Analysis Report for New Product - Free Essay Example

Sample details Pages: 7 Words: 1972 Downloads: 9 Date added: 2017/06/26 Category Marketing Essay Did you like this example? ANALYSIS REPORT FOR NEW PRODUCT SUMMARY: The whole case study is based on the decision making analysis based on the new product operations. For this purpose I would prefer to understand about the market in which the product would be compete with the other products. These findings were made by Robert himself and the information in the questions available against these findings. We discuss them one by one and if any assumptions made there under. The Exclusive rights given by the Kokoa SA to Robert for selling and using their name. Such type of rights given by the company or manufacturer to their seller for enhancement and increase their sales. This right is provided for the period of 5 years and Robert must be paid some money in advance. The advance amount is not mentioned by Robert in his finding so according to the American royalty rates for food industry we studied that the upfront payment may be $200 per month and should be paid 5 years payment in advance that is $12,000. The second assumption we made for the inventory turnover period and Kg(s) of the chocolates. According to the study Robert wants to make orders after every two weeks and maintain the stock level for the four weeks in the first year of operations the stock level and orders sequence would not be made accurate as per the willing of Robert because the demand and supply rule of economics is applied. The market analysis made by the expert is based on the assumptions and estimations but the actual results show the greater variation. Such variation would be reduced at the end of the first year for the first year the assumption is made that is random growth in sales units of chocolates. Which makes the random increase in the Kg (s) which is imported from Switzerland? The third assumption is made for the order size which would be imported from the supplier according to the market survey and Robert’s given information, the order should be made after two weeks and must be enough for the next four weeks. In the first year of operations the sales units are vary randomly therefore, I made an assumption regarding the ordering the units that is in the current month order will be made for the following month requirements, and such requirements will be made on the assumptions which are made for the sales units. For the next year and thereafter the sales units are sold out of the same quantity as the market survey said. So, the minimum stock would be the same as Robert required. And the sales units will be the same as market survey state. Therefore, in the next year budgeted cash flow is not required any specific type of assumptions. The cost of the material is based on the currency of Switzerland that is CHF, and the supplier will give the 40% discount on the price in which the chocolates Kg sold out in Switzerland. Therefore, the actual price at which Robert will receive the material that is CHF 51 and the conversion rate is 1.06 then the price is 54.41 US dollars. The freight charges also be paid in CHF and conversion rate is used for the purpose of monthly and annual cash flows. The available capital for the new product is $100,000 and the loan facility is also available if necessary. But as per the monthly cash flows for the first year of operations there is no need any type of loan facility as the available capital is enough for this purpose. Robert also said about the available excess capital can be invested at the rate of 5%. The cash flows of the first year at the month level show that the company has excessive capital at the level of $30,000. I have made an assumption in respect of the investment of the amount of $30,000 and the return on such investment will be received in first month of following the investment e.g. February. In the first year the return will be made for 11 month as the assumption is made by me that the investment is made at the last day of the first month and it will made for minimum three years. AMOUNT WHICH WILL NEED TO GET GOING: There are many things which would be considered when a business is going to be start. There is a need to made feasibility study, if research is going appropriate and there is no uncertain indications then the development phase is started. In our case study, the research phase is completed now the operations of the company will be started. The study reveals that the available cash is enough for starting of the company’s food operations. The company has backup cash support from the bank of $50,000 at the rate of 8%. The initial expenses of the company are reasonable and there is no heavy machinery is required for the sake of starting the business and the main advantage which reduces the various ancillary expenditures which are necessary to start a business as he is an online seller. The available analysis made by Robert and the estimated monthly and yearly cash flows stated that the maximum cash which would be needed in the current situation if all other circumstances which would not lead to the circumstances change then the funds will be enough for the commencement of the food business that is $100,000. And the maximum expenditures will not be more than $50,000. So, for any uncertainty company has more than enough funds to control the circumstances. SENSITIVITY ISSUES: For the development or expanding an existing business, the organization either small or large, should develop the following things to reduce the effects of any uncertain happening. The sensitivity is the matter of product development which having the base of past research, present findings and future directions. If the new project is not following the planned directions or instructions then it will reduce the effects of the expected outcomes of the projects. Each analysis has some type of steps and components which must be followed during the working on them. Robert should follow, in start of the new product, demand and supply rule. I n this rule, production will be start at that time when the order will be taken by the company. For reducing the risk of loss in production, the system of production on the basis of orders is best in that environment. Another thing, which should be consider by Robert, that is, the online competitors of the company with the similar type of food products. He must evaluate the; Don’t waste time! Our writers will create an original "Analysis Report for New Product" essay for you Create order Prices Quality of product Quantity in each unit pack Quality of services Systems and technology used by the other competitor Influencing areas of operations Customer response Promotions and Schemes to attract the general public Advertisement plans In the regulatory prospective, Robert should get his product register, and must be taken a prior permit to start the selling of the new product. In order to achieve the expected results Robert must follow the following points in his market survey. UPFRONT PAYMENT FOR EXCLUSIVE RIHTS: Kokoa SA gives a right to use the name and its products under his own name in North America. Robert is allowed to use freely the right by paying an amount for a period of five years. It is the nature of royalty or purchasing an intangible asset. The amount of right must be paid in full for the period of five years. There is no clear information in the statements given by Robert about the terms and conditions of the contract made between both the parties. It is a small business operating in a limited area as the shipping is available only for North America. The company cannot exercise the right until the upfront payment clearance made by the Kokoa SA. In addition, the right gives Robert an oppo rtunity to purchase as much as the demand of the chocolates is increased in the future. There is no restriction regarding the purchase and time limits in respect of re-ordering. There is no specific law made by the regulation authority in respect of any royalty payment or license to use the products of the company of other jurisdiction except the prior approval and settlement. In our case, the Kokoa SA is a manufacturer of chocolates; Robert will purchase the chocolates and pack it under his own brand name then sell it. In US law, the right to use the other brand name is restricted but the use of products of other companies in making of company’s own product is not prohibited. It the company arise the liability by using the name of Kokoa SA, then the Law exists. So, there is only a contract can be made by the company in respect of the exclusive rights and its payment. In the market survey we find that the current rates in US of the similar contracts and rights made b y the other companies and competitors are from $150 to $400 in medium scale businesses. Our contract made by the Kokoa SA is on the basis of each order. The exclusive right settlement for five years is for $200 per month and for the whole period is $12,000 which is not refundable. If unexpectedly, the operations of selling and buying of chocolates need to stop then the payment of exclusive rights cannot be able to reverse by the Kokoa SA. CONCLUSIONS AND RECOMMENDATIONS: There are the following recommendations to Robert for the start up the new product. Market surveys based on the advertising the product and customer responses must be critically evaluate. Start small investment in respect of the new product Make up a portfolio of the products Acquire the business license for the new products Make a business plan for the new setup and running business too. And upload it on the website and advertise it accordingly in the manner which are most effective and enhance the productivity and customer response. I would like to suggest as a professional, to create a department for recording the whole operations of the business and report on them, which exactly represents the profitability of the company and new product. Always find the new ways to cover up the high cost and how to low the cost or alternative ways. During the planning, always overestimate the costs and expenses and underestimate the incomes and receiving. Always finds the ways to make the profit exponentially increase. For this, there are five drivers which are directly impact on the profits of the company. These are as following; Leads: how can the total number of customer increases day by day. Conversion rate: the average number of people who buy the product as the percentage of number of people who visits the website Average dollar sale: estimate the average dollar sale on the basis of conversion rate for the year. Average number of transaction Profit Margin: the profit percentage which the company earns by the selling of a single unit of its product. These are the evaluating factors which are having the influence on the profitability of the company. The ultimate conclusion of the research made by Robert for his new product in the portfolio of his company is good for his business only in the case, if he spends more money in the advertising campaign of the products and website at which the buying and selling take place. If the other things remain same i.e. economical conditions, exchange rate, inflation, stability in the foreign exchange market, political conditions, external factors which are directly affect the business in the North America and South America, then the expected and estimated cash flows monthly and annually are present the appropriate cash in and out of the company for the new products. For any uncertain happening the company has enough cash in backup to take care of the company’s future viability.

3rd Grade Science Fair Projects

The 3rd grade may be the first time students are introduced to science fair projects. Children ask questions from a young age, but this is a great time to begin to apply the scientific method. Introduction to 3rd Grade Science Fair Projects 3rd grade is a great time to answer what happens if... or which is better...  questions. In general, elementary school students are exploring the world around them and learning how things work. The key to a great science fair  project at the 3rd-grade level is finding a topic that the student finds interesting. Usually, a teacher or parent is needed  to help plan the project and offer guidance with a report or poster. Some students may want to make models or perform demonstrations that illustrate scientific concepts. 3rd Grade Science Fair Project Ideas Here are some project ideas appropriate for 3rd grade: Do cut flowers last longer if you put them in warm water or in cold water? You can test how effectively flowers are drinking water by adding food coloring. Youll get the best results with white cut flowers, such as carnations. Do flowers drink warm water faster, slower, or at the same rate as cold water?Does the color of your clothing affect how hot or cold you feel when youre outside in the sunlight? Explain your results. This project is easiest if you compare solid colors, such as black and white t-shirts.Do all students in the class have the same size hands and feet as each other? Trace outlines of hands and feet and compare them. Do taller students have larger hands/feet or does height not seem to matter?How much does the temperature have to change for you to feel a difference? Does it matter whether its air or water? You can try this with your hand, a glass, a thermometer, and tap water of different temperatures.Are waterproof mascaras really waterproof? Put some mascara on a sh eet of paper and rinse it with water. What happens? Do 8-hour lipsticks really keep their color that long?Do clothes take the same length of time to dry if you add a dryer sheet or fabric softener to the load?Which melts faster: ice cream or ice milk? Can you figure out why this might happen? You can compare other frozen treats, such as frozen yogurt and sorbet.Do frozen candles burn at the same rate as candles that were stored at room temperature? Ideally, compare candles that are identical in every way except their starting temperature.Research what dryer sheets do. Can people tell the difference between a load of laundry that used dryer sheets and one that didnt use them? If one type of laundry was preferred over the other, what was the reason? Ideas might be scent, softness, and the amount of static.Do all types of bread grow the same types of mold? A related project would compare types of mold that grow on cheese or other food. Keep in mind mold grows quickly on bread, but migh t grow more slowly on other food. Use a magnifying glass to make it easier to tell the types of mold apart.Do raw eggs and hard-boiled eggs spin the same length of time/number of times?What type of liquid will rust a nail the quickest? You could try water, orange juice, milk, vinegar, peroxide, and other common household liquids.Does light affect how fast foods spoil?Can you tell from todays clouds what tomorrows weather will be? Tips for Success Choose a project that wont take too much time to complete. Performing an experiment or making a model often takes longer than one expects, and its better to have extra time than to run out at the last minute.Expect a 3rd-grade project to require adult supervision or help. This doesnt mean an adult should do the project for a child, but an older sibling, parent, guardian, or teacher can help guide the project, offer suggestions, and be supportive.Select an idea that uses materials you can actually find. Some project ideas might look great on paper, but be difficult to perform if the supplies are unavailable.

La Dame and Cathy Ames Comparison Free Essays

In the poem â€Å"La Belle Dame Sans Merci† by John Keats and the story East Of Eden by John Steinbeck both authors similarly characterize women as merciless through the use of the literary technique of imagery. Both Steinbeck and Keats throughout their writings describe events and people in great detail. Both of the women are beautiful yet ‘wild’, put a man to sleep, and force someone to solitude. We will write a custom essay sample on La Dame and Cathy Ames Comparison or any similar topic only for you Order Now In the beginning of both the poem and story the authors give a very visual description of the women. They are both considered to appear on the outside as if they are â€Å"a faerys child† – beautiful. But when you look into their eyes a sense of being â€Å"wild† is within them. The wildness that the men see in their eyes foreshadows their merciless nature. The wildness alludes to and foreshadows the womens animalistic and heartless actions. In both storys the women seduce multiple men with their physical attractiveness in order to gain control of them and make the situation benefit them. The authors use imagery in their texts by explaining in detail the womens outstanding physical features in order to make the reader picture the women in the same way that the narrator does. Steinbeck and Keats effectivly project the images of the women into the minds of the reader. In the two pieces of literature both of the authors specify a scene using imagery in which the beautiful women make a man fall asleep in order to obtain what they want. In Steinbecks case it would be Cathy Ames overdosing Adam so she can sleep with Charles on the night of their wedding. While in Keats poem it is La Dame who slowly puts the unsuspecting knight to sleep so she can murder him. The women in these scenes commit awful acts but neither of them feel any remorse or conscience, which oes to show the women are truly merciless and have a â€Å"wild† nature. In Keats story he uses imagery in the knights vivid dream as a warning to show him all of La Dame’s past victims who had been lured in and killed before him. This shows that La Dame’s feeling of love are false and that she will continue to mercilessly hurt people. The authors uses of imagery in these scenes make the reader feel like they are in the story watching the horrible acts take place and make the reader lovingly hate the women for their cruel and clever actions. In both texts Steinbeck and Keats write a very visual scene about men leaving the eautiful women and cutting all ties to them because they realize that the women are fake, merciless and â€Å"wild†. In the poem written by Keats the knight wakes up as a lonely and â€Å"palely loitering† man because he realizes that if he continued to follow La Dame he would end up like all the other men who fell for her because she is â€Å"wild† and will never be tamed, she is merciless and all of her fealings were false. La Dame emotionally misconstrues the knight and leaves hime to live his life as a ‘dead’ person with his heart in a million pieces. In Steinbecks novel the whoremaster, Mr. Edwards, beats and then leaves Cathy to die because he feels that Cathy had constantly manipulated him and hurt him emotionally, physically and finically and he ever have to deal with her and be put through what he had been. Throughout each of the literary masterpieces both authors similarly characterize women as merciless through the use of the literary technique of imagery. Both of the women are beautiful yet ‘wild’, put a man to sleep, and force someone to solitude. Cathy Ames and La Dame were characterized as two despicipable women who inflicted pain and suffering upon others, to make up for the emotions that they cannot feel. How to cite La Dame and Cathy Ames Comparison, Papers

Briefing Paper Marking Guide - Big Data

Introduction In this briefing paper, the ICT topic Big Data will be reviewed from literatures. Big data is the new IT buzzword that refers to the voluminous data processed in different business processes in different industries around us. There is explosive growth of the volume of structured and unstructured data in last decades. In the early days of implementation of information technology in different kind of organizations had implemented databases for working with data related to their business processes, but in last few years, emergence of social media and ecommerce have accelerated the growth of data outside organization and from individuals. For example, over social media like Facebook, people uploads and shares heavy volumes of images, texts, videos from different parts of the world at the same time their location details, machine details etc. are also being circulated. Analysis of these type of data reveals several interesting information about peoples lifestyles, choices etc. and busines ses are very interesting for these type of information. Working with these kind of data using typical database management software and information technologies is difficult. Big data and technologies have given rise of a new dimension in this case. It covers all technologies that helps to address the volume and complexities of these voluminous data. (Madden, 2012) In this briefing paper, it will discuss about the technology, current research and trends on big data in details. The Problem As, it has been already told that, processing of volumes of structured and unstructured data, using traditional database management systems or data processing systems were difficult. This was the problem that led to the invention of big data concept and related technologies. (Madden, 2012) There is common confusion around the term big data, that is, whether it refers to technology or volume of data. When vendors use the term big data they generally refers to the technologies like processes and tools that helps in working with volumes of data efficiently. So, the term encompasses any collection of complex and larger data set that is difficult to handle by typical database management or data processing applications. It also covers up the collection of tools to support processing of such data through different kind of operations like searching, curation, sharing, transfer, storage, visualization etc. (Zikopoulos, 2011) Bid Data: Characteristics There are some characteristics of a dataset that makes it a Big data data set. Those characteristics are, A. Volume Volume refers to the quantity of data, generated from a process or system. The potential and value of a dataset is directly proportional to its volume. This characteristic is the first criteria to classify a dataset as big data or not. Even this concept has been reflected on the term Big data itself. (Marz Warren, 2014) B. Velocity This characteristic is related to the rate of generation of data or how fast data is getting generated or processed to provide desired outcome. C. Variety Big data takes data from heterogeneous sources into consideration while processing the same. Variety in data sets helps to analyze it from different aspects and in deriving different outcomes. D. Veracity Veracity of data sets refers to the captured quality of those. Veracity of a dataset plays significant role in the accuracy of the outcomes from analysis of the data sets. (Zikopoulos, 2011) E. Variability Variability refers to the levels on inconsistencies present in the data and that show up any time during processing. This may be problematic for data analysts. F. Complexity Managing the processing of big data, is a complex process by itself. It becomes more complex when data comes from heterogeneous sources and larger in volume. These kind of data is needed to be interlinked, correlated and connected. Otherwise it is difficult to work on these data. Big Data: Technologies Computation power and storage for larger datasets are not a serious problem now a days. Advancement in electronics and digital technologies have made these solutions more efficient, easily available and cheaper. This has helped in emergence of big data. There is a paradigm shift from computer architecture to the mechanisms in data processing. There is a growing demand for data mining and analysis applications for big data. (Barlow, 2013) There are wide range of tools and technologies that supports the concept of big data and analysis, processing of the same. There are technologies like crowdsourcing, A/B testing, data fusion etc. along with machine learning, natural language processing, time series analysis, integration, simulation, genetic algorithms, signal processing, visualization etc. Tensors are the representative of multidimensional big data. Tensor based technologies and computation methods like multi- linear sub space learning helps in this case. Other than that there are database related technologies, parallel processing support, search based application, distributed file systems and databases, data mining, cloud computing etc. and Internet that supports big data revolution. There are big data analytics that processes the big data and helps in finding out different patters out of it. These patterns gives critical insights into data sets. Storage is an important issue for big data. A proposed solution is distributed and shared storage. Storage area network or SANs, Networked Area storage or NAS etc. come into these categories. However, big data practitioners are not quite interested in these solutions. There are RDBMS based storage solutions for big data that is capable of storing petabytes of data. (Madden, 2012) All these technologies supports big data in analysis of data from web, analysis of network monitoring logs, click stream analysis etc. There are data science applications like simulations for massive scale analysis of data, deployment of sensors etc. Parallel database systems like Vertica, Teradta, Greenplum etc. are powerful but expensive and hard to administer. There are lack of fault tolerance levels in case of longer queries. Hadoop is a popular big data technology accepted worldwide. (Roebuck, 2011) Big Data: Process There are number of phases in data processing in big data. Those are explained as, 1. Data Acquisition Big data takes data that are evolving from different industries and scientific researches, demographics, social media and ecommerce. However, all data is not equally important for a particular goal so after collecting data, it will be filtered. Data are collected from systems, social media and numerous sources. There can be operational or transactional data, structured and unstructured data. When it comes to big data them all types of data irrespective or format and type are collected. Later on these data are filtered and compressed before processing. The most challenging part of data acquisition is, filtering out the unnecessary data. It must be done in a way so that useful information dont get discarded. Data science deals with numerous issues that helps to define different filters to ensure, accuracy and relevancy of collected data. (Marz Warren, 2014) For streaming data from online sources, it is not always possible to store and process those data to filter those later on. Rather it needs an on the fly approach to work on such streamlines of data from web. There are online data analytics applications and systems that helps in filtering and collected data from online streaming data. Next big challenge in to create metadata from acquired data. This is not easy. Meta data should give details about the sources and structure of data. There are metadata acquisition systems that can automatically record metadata without any human intervention. However, there are lots of things to do with metadata after recording those correctly. There is a pipeline for analysis of big data. Metadata is required in every stage of the pipeline. Thus acquisition of data refers to the collection of technologies, tools and processes of collecting data, filtering it and recording metadata of data at the same time without storing and processing data every time. 2. Cleaning and Extraction of information Data analysis needs some level of uniformity of data. Thus, after acquiring data, it is needed to be cleaned and ready for processing. Data analysis will require data in correct formant otherwise the results of the analysis will not be accurate and effective. It needs an information extraction process that will bring out the required information from the piles of data from heterogeneous sources. Then it should present the extracted data in a structured form. The process is technically challenging. For example, there are data like images and videos. Extracting information from these formats of data and presenting the same in structured format are really hard. A common misconception is, big data always provides truth. This is not the case all the time. The truthfulness of big data and analysis depends on these extraction steps. It depends on how effectively truth is getting extracted from raw data. There are different constraints on valid data and error models that are well recognized. However, till now there are many domain of big data where these constraints are still not available. 3. Integration, Aggregation and Representation of Data It has been already discussed that data comes from different heterogeneous sources. Those are no structured and in right format even. It is not possible to acquire and clean data then store the same in data repositories. There are processes like integration, aggregation of those data and then representing those in the right format to sore and process in future. Data analysis is a complex process. For large scale data analysis it is needed to have effective analysis and the process should be automated. In data analysis process, different semantics and data structures are needed to be expressed in correct formats that are readable by computers and can be resolved by robots. Data integration is important and there are additional works for making the data error free using automated system. There are different alternative solutions for storing data other than databases. Each of these alternatives have its own advantages and disadvantages. Designing database or correct storage solution is needed to be done very carefully. There are many decision making tools to provide assistance in designing databases. 4. Processing of Query, data modeling and analysis of data Making query in traditional databases and processing of query in big data, are fundamentally different. Big data contain volumes of dynamic, interrelated, heterogeneous data. These forms larger networks of interrelated data. There are higher level of data redundancy. These redundancies can be explored through validation, crosschecking etc. There are inherent clusters and these clusters reveals relationships among collections of data. (Roebuck, 2011) Data mining is a related topic here. It required, cleaned, integrated, trustworthy, easily accessible and effective data that can help in declarative query through data mining interfaces and computing environments. Big data supports provisions of interactive data analysis in real time applications. Scaling of complex queries is also supported. However, there is a problem with analysis of big data. That is lack of co- ordination in the systems that stores data, support SQL queries and analytics for performing non-SQL data processing, for example statistical analysis, data mining etc. 5. Interpretation Obtaining only results from analysis is not enough. It needs to explain or provide enough explanatory details about those results so that someone can interpret the results from analysis. There are visualizations used in this case. (Marz Warren, 2014) Challenges in Big data There are number of challenges in big data. Some of those are already explained in related contexts. Still, most prevailing challenges are, Heterogeneous sources and nature of data. Incompleteness in data. Problem with effective cleaning and extraction of data. Scale and volume of data. Timeliness of data. Privacy of data. (ene Polonetsky, 2013) Human collaboration needed in certain phases and lack of it in some cases. Lack of suitable and effective system architecture for big data only. Conclusion In this briefing paper, there is a discussion on an emerging topic in ICT, called big data. After the introduction, there is the problem statement that had given rise to the concept of big data. In the sub sequent sections there are discussions on different characteristics, technology etc. related to big data, finally a detailed description of processes in processing of big data. In the end there is a summary of challenges in big data. References Barlow, M., 2013. Real-Time Big Data Analytics: Emerging Architecture. s.l.:O'Reilly Media, Inc.. Boyd, D. Crawford, K., 2011. Six Provocations for Big Data, s.l.: SSRN. ene, O. Polonetsky, J., 2013. Big Data for All: Privacy and User Control in the Age of Analytics. Northwestern Journal of Technology and Intellectual Property , XI(5). Leskovec, J., Rajaraman, A. Ullman, J. D., 2014. Mining of Massive Datasets. s.l.:Cambridge University Press. Madden, S., 2012. From Databases to Big Data. IEEE Computer Society, 16(3), pp. 4-6. Marz, N. Warren, J., 2014. Big Data: Principles and Best Practices of Scalable Realtime Data Systems. s.l.:Manning Publications Company. Roebuck, K., 2011. Storing and Managing Big Data - NoSQL, Hadoop and More: High-impact Strategies - What You Need to Know: Definitions, Adoptions, Impact, Benefits, Maturity, Vendors. s.l.:Emereo Pty Limited. Zikopoulos, P., 2011. Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. s.l.:McGraw Hill Professional.