 934 4. 39 |Year X |Patients Y |X2 |Y2 |XY | |? 1 |? 36 | 1 |? 1,296 | 36 | |? 2 |? 33 | |? 1,089 | 66 | |? 3 |? 40 | 9 |? 1,600 |? 120 | |? 4 |? 41 |? 16 |? 1,681 |? 164 | |? 5 |? 40 |? 25 |? 1,600 |? 200 | |? 6 |? 55 |? 36 |? 3,025 |? 330 | |? 7 |? 60 |? 49 |? 3,600 |? 420 | |? 8 |? 54 |? 64 |? 2,916 |? 432 | |? 9 |? 58 |? 81 |? 3,364 |? 522 | |10 |? 61 |100 |? 3,721 |? 10 | |55 | | |478 | | |X |Y |Forecast |Deviation |Deviation | |? 1 |36 |29. 8 + 3. 28 ( ? 1 = 33. 1 |? 2. 9 |2. 9 | |? 2 |33 |29. 8 + 3. 28 ( ? 2 = 36. 3 |–3. 3 |3. 3 | |? 3 |40 |29. 8 + 3. 28 ( ? 3 = 39. 6 |? 0. 4 |0. 4 | |? 4 |41 |29. 8 + 3. 28 ( ? 4 = 42. 9 |–1. 9 |1. 9 | |? 5 |40 |29. 8 + 3. 28 ( ? 5 = 46. 2 |–6. 2 |6. 2 | |? 6 |55 |29. 8 + 3. 28 ( ? 6 = 49. 4 |? 5. 6 |5. 6 | |? 7 |60 |29. 8 + 3. 28 ( ? 7 = 52. 7 |? 7. 3 |7. 3 | |? |54 |29. 8 + 3. 28 ( ? 8 = 56. 1 |–2. 1 |2. 1 | |? 9 |58 |29. 8 + 3. 28 ( ? 9 = 59. 3 |–1. 3 |1. 3 | |10 |61 |29. 8 + 3. 28 ( 10 = 62. 6 |–1. 6 |1. 6 | | | | | | ( = | | | | | |32. 6 | | | | | |MAD = 3. 26 | The MAD is 3. 26—this is approximately 7% of the average number of patients and 10% of the minimum number of patients. We also see absolute deviations, for years 5, 6, and 7 in the range 5. 6–7. 3.The comparison of the MAD with the average and minimum number of patients and the comparatively large deviations during the middle years indicate that the forecast model is not exceptionally accurate. It is more useful for predicting general trends than the actual number of patients to be seen in a specific year. 4. 40 | |Crime |Patients | | | | |Year |Rate X |Y |X2 |Y2 |XY | |? 1 |? 58. 3 |? 36 |? 3,398. 9 |? 1,296 |? 2,098. 8 | |? 2 |? 61. 1 |? 33 |? 3,733. 2 |? 1,089 |? 2,016. 3 | |? 3 |? 73. |? 40 |? 5,387. 6 |? 1,600 |? 2,936. 0 | |? 4 |? 75. 7 |? 41 |? 5,730. 5 |? 1,681 |? 3,103. 7 | |? 5 |? 81. 1 |? 40 |? 6,577. 2 |? 1,600 |? 3,244. 0 | |? 6 |? 89. 0 |? 55 |? 7,921. 0 |? 3,025 |? 4,895. 0 | |? 7 |101. 1 |? 60 |10,221. 2 |? 3,600 |? 6,066. 0 | |? 8 |? 94 . 8 |? 54 |? 8,987. 0 |? 2,916 |? 5,119. 2 | |? 9 |103. 3 |? 58 |10,670. 9 |? 3,364 |? 5,991. 4 | |10 |116. 2 |? 61 |13,502. 4 |? 3,721 |? 7,088. 2 | |Column | |854. | | |478 | |Totals | | | | | | |months) |(Millions) |(1,000,000s) | | | | |Year |(X) |(Y) |X2 |Y2 |XY | |? 1 |? 7 |1. 5 |? 49 |? 2. 25 |10. 5 | |? 2 |? 2 |1. 0 | 4 |? 1. 00 |? 2. 0 | |? 3 |? 6 |1. 3 |? 36 |? 1. 69 |? 7. 8 | |? 4 |? 4 |1. 5 |? 16 |? 2. 25 |? 6. 0 | |? 5 |14 |2. 5 |196 |? 6. 25 |35. 0 | |? 6 |15 |2. 7 |225 |? 7. 9 |40. 5 | |? 7 |16 |2. 4 |256 |? 5. 76 |38. 4 | |? 8 |12 |2. 0 |144 |? 4. 00 |24. 0 | |? 9 |14 |2. 7 |196 |? 7. 29 |37. 8 | |10 |20 |4. 4 |400 |19. 36 |88. 0 | |11 |15 |3. 4 |225 |11. 56 |51. 0 | |12 |? 7 |1. 7 |? 49 |? 2. 89 |11. 9 | Given: Y = a + bX where: [pic] and (X = 132, (Y = 27. 1, (XY = 352. 9, (X2 = 1796, (Y2 = 71. 59, [pic] = 11, [pic]= 2. 26. Then: [pic] andY = 0. 511 + 0. 159X (c)?Given a tourist population of 10,000,000, the model predicts a ridership of: Y = 0. 511 + 0. 159 ( 10 = 2. 101, or 2,101,000 persons. (d)? If there are no tourists at all, the model predicts a ridership of 0. 511, or 511,000 persons. One would not place much confidence in this forecast, however, because the number of tourists (zero) is outside the range of data used to develop the model. (e)? The standard error of the estimate is given by: (f)? The correlation coefficient and the coefficient of determination are given by: [pic] 4. 42? (a)? This problem gives students a chance to tackle a realistic problem in business, i. e. , not enough data to make a good forecast.As can be seen in the accompanying figure, the data contains both seasonal and trend factors. [pic] Averaging methods are not appropriate with trend, seasonal, or other patterns in the data. Moving averages smooth out seasonality. Exponential smoothing can forecast January next year, but not farther. Because seasonality is strong, a naive model that students create on their own might be best. (b) One model might be: Ft+1 = At–11 That is forecastnext period = actualone year earlier to account for seasonality. But this ignores the trend. One very good approach would be to calculate the increase from each month last year to each month this year, sum all 12 increases, and divide by 12.The forecast for next year would equal the value for the same month this year plus the average increase over the 12 months of last year. (c) Using this model, the January forecast for next year becomes: [pic] where 148 = total monthly increases from last year to this year. The forecasts for each of the months of next year then become: |Jan. |29 | |July. |56 | |Feb. |26 | |Aug. |53 | |Mar. |32 | |Sep. |45 | |Apr. |35 | |Oct. |35 | |May. |42 | |Nov. |38 | |Jun. |50 | |Dec. |29 | Both history and forecast for the next year are shown in the accompanying figure: [pic] 4. 3? (a) and (b) See the following table: | |Actual |Smoothed | |Smoothed | | |Week |Value |Value |Forecast |Value |Forecast | |t |A(t) |Ft (( = 0. 2) |Err or |Ft (( = 0. 6)|Error | | 1 |50 |+50. 0 |? +0. 0 |+50. 0 |? +0. 0 | | 2 |35 |+50. 0 |–15. 0 |+50. 0 |–15. 0 | | 3 |25 |+47. 0 |–22. 0 |+41. 0 |–16. 0 | | 4 |40 |+42. 6 |? –2. 6 |+31. 4 |? +8. 6 | | 5 |45 |+42. 1 |? –2. 9 |+36. 6 |? +8. | | 6 |35 |+42. 7 |? –7. 7 |+41. 6 |? –6. 6 | | 7 |20 |+41. 1 |–21. 1 |+37. 6 |–17. 6 | | 8 |30 |+36. 9 |? –6. 9 |+27. 1 |? +2. 9 | | 9 |35 |+35. 5 |? –0. 5 |+28. 8 |? +6. 2 | |10 |20 |+35. 4 |–15. 4 |+32. 5 |–12. 5 | |11 |15 |+32. 3 |–17. 3 |+25. 0 |–10. 0 | |12 |40 |+28. 9 |+11. 1 |+19. 0 |+21. 0 | |13 |55 |+31. 1 |+23. 9 |+31. 6 |+23. 4 | |14 |35 |+35. 9 |? 0. 9 |+45. 6 |–10. 6 | |15 |25 |+36. 7 |–10. 7 |+39. 3 |–14. 3 | |16 |55 |+33. 6 |+21. 4 |+30. 7 |+24. 3 | |17 |55 |+37. 8 |+17. 2 |+45. 3 |? +9. 7 | |18 |40 |+41. 3 |? –1. 3 |+51. 1 |–11. 1 | |19 |35 |+41. 0 |? –6. 0 |+44. 4 |? –9. 4 | |20 |60 |+39. 8 |+20. 2 |+38. 8 |+21. 2 | |21 |75 |+43. 9 |+31. 1 |+51. 5 |+23. 5 | |22 |50 |+50. 1 |? –0. 1 |+65. 6 |–15. | |23 |40 |+50. 1 |–10. 1 |+56. 2 |–16. 2 | |24 |65 |+48. 1 |+16. 9 |+46. 5 |+18. 5 | |25 | |+51. 4 | |+57. 6 | | | | |MAD = 11. 8 |MAD = 13. 45 | (c)? Students should note how stable the smoothed values are for ( = 0. 2. When compared to actual week 25 calls of 85, the smoothing constant, ( = 0. 6, appears to do a slightly better job. On the basis of the standard error of the estimate and the MAD, the 0. 2 constant is better. However, other smoothing constants need to be examined. |4. 4 | | | | | | |Week |Actual Value |Smoothed Value |Trend Estimate |Forecast |Forecast | |t |At |Ft (( = 0. 3) |Tt (( = 0. 2) |FITt |Error | |? 1 |50. 000 |50. 000 |? 0. 000 |50. 000 | 0. 000 | |? 2 |35. 000 |50. 000 |? 0. 000 |50. 000 |–15. 000 | |? 3 |25. 000 |45. 500 |–0. 900 |44. 600 |–19. 600 | |? 4 |40. 000 |38. 720 |– 2. 076 |36. 644 | 3. 56 | |? 5 |45. 000 |37. 651 |–1. 875 |35. 776 | 9. 224 | |? 6 |35. 000 |38. 543 |–1. 321 |37. 222 |? –2. 222 | |? 7 |20. 000 |36. 555 |–1. 455 |35. 101 |–15. 101 | |? 8 |30. 000 |30. 571 |–2. 361 |28. 210 | 1. 790 | |? 9 |35. 000 |28. 747 |–2. 253 |26. 494 | 8. 506 | |10 |20. 000 |29. 046 |–1. 743 |27. 03 |? –7. 303 | |11 |15. 000 |25. 112 |–2. 181 |22. 931 |? –7. 931 | |12 |40. 000 |20. 552 |–2. 657 |17. 895 |? 22. 105 | |13 |55. 000 |24. 526 |–1. 331 |23. 196 |? 31. 804 | |14 |35. 000 |32. 737 |? 0. 578 |33. 315 | 1. 685 | |15 |25. 000 |33. 820 |? 0. 679 |34. 499 |? –9. 499 | |16 |55. 000 |31. 649 |? 0. 109 |31. 58 |? 23. 242 | |17 |55. 000 |38. 731 |? 1. 503 |40. 234 |? 14. 766 | |18 |40. 000 |44. 664 |? 2. 389 |47. 053 |? –7. 053 | |19 |35. 000 |44. 937 |? 1. 966 |46. 903 |–11. 903 | |20 |60. 000 |43. 332 |? 1. 252 |44. 584 |? 15. 416 | |21 |75. 00 0 |49. 209 |? 2. 177 |51. 386 |? 23. 614 | |22 |50. 000 |58. 470 |? 3. 94 |62. 064 |–12. 064 | |23 |40. 000 |58. 445 |? 2. 870 |61. 315 |–21. 315 | |24 |65. 000 |54. 920 |? 1. 591 |56. 511 | 8. 489 | |25 | |59. 058 |? 2. 100 |61. 158 | | To evaluate the trend adjusted exponential smoothing model, actual week 25 calls are compared to the forecasted value. The model appears to be producing a forecast approximately mid-range between that given by simple exponential smoothing using ( = 0. 2 and ( = 0. 6.Trend adjustment does not appear to give any significant improvement. 4. 45 |Month |At |Ft ||At – Ft | |(At – Ft) | |May |100 |100 | 0 | 0 | |June | 80 |104 |24 |–24 | |July |110 | 99 |11 |11 | |August |115 |101 |14 |14 | |September |105 |104 | 1 | 1 | |October |110 |104 |6 |6 | |November |125 |105 |20 |20 | December |120 |109 |11 |11 | | | | |Sum: 87 |Sum: 39 | |4. 46 (a) | |X |Y |X2 |Y2 |XY | | |? 421 |? 2. 90 |? 177241 | 8. 41 |? 1220. 9 | | |? 377 | ? 2. 93 |? 142129 | 8. 58 |? 1104. 6 | | |? 585 |? 3. 00 |? 342225 | 9. 00 |? 1755. 0 | | |? 690 |? 3. 45 |? 476100 |? 11. 90 |? 2380. 5 | | |? 608 |? 3. 66 |? 369664 |? 13. 40 |? 2225. 3 | | |? 390 |? 2. 88 |? 52100 | 8. 29 |? 1123. 2 | | |? 415 |? 2. 15 |? 172225 | 4. 62 | 892. 3 | | |? 481 |? 2. 53 |? 231361 | 6. 40 |? 1216. 9 | | |? 729 |? 3. 22 |? 531441 |? 10. 37 |? 2347. 4 | | |? 501 |? 1. 99 |? 251001 | 3. 96 | 997. 0 | | |? 613 |? 2. 75 |? 375769 | 7. 56 |? 1685. 8 | | |? 709 |? 3. 90 |? 502681 |? 15. 21 |? 2765. 1 | | |? 366 |? 1. 60 |? 133956 | 2. 56 | 585. 6 | | |Column |6885 | |36. 6 | | | |totals | | | | | |January |400 |— |— | — |— | |February |380 |400 |— |20. 0 |— | |March |410 |398 |— |12. 0 |— | |April |375 | 399. 2 |396. 67 |24. 2 |21. 67 | |May |405 | 396. 8 |388. 33 |8. 22 |16. 67 | | | | |MAD = | |16. 11| | |19. 17| | (d)Note that Amit has more forecast observations, while Barbara’s moving average does not start until month 4. 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1 |? 1 |0. 25 |–17. 330 |309. 061 | |? 2 |? 2 |0. 24 |–15. 692 |253. 823 | |? 3 |? 3 |0. 24 |–14. 054 |204. 31 | |? 4 |? 4 |0. 26 |–12. 415 |160. 662 | |? 5 |? 5 |0. 25 |–10. 777 |121. 594 | |? 6 |? 6 |0. 30 |? –9. 1387 |89. 0883 | |? 7 |? 7 |0. 31 |? –7. 50 |61. 0019 | |? 8 |? 8 |0. 32 |? –5. 8621 |38. 2181 | |? |? 9 |0. 24 |? –4. 2238 |19. 9254 | |10 |10 |0. 26 |? –2. 5855 |8. 09681 | |11 |11 |0. 25 |? –0. 947 |1. 43328 | |12 |12 |0. 33 |? 0. 691098 |0. 130392 | |13 |13 |0. 50 |? 2. 329 |3. 34667 | |14 |14 |0. 95 |? 3. 96769 |9. 10642 | |15 |15 |1. 70 |? 5. 60598 |15. 2567 | |16 |16 |2. 30 |? 7. 24 427 |24. 4458 | |17 |17 |2. 0 |? 8. 88257 |36. 9976 | |18 |18 |2. 80 |? 10. 52 |59. 6117 | |19 |19 |2. 70 |? 12. 1592 |89. 4756 | |20 |20 |3. 90 |? 13. 7974 |97. 9594 | |21 |21 |4. 90 |? 15. 4357 |111. 0 | |22 |22 |5. 30 |? 17. 0740 |138. 628 | |23 |23 |6. 20 |? 18. 7123 |156. 558 | |24 |24 |4. 10 |? 20. 35 |264. 083 | |25 |25 |4. 50 |? 21. 99 |305. 62 | |26 |26 |6. 10 |? 23. 6272 |307. 203 | |27 |27 |7. 70 |? 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12. 2643 |? 150. 412 | |41 |4. 60 |70. 10 |44. 951 |? 25. 20 |? 635. 288 | |42 |4. 60 |70. 90 |44. 8951 |? 26. 00 |? 676. 256 | |43 |4. 70 |79. 10 |46. 2544 |? 32. 8456 |1,078. 83 | |44 |5. 00 |94. 00 |50. 3325 |? 43. 6675 |1,906. 85 | |TOTALS | | | |451. 223 |9,016. 45 | |AVERAGE | | | |? 10. 2551 |? 204. 92 | | | | | |? 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Production Method in Chicken Industry - Essay Example In a wider point of view, some people may know utilitarianism as way to contrary Human Rights but utilitarian have answered to most of these questions or at least tried to bring a justification to disavow these ideas.7 "Utilitarianism consists of two doctrines: A theory of what is Right, and a theory of what is Good."8. In the first section of this case study we will try to bring enough justification via utilitarian principles to persuade the consumers that the Supply Chain's position is in the best form of it in the current situation of the Chicken Industry in the United Kingdom. (poultry) being cheaper in our supermarkets today than twenty years ago. The supply chain of the industry consists of four key elements, the breeders, the factory farmers, the abattoirs/packers and the supermarkets. Consumer groups have in recent times been critical of every stage of the supply chain. The RSPCA considers "suffering of broiler chickens as one of the most pressing animal welfare issues in the UK today". Fifty percent of chickens entering the food chain are also known to carry campylobacter; a cause of food poisoning. Supermarkets have been criticised for using chicken in marketing promotions such as "buy one get one free" that cause farmers substantial loss of income."9 As mentioned before utilitarianism consists of two doctrines. The first one or "What is right" is actually Varieties of "Consequentialism". The first one is "Act Consequentialism" that states that an action is right only if it brings us benefits no matter if is a wrong decision. In our case study, the supply chain decides to sell the products in any way to prevent serious detriment to the whole system in long run no matter if it harms the consumer or cause farmers substantial loss of income. The best decision is the decision that gives the supply chain a benefit or prevents huge detriment. It is not important if a minority hurts or even become sacrificed. Farmers does hurt but they are a minority of the population. Customers hurt too but the supply chain decides to give them some incentive such as bringing the price to 50% via "buy one get one free" policy. This way, the chain and the consumers are happy but the farmers are not. This isn't much fair but it

The role of the IMF & World Bank Essay Example | Topics and Well Written Essays - 2500 words

The role of the IMF & World Bank - Essay Example The realist theories propose that the sovereign states are the main actors in the international system and that other institutions have little influence in the international scene (Evans M. 2001). Of course this assumption at that time was very plausible considering the fact that globalization and giant multi-national organizations were not really very popular at the time when the World Bank and the IMF were organized. Remember that it was just after World War II when these organizations came into being and at that time the notion that the international system is anarchic (Doyle, Michael (1997) and that no authority is considered above the state that is capable of regulating the interactions among nations (Schweller, Randall L (2003) was very popular. Since the World Bank and the IMF were organized to help the states, their presence was more or less acceptable to its member nations. Of course the roles that World Bank and the IMF play have been questions by many people over the years but the point is that these organizations have been instrumental in bringing together some order in the international financial scene. Moreover, aside from trying to make some policy influence on some nations, the World Bank and the IMF do not really have any means of directly intervening into the affairs of the different states all over the world. In other words, despite the presence of these international organizations, nations remain to be relatively independent when it comes to making decisions. At the start, we can say that the World and the IMF were more biased toward assisting sovereign nations and do not really recognize non-government organizations as potential vehicles for development. The initial task of the World Bank was specific towards rebuilding the European nations after World War II and the IMF were more geared towards stabilizing the economy of

Intriguing Giant Panda Mysteries Essay Example for Free

Intriguing Giant Panda Mysteries Essay While most adore their fluffy fur and round heads, which help give them their cuddly bear quality, others are fascinated by the many mysteries of the giant panda. Did you know that the giant panda may actually be a raccoon, they have an opposable pseudo thumb, and that they’re technically a carnivore even though their diet is primarily vegetarian? These things and more have baffled scientists and naturalists for hundreds of years. Opposable Pseudo Thumb A characteristic of the giant panda that has mystified scientists is their movable, elongated wrist bone that acts like an opposable thumb. This human-like quality that helps give them even more of a cuddly-bear appearance enables the giant panda to pick up objects and even eat sitting up. Quick Fact Giant pandas have five clawed toes and one pseudo thumb. Their pseudo thumb, along with pads of skin, help the giant panda strip the more nutritious small bamboo shoots and leaves while holding the stalk in their mouth. Small Bear or Large Raccoon? Giant pandas are generally referred to as bears and are typically called panda bears rather than giant pandas. Though we may think they look like bears, there has been a great deal of discussion for decades about where giant pandas actually fit in the animal kingdom. Much of the debate has been whether they are more closely related to the red panda, once thought to be a member of the raccoon family, than the bear family. While a giant panda has a body that resembles a small bear and climbs trees like a bear, it also has several characteristics in common with the red panda. For example, both giant pandas and red pandas eat bamboo and have the same pseudo thumb. The table below lists the main characteristics the giant panda shares with bears and red pandas. Panda Facts Researchers have recently discovered that the gene responsible for tasting savoury or umami flavours, such as meat, is inactive in giant pandas. For many centuries, giant pandas were thought to be a mythical creature, similar to a dragon or unicorn. Unlike other bears in the region, giant pandas don’t hibernate. Giant pandas can stand erect on their hind legs but rarely walk. The Qinling panda, another giant panda species with a dark brown and light brown coat, lives only in the mountains of Shaanxi. Giant pandas have very sensitive hearing and smell, but they have poor eyesight. A newborn giant panda is blind and looks like a t

Free

Free Space Optical Communication Essay Free space optical communication is the most growing communication because it is easy to install and has a high speed because the signal is transmitted in the air. So that will introduce the atmospheric affect in the optical wave propagation. Atmospheric turbulence causes fluctuations in both the intensity and the phase of the received signal. So we need to study the effect and the limitation if we introduce a free space optical communication system with dual wavelength (980 nm, 1550 nm). Also studying the effect of turbulence when using two different wavelengths. Introduction Free space optical communication is a kind of communication that use light propagation to send data between two points. Free Space Optics are capable of up to 2.5 Gbps of data, voice and video communications through the air, allowing optical connectivity without requiring fiber-optic cable or securing spectrum licenses. So we can use LED’s or Laser for transmission data. Free Space Optics (FSO) technology is relatively simple. Its built on a laser transmitter and a receiver to provide full duplex capability. Each FSO unit uses a high-power optical source, a lens that transmits light through the atmosphere to another lens receiving the information. The receiving lens connects to a high-sensitivity receiver via optical fiber. Because the transmission in occurred in air it is easily upgradable. FSO send a light beam from one point to another using low power lasers in the teraHertz spectrum. This beam is transmitted by laser light focused on photon detector receivers. These receivers collect the photon stream and transmit digital data. If there is a clear line between the two point FSO can operate on a distance of several kilometers as long we have a powerful transmitter. Features of the laser communications system Information usually in the form of digital data, data is entered to be regulated by the laser source transmitting electronics. Coding techniques can be used directly or indirectly depending on the type of laser used. Output source passes through the optical system in the channel. The visual system usually involves the transfer, beam shaping, and the telescope optics. Beam receiver comes in through the optical system and passed to the detection and signal processing electronics. There is also a terminal control electronics that must manage gimbals guidelines and other mechanisms, and machinery, to maintain and track the acquisition of the operating system designed in the mass of the process. In order to communicate, you must have received enough energy by the detector to distinguish signal from noise. Laser power, optical transmission system losses, pointing out shortcomings of the system, transmitter and receiver antenna gains and losses, receiver, receiver and loss tracking, are all factors that force in the establishment of the receiver power. The required optical power is determined by data rate, detector sensitivity, configuration modes, noise, and detection methods. When the receiver is to detect the signals, it is in fact the decision-making regarding the nature of the signal (digital signal is sent when the distinction between the ones and zeros). There are two types of distributions: one when the signal present (including the amount of photocurrent due to the background and the current detector in the dark), and one when there is no signal present (including sources of no signal current only). A threshold must be developed to increase the success rate and reduces the error rate. Even when there is no signal present, the fluctuation sources of no signal lead periodically to the threshold to be exceeded. This is an error stating that the signal exists when there is no signal present. Distribution of signal may also fall on the other side of the threshold, so any errors stating that the signal is going to happen even when the signal is present. Security FSO systems work in the near infrared wavelength range slightly above the visible spectrum. So, the human eye cannot clearly see the transmission beam. The wavelength range is around 1 micrometer that is used in FSO transmission. The interception of FSO operating systems with narrow beam in the infrared spectral wavelength is by far the more difficult. Small diameter of the beam is usually only a few meters in diameter in the target site are one of the reasons that make it extremely difficult to intercept the communications of the FSO. Intruder must know the exact origin or target of the infrared beam and intercept only within a very narrow angle of beam propagation. Intercept packets directly from the FSO networks between remote locations is impossible mainly because the beam passes through the air usually at a higher altitude than at ground level. Due to the fact that the transmission beam is not visible, and that any attempts to block the beam can occur near the FSO point of acces s and the process of transition poses another obstacle. Capture the signal from the location that does not fall directly within the path of light with photons of light scattered from aerosols, fog, rain, or molecules that may be present in the atmosphere is almost impossible because of the energy levels are very low use infrared through FSO process transmission. The main reason for the exclusion of this possibility of intrusion is the fact that light is an ally and statistically isotropic in different directions from the path of the original propagation. This specific mechanism keeps the total number of photons or the amount of radiation that can potentially be collected on the detector that is not placed directly in the beam path beyond the detection level of noise. Atmospheric turbulence Atmospheric turbulence can destroy the performance of FSO systems. The changes in temperature and pressure in the atmosphere lead to changes of the refractive index along the transmission path. These changes can make the quality of received signal fade and causes fluctuations in the intensity and the phase of the received signal. These fluctuations can limit the performance of the system. The atmosphere is a viscous fluid and it has two state motions: 1) laminar (there is no mixing in the air molecules) 2) turbulent: (there is mixing that creates eddies). Atmospheric turbulence can be physically described by Kolmogorov theory. The energy of large eddies is redistributed without loss to eddies of decreasing size until finally dissipated by viscosity. The size of turbulence eddies normally ranges from a few millimeters to a few meters, denoted as the inner scale and the outer scale, respectively. So the index of refraction n is very sensitive to small scale temperature fluctuations (te mperature fluctuations are combined with turbulent mixing). So, the index of refraction is the most important in optical wave propagation. Because it behaves like a passive additive. So the spectrum of index of refraction can be described by Kolmogorove spectrum ÃŽ ¦n (ÃŽ º) = 0.033 Cn 2 ÃŽ º-11/3 , 1/L0 ÃŽ º 1/l0 Here in this model the variations in humidity and pressure are neglected. This model is the most model used in theoretical analyses but it is right only over wave number within the inertial subrange. To take into account the inner and outer scale effects, there is various models have been developed. Like Tatarskii and van Karman models. So all these models are useful for theoretical calculations but only inside the inertial range. They are not based on rigorous calculations outside the inertial range, but more on mathematical convenience and tractability. The modified atmospheric spectrum is the only model that features the high wave number rise prior to the dissipation range. ÃŽ ¦n (ÃŽ º) = 0.033 Cn 2 [1+1.802(ÃŽ º/ÃŽ ºl)-.254(ÃŽ º/ÃŽ ºl)7/6] x exp(-ÃŽ º2/ÃŽ º2 l)/(ÃŽ º2 + ÃŽ º20)11/6 , 0= ÃŽ º ∞ , ÃŽ ºl=3.3/l0 Experiment The experiment that we need to do is to use two laser sources with different wavelength (980 , 1550) and set the receivers about 2-4 km from the transmitter and start sending the signals. We will use the same signals in both transmitters. Then we will study the performance of the system and see if that help to receive the signal in more accurate way than using one transmitter. That will help us to see the effect of optical turbulence and atmospheric effects. So we will calculate the performance of the system and measure the atmospheric turbulence. So we need to ask some questions: What is the effect of optical turbulence? Is losing a part of one signal will be recovered by the other signal? Is that going to help the performance of the system? Is the pdf that we used in the transmitter side will be the same as the pdf in the receiver side? Light wave Light wave Receiver Receiver Transmitter Transmitter Transmitter Transmitter Receiver Receiver Read phonetically Dictionary Reference 1. Laser beam propagation through random media by Larry C. Andrews, Ronald L. Phillips. 2. Free space optical communications class notes. 3. http://www.seminarprojects.com/Thread-freespace-optics-full-report#ixzz1KfUtl5xP 4. http://en.wikipedia.org/wiki/Free-space_optical_communication

Research On Compensation And Benefits In Employee Motivation Business Essay

Research On Compensation And Benefits In Employee Motivation Business Essay Abstract (executive summary) One of the biggest challenges facing business entities is the recruitment and retaining employees especially in the 21st century where the interest of employees is not getting employed, but rather in getting satisfaction in their jobs. Many employees come from houses and environments that are violent and chaotic. In the job, such kind of an employee needs to feel happy and forget the home problems. Consequently, employees move from one job to another in search of this environment. One of the ways of keeping these employees is to motivate them, a subject very complex, broad and expensive. The research carried out identifies compensation and benefits of keeping such employees in addition to the other motivational factors. Introduction Employees can very committed to the work assigned and be working very hard. However, if their hard work is not seen and appreciated, they become demoralized and their productivity may diminish considerably (Werner, and DeSimone, 2009). It is believed that human resource is the most valuable and delicate asset of a business though never included in the balance sheet of the corporation. Mistreating them will make the productivity of the business go down and consequently collapse, while appreciating their efforts will encourage them more leading to more production thus growth, development, and expansion of the business with the goals, objectives, vision, and mission in the mind in a bid to achieve them (McNamara). Motivation is one of the factors that keep employees on board, motivates them to work harder and better thus leading to increased productivity and growth of the business. Without motivation, productivity, morale, profits, product, and service delivery becomes at stake. It may be external or internal in nature (Werner, and DeSimone, 2009). The external motivation factors include the non-related work environment including both financial and non-financial aspects. On the other hand, the internal factors are those related to working environment that may include good working relationship, clean working environment and probably use of appropriate tools. Whether internal or external, there should be motivation. Compensation and benefits are reward based motivational factors. Benefit is an indirect reward that an employee gets for being part of the family or the organization (Mathis, and Jackson, 2008). On the other hand, compensation entails the reward that is given to an employee to complement the time or any resource that he might have used. This is going to be the basis of my research and as I present this research paper together with the recommendation, I believe it will see the company go further. Through developing the right strategic planning, steps are going to be taken to support the motivation of your employees (Mathis, and Jackson, 2008). Problem Statement Many organizations including our organization have found it difficult to retain good employees and enhance their productivity. We lose employees to other organizations, especially our competitors who offer them good packages putting our strategies to dealing with the competitors at risk. As a human resource manager, I have come to realize that this is really affecting our organization. After a seriously consultation, there is need for us to come up with strategies that will see us retain most of our employees and improve the companys productivity. As a result, the human resource management team has decided to develop strategy that will compensate our employees increasing the production of the company by 25% in the next 5 years. Review of literature of the recent opinions Abraham Maslow Hierarchy of needs According to Abraham Maslows hierarchy of need, different people are at different level of satisfaction. Discovering which level each employee is at may be difficult complicating the idea behind motivational (Podmoroff, 2005). This aspect of challenge is termed management challenge. It is believed that in the past a person would work for a company for very long period unlike to day where a person within a short span of time has worked for more companies (Podmoroff, 2005). It is there fore very right to assume that employees no longer look for job as a security rather to achieve certain satisfaction, no wonder one keeps on moving from one job to the other. It is therefore very important that in the event that the company wants to keep employees long enough to achieve its goals, we must be keen in motivating them (Javitich, 2004). Fredrick Herzbergs theory of Hygiene and Motivational Factors This theory was developed based on the needs identified by the Abrahams hierarchy of needs. Herzberg divided these needs into two fold; needs focusing on survival while the other need emphasizing on personal growth, very important factors that employees would want in a job (Werner, and DeSimone, 2009). According to him, any factor that satisfies the survival need cannot provide job fulfillment to the fullest. In fact, Podmoroff (2005) says that combination of these two factors may result into four very influential conditions namely, low hygiene, and motivation and high hygiene and motivation. Werner, and DeSimone add that for these to be effective there is need to enrich the job given to the employee which entails providing both hygiene factors and adding the motivational ones. Douglas McGregors Theory X and Theory Y According to McGregors theory X, a person considers work intrinsically unpleasant and as such can do what he can to avoid the work. Theory Y on the other hand starts the contrary of events; a person looks at work as very favorable and would do anything to stay in the job (Podmoroff, 2005). Ensuring performance would there mean that. This calls for different principles to be applied by the management in order to achieve the desired motivational level. Some of the principles may include decentralizing the control of the organization, delegating some of the duties and especially to those who seem to fear job, make job diverse to accept different kind of people, ensure that the employees participate in the management of the organization and performing appraisals for the employees (Randhawa, 2007). Motivation of employee through Incentive compensation According to Gunkel (2006), motivation is the willingness to exert high levels of effort toward organization goals conditioned by the efforts ability to satisfy some individual needs. He believes that however much the idea of motivation is universal where individuals go ahead to maximize their usefulness by ensuring that the issues or objectives they value most are me, it is limited to the challenging design of the study. Some organizations however, will never offer rewards to its workers when they incur higher costs that the revenues or benefits that they derive from business operations (Gunkel, 2006). To him, motivation can either bee intrinsic, coming from within the individual or extrinsic, any thing an individual gets from another person. Processes theories of motivation by Victor Vroom, Lyman Porter and Edward Lawler, III This theory assumes that any action of an individual is always goal oriented. This means therefore that when the compensation of an individual is directed towards performance, then the employee is likely to perfume better (Gunkel, 2006). . The theory asserts that even with intrinsic motivational factors, hygiene or any other factors discussed above, there still exists the need for an extrinsic power to motivate further the employee say rewards (Gunkel, 2006). Gunkel (2006) further disagrees with the idea that when incentives are give to promote extrinsic motivation, a crowding out effect will be felt between the two that is , a persons internal motivational factors will be corrupted and in many cases may not perform well until the extrinsic motivator comes into play. According to him, this holds no water. Strategic plan for change From the literature review, Processes theory developed by Victor Vroom, Lyman Porter and Edward Lawler III, it is very evident that whether all the factors of motivation come into play without the reward or compensation aspect, then the motivation becomes useless. It is therefore proper that measures be put in place to ensure that the reward aspect of motivation is there. In this regard, the human resource department has seen it worth that will improve the compensation and benefits of the employees. This will not only see our goof workers remain in the company but also enhance the productivity of the company. Our target is to be a leading company with approximately 75% of the market share in the next five years. The compensation and reward scheme that we have developed will also see our company attracting many qualified employees. This will equip the management and the skills of our employees. Better management and qualified skills will ensure that we meet the set objectives within the stipulated period, which is five years. In the recruitment, we shall ensure that we employ the best workers and especially from our competitors. The idea is to know the strengths of our competitors and their weaknesses, developing on them, and devising policies to counter act their strengths. This I believe will make us go a long way in increasing the productivity of this company and make it grow. Pay system support to the business strategy With the introduction of new rewards comprising of the compensation and benefit schemes, it is important for us to enlarge the pay system of our organization. Through this pay system, the method of reward distribution will be easier, faster, and more efficient. The enlargement of the pay system will enable us have more employment opportunities which will lead to recruitment of more employees. The efficiency and effectiveness of the system will see into it that employees get the best working environment. This in turn will enable us meet the set objective of employing more employees and retaining them to increase productivity, market share and out wit the competitors. Our recruitment will majorly concentrate on employees from our competitors. The idea is to discover their weaknesses and strengths and outwit them using the SWOT analysis technique by majoring on their weaknesses. New system and motivation of behavior, Developed system will also help us attract more employees and retain them. This will be achieved by the fact that the working environment will be very conducive to the employees. The motivational factors employed will not be limited to hygiene, and motivational factors as well as a better and efficient system to help us identify the different levels of satisfaction of each employee and try to satisfy them. Efficiency and effectiveness in service delivery makes work easier thus many employees will opt to stay rather than leave for another job that has no aspect of efficiency in it as well as effectiveness of performance in the production process. Final recommendations and possible outcomes (best and worst case scenarios) Finally, based on the data obtained, there is need to make the following recommendations: We need a strategic approach to help us in implementing the changes that we would like to introduce. To assist us in doing this, I would like to recommend that a team be selected form all the departments who will assist in designing a strategy that we will use to implement the changes. Caution however should be taken, as many employees may be resistance to change. In formulating the total compensation scheme, as the one we have offered is a sketchy one, we would like the overall management of the organization, that is the president of the company, to help us with resources including human and other required resources; finances. In addition, a team majorly comprising of the accounts, finance, overall management department and operations management departments should be composed to help in developing the scheme. This is necessary since there will be need to know the revenues and the expenditure as well as get approval from the overall. The human resource department, on my part will come up with ways of evaluating the employees, recruiting, and doing the performance appraisal in conjunction with training and development of the employees. We shall develop efficient ways through which some of the employees will be communicated to the final strategy to prevent any rebellion. In the mean time, I recommend that the accounting and finance department to develop policies and procedures of developing our payment system level. In recruiting, I would like to recommend that we target the employees of our competitors. Through this we shall discover their strengths and weaknesses and take advantage to outwit them in the market. However, I would like you to note that the above recommendation will be very costly to the organization at the on set but once the strategies are implemented, I assure you the benefits derived will far much exceed the costs experience. In effect, it is a long-term plan, five years plan. In addition, the program will not be introduced once but rather in stages and therefore there is no course for alarm. I further recommend that caution be taken when implementation of the various strategies as they are likely to be met by opposition from some employees. Summary/Conclusions In as much as employee motivation may be expensive, it is advisable that we should look at the long-term perspective of the study. The study is very broad and not all employees may be satisfied. In this regard, the human resource management department should work on achieving most of the basic forms of motivation. This include ensuring a better working environment, treating each employee equally, appraising performance of the employees, if possible allow the employees contribute to the management of the company and ensure the reward scheme is very favorable. Meeting all these will ensure that at least 85% of the workers are satisfied with the organization. As a result, many employees will be attracted, the existing ones will be retained as in effect, increased productivity, market share and growth and expansion of the organization. Let organizations take care of the most valuable and delicate asset and this will minimize costs associated with breakdown of machines, ineffective and inefficient work force. References section Gunkel, M. (2006). International Management Studies. Country Compatible Incentive Design: a Comparison of Employees Performance Reward Preferences in Germany and the USA. Wiesbaden: DUV. Javitich, A. (2004). Motivating Employees. Retrieved on November 24, 2010 from http://www.javitch.com/Q/004.pdf Mathis, R.L., Jackson, J.H. (2008). Human Resource Management. 12th Ed. Ohio: Thomson Inc. McNamara, C. Basics about Employee Motivation (Including Steps you can take). Retrieved on November 24, 2010 from http://managementhelp.org/guiding/motivate/basics.htm Podmoroff, D. (2005). 365 Ways to Motivate and Reward your Employees Ever Day-With Little or No Money. Florida : Atlantic Publishing Group, Inc. Randhawa, G. (2007). Human Resource Management. New Delhi: Atlantic Publishers Distributors Werner, J. M., DeSimone, R. L. (2009). Human Resource Development. 5th Ed. Ohio: South Western Cengage Learning.