MAR free essay sample

A bald-headed black man strides into the meadow and stands before 57 students lined shoulder to shoulder. â€Å"If you’re satisfied with life, step forward. If not, step back.† Fifty-seven students take a step. â€Å"If your parents are divorced, step back. If they’re happy, step forward. If you don’t know, stay put† Forty students step. The rest stand still. Although I missed the opening dance of senior year, I learned important lessons by attending MAR, Culver’s weekend Multicultural Awareness Retreat. From cultural mash-ups to role-playing skits to the â€Å"Starting Line† game, 57 students and 15 faculty learned about living in a diverse world. When â€Å"Starting Line† began, we closed our eyes, and responded to questions about our social and economic background, our faith and sexuality. We stepped forward or backward when we believed our answers were social advantages or disadvantages. After 40 questions, still blindfolded, I figured I was in the middle. We will write a custom essay sample on MAR or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page But I wasn’t. I was third from front. I’d never realized my life was so good, at least compared to my friends’. We were told to look at who was in front of us, who was behind us, who was beside us. How different we are from each other, but how much we are the same. Culver’s 800 students come from 26 countries and 37 states, but the University of Michigan will be far larger, more diverse, more challenging. I will bring the acceptance from MAR to U-Mich community; I will be part of the rich diversity of campus life.

buy custom Descartes essay

buy custom Descartes essay Descartes portrays his own search for truth as the only knowledge. This includes the truth of mathematic and the metaphysical foundation of sciences. He argued that such knowledge could only be acquired through reasoning. However, the knowledge of physics can be gained from experience of the scientific methods. According to him, the rational pursuit of truth should be based on doubting every belief about reality. He developed a way to attain the real truth other than what he had acquired in the school. Truth that is obtained by reason is broken down into intuition elements which through a deductive process can result to clear truth. For example, he introduced metaphysical dualism which can be used to distinguish between the human mind and body to solve the mind-body problems. Can philosophy be taught? According to Descartes, it cannot be taught but can only be studied and learned. Philosophy begins from a wonderment of the Being of the universe which is the basic problem of philosophy. It actually starts from the self. According to Socrates, philosophy is learned from the act of persistent questioning of authorities and public figures in order to discover the truth of a good life. Socrates was much interested in ethics; he considered the principle of self-knowledg as the adequate condition to a good life. His paradox of an unexamined life is not worth living was meant to highlight the importance of knowledge before anything else on earth. Logic is a branch of mathematics which is a sub set of philosophy. Mathematical logics employ the use of operations which make use of true or false parameters other than numbers. Mathematics is usually a good model to whoever wants to have a clear and logical reasoning because the rules of logics are properly designed, therefore, any well designed and valid mathematical deduction is usually correct. It cannot be realistic to believe that our thought processes are as clear as mathematical proofs because not all thoughts are properly designed to tackle basic human problems. The cogito ergo sum is Descartes most celebrated contribution to the history of ideas. The meaning of this is that someone is wondering whether or not they exist, in and or itself; proof that something an I exists to do the thinking. According to Ren Descartes, the reason why human beings doubt that they have a body is because of the failure to apply their brains to work i.e. not thinking. The message actually depicts that whatever a person thinks, that iss what he is. And if a person believes there is external world, there is, if not there isnt. In Meditation II, Descartes addresses a piece of wax as he melts it in the fire. His main intention is to demonstrate how the same wax changes all its eight characteristics upon exposure to some source of heat. He illustrates that despite the piece of wax still remain even after its change of form, it is nothing appealing to the five senses. It remains to concede that I do not take hold of what this wax is although the imagination i perceive it through the mind alone. But I need to recognize that the insight of the wax is neither a touching, nor a seeing, nor an imagining. Dreams are perceived as external object openly through the concept of our own minds and the images are the result of the external object we perceive. He complements that there are no precise ways of differentiating dreams from waking experiences and hallucinations. My view is that a persons dream is a clear picture of what the mind can see. The method of hyperbolic doubt is the practical and excellent method that ensures both provable and true statements are deductively demonstrated. It actually resembles modern scepticism in the questioning of the most accepted beliefs and norms. Buy custom Descartes essay

Cantonese opera Essay Example for Free

Cantonese opera Essay Most foreign people know what Bejing opera is, but Chinese national Opera has a long history and 275 species of Chinese operas have been saved, there are a wide range of operas were not extended yet, Cantonese opera is very popular in the south of China, many Chinese people prefer Cantonese opera to Beijing Opera. The biggest difference between Beijing Opera and Cantonese Opera is language, the Beijing Opera use Mandarin, the Cantonese Opera use Cantonese. Cantonese opera is local opera in Han Dynasty is formerly known as drama or Guangdong opera from the Southern Opera. Cantonese opera began to appear in Guangdong, Guangxi from AD 1522 to 1566 (Ming Dynasty Jiajing) included singing, read, hit musicians ,soundtrack, stage costumes, The abstract body performing arts. Each Cantonese opera role has its own unique costumes dress. The initial performance’ language is Zhongyuan phonological, also called matshed Mandarin. At the end of the Qing Dynasty, the intellectuals changed the opera language to Guangzhou language in order to facilitate their revolution, also aimed to make Cantonese understand easier. Cantonese opera ranked into national intangible cultural heritage on May 20, 2006. The UNESCO add Cantonese opera in the human intangible cultural heritage list on September 30, 2009. Cantonese opera originated in the Chinese folk songs which called Qi folk songs, the earliest folk songs can be traced back to the â€Å"Book of Songs† from pre-Qin Dynasty, but this is the common origin of all Chinese opera, such as Beijing opera, Cantonese opera, class opera, Shanghai opera, Shaoxing opera, and Huangmei opera. The stage art style is impressionistic. The scenery is simple, the play provides situational by virtual performance program, or write captions on board like â€Å"riverside†, â€Å"alpine† instead of stage background. Performances who in the city called â€Å"GD-HK† learned drama, opera and movies to improved their performance and made theme reflect contemporary life. Later, people Change falsetto into true voice in Cantonese opera. The men sing like relatively stable, low; women sing like very delicate and mellow. As some Cantonese opera are very favorite in new media, these famous Cantonese opera has recomposed in movies, TV series, dramas, and music. For example, â€Å"Princess Chang Ping† Purple Hairpin â€Å"† Peony Pavilion â€Å",† Gemini worship the Moon, â€Å"† The Reincarnation of Hongmei mind â€Å"† Butterfly and Red Pear â€Å"Hanada Baxi Xiangluo Otsuka â€Å"Red Cherry broken heart† â€Å"A Dry White Begonia Red,† â€Å"A Dream of Red Mansions† the Sanxiao marriage â€Å"† White Rabbit â€Å"Guizhi complain† Dou E Yuan â€Å"(also known as† June Feishuang â€Å"or† June Snow â€Å"), also included the first national intangible cultural heritage â€Å"Butterfly Lovers†. Cantonese opera. (2017, Jan 10).

Bryan Forbes The Stepford Wives Movie Review Example | Topics and Well Written Essays - 2250 words

Bryan Forbes The Stepford Wives - Movie Review Example The TV show Desperate Housewives clearly references the film in its depiction of one of the main characters, Bree Van De Kamp, due to her 1970s-era standard of wifely and motherly perfection. But while the novelty of the concept of wives being turned into robotic versions of themselves may be exactly what is needed to affirm the 1970s genre of horror cinema-as evidenced by Carrie, The Exorcist, The Omen, and many others-the social implications of the film were not always welcomed by concerned parties. In particular, the undeniable strengthening of the feminist movement in America in the 1980s that gave women even louder voices in societal issues did not find much significance in The Stepford Wives, despite the clear commentary on the prevalent patriarchal norms being followed by general American societies. The analysis then would be centered on this issue, from the communication of female-related concepts and the subsequent interpretation made; the statement about women, after all, is much more pronounced in this text than in the author's previous work, Rosemary's Baby. The film is quite curious from the very beginning, with the ominous perfection of a scene showing a young couple, Joanna and Walter, moving their family from busy, noisy New York City to the peaceful suburb of Stepford. As many horror stories would have it, the idyllic situation slowly starts changing, mainly due to the peculiar behavior of some of the wives in the community. They were strange in their demeanor and ideals, akin to TV portrayals of perfect mothers and wives who spent all their time cooking and cleaning with nary a hair out of place. Subsequently, the transformation of Joanna's friend Bobbie and Joanna herself reveals how the community is controlled by the men, who apparently discard their wives for mechanical look-alikes that would function exactly as expected. But the image created by the film with regard to the epitome of womanhood-specifically in women's roles in the home, such as cooking, cleaning, and maintaining an appearance that conforms to standards promoted by media-is largely within the stereotype of the Caucasian female married to a Caucasian man of stable economic means, enough to provide for a home equipped with the necessary elements that would allow for the keeping up of the image. Children would not be more than two, and are well-dressed and well-behaved. Husbands would leave home and return at very specific times, during which the wife must be ready to attend to his every wish. As this cannot be possible in the frenetic environment of cities and urban addresses, it essentially finds its setting in the suburbs of America, taking from the afterthought to the phenomenon of urbanization, which is the contrary suburbanization. Joanne and Walter's move from New York to Stepford is typical of this occurrence, as more and more problems become associated with living in cities. The growing concern for less substantial economic costs and adhering to a lifestyle denoted by family and community time is at the core of suburbanization, which led many to move back to the suburbs. One of the major influences of this change is "the preference for

Organizational Change Essay Example | Topics and Well Written Essays - 250 words - 6

Organizational Change - Essay Example Failure to anchor the changes on corporate culture makes the change process to fail. Organizational culture is very critical to the success of the change process. As a result, when the management fails to incorporate the organization values and believes, they end up failing to implement changes. One of the major success pillars of change is the understanding and spelling out of the impact of the change process on the people (Burke, 2010). This enables the management to engage all the affected personnel. Effective leadership during the change process provides a base for the change process (Burke, 2010). This is because they are able to communicate effectively to the subordinates and act as role model to them. One of the companies that failed to implement change is Avon. The company failed because some leaders were not in support of the process. In addition, the employees were not involved in the change process. Lastly, there were no clear guidelines to implement the change

The Kite Runner Essay Example for Free

The Kite Runner Essay When one makes the transition from child to adult, they must make the decision to either adopt the traits they have developed, or to see fault and change the problems before the time to do so has past. It takes strength to use the positive traits one possesses, and it takes even more strength to assess the negative traits and emancipate the positive ones. Alan Alda (American actor) once said that â€Å"You have to leave the city of your comfort and go into the wilderness of your intuition. What youll discover will be wonderful. What youll discover is yourself. † Before death, a person needs to break their boundaries, and find the security of knowing their identity, otherwise one could go through an entire life, learning all they could about life; but forgetting all about their self. Another key factor influencing our personality is our environment. A society constantly changing for the worse is no place for a person to grow or reside. In Khaled Hosseini’s â€Å"the Kite Runner†, Afghanistan is a place of ethnic differentiation, civil war and darkness. Amir, Baba, and Hassan’s identities, are all examples of different ways a person’s personality and conscience could develop in this oppressive time in Afghanistan’s history. Amir finds peace in who he is through great mental anguish and dangerous decisions, Baba’s weak traits are discovered, and Hassan manages to preserve his Good Samaritan lifestyle whilst fighting off the turmoil’s of being a Hazara boy. The Kite Runner focuses mainly on the themes of identity and self-actualization. Amir from the beginning of the novel was never perfect in the eyes of his father, Baba. During Rahim Khans visit early in the story, Amir overhears Baba speaking about how Amir is weak and disappointing, that â€Å"a boy who cannot stand up for himself becomes a man who cannot stand up for anything. †(24) This is an important quote, because it first introduces Amir’s most dominant trait through his childhood, his cowardice. Baba’s reluctance to praise Amir stems from Baba’s disbelief in his courage. Amir quite often was defended by Hassan in times of trouble, whether the cause was Assef or not. Then when it was Hassan who was in need, Amir was over shrouded by his fear. Amir had felt guilt until his arrival in Pakistan. â€Å"â€Å"That was a long time ago, but it’s wrong what they say about the past, I’ve learned, about how you can bury it. Because the past claws its way out. Looking back now, I realize I have been peeking into that deserted alley for the last twenty-six years. † (1) Amir made the decision to save Sohrab from the Taliban (Assef) was the moment in his life, where he finally felt at peace. Saving Sohrab was his way of gaining up the courage to save Hassan. After the rescue of Sohrab, Amir’s conscience had cleared and he could finally live his life. Amir’s passion for literature was another example of his self-actualization. He would always read to Hassan, due to Hassan’s illiteracy. Amir wished in the future to pursue a degree in English, but this idea was hastily dismissed by Baba and Amir began growing to a man with even less confidence. Amir pondered the thoughts of his father resenting him, which at a young age is a terrible burden for him to hold. The evidence of this hate was displayed in Amir’s face, and as a young child, he is not intelligent enough to realize his father’s love, and it bothered him greatly. Rahim Khan seemed to be the only adult in Amir’s life who supported the idea of his future in literature. He would read, and show great interest in Amir’s story’s; as well as instill hope in Amir with positive feedback. Rahim Khan was the spark that ignited the ever burning flame of Amir’s literary passion. To the reader early on, Baba is the epitome of a man. He is introduced as a man that will stand up for his loved ones, whether it’s a life or death situation. He speaks of Amir like he has no courage whatsoever, which gives the reader some idea of how much Baba values doing the right thing. When Baba and Amir flee Kabul, Baba risks his life to prevent the rape of a woman he doesn’t even know. This drastic act of courage and compassion for his fellow man is inspiring and sets the moral bar for Baba very high. When Amir arrives in Pakistan, he is distraught at the news he hears from Rahim Khan regarding Hassan being his half-brother and Baba’s son. Amir now knows, that the pain he felt from Baba’s resentment was purely a byproduct of the pain Baba feels about Hassan. Baba’s character takes a moral blow in the view of the reader, and to many it never recovers. After hearing of the news, Amir’s betrayal of Hassan is now very reminiscent of his father’s; showing more similarity between them than known before. Amir now knows, Baba’s resentment, was him showing he is too weak to be known as the man who slept with a Hazara. Baba tells Amir in chapter 3 that â€Å"there is only one sin, only one. And that is theft. Every other sin is a variation of theft. †(19) it’s ironic that Baba says this because he stole Ali’s honor, Amir’s right to a brother, and Hassan’s identity. While all the drastic self-realization of the characters was taking place, Hassan, managed to keep his same and ideal identity. Hassan was righteous and strong, the ideal symbol of the Muslim Religion and every other; to be pure and good. Amir’s resentment towards Hassan after his rape by Assef did not faze Hassan a bit. Hassan was almost too pure to feel any remorse towards Amir, they grew up together, and Amir was his best friend. Even after Amir had lied to Baba to expel Ali and Hassan from their home, Hassan felt no different towards them. He cared for their home while they resided in America; he even stayed in his and Ali’s same hut rather than the house to show respect. His loyalties to Amir and Baba stayed faithful until his death in the very home that he was practically raised in. He said he was caring for it for a friend, and the Taliban called him a liar like all Hazara’s, and killed him in the streets, as well as his wife. Amir might have made different choices in his life had he not plotted to make Hassan and Ali leave, but amidst the cowardice shown by both Amir and Baba, appeared a boy with the morals of an angel. No one can live life without realizing their true identity, and as the story ends; the characters take with them new traits, good or bad. Amir realizes his purpose in life, and he saved a life in the process of discovery of his own identity. Baba is reviled to be similar to a great dam with a crack, viewed as great and powerful, but in turn; the final view of him is weaker than the original opinion of the reader. Hassan through turmoil, conflict, and resentment, stayed true to himself and stayed loyal till his death. One could learn all there is to know, but without knowing their true identity, it is a life not lived.

The Beast In the Cave Essay -- Literary Analysis, H.P. Lovecraft

â€Å"You’ve just crossed over into The Twilight Zone† says Rod Serling before every episode of The Twilight Zone. A show that leaves it’s viewers in a macabre state. Instead of drawing a conclusion like most shows, the show usually ends mysteriously. It utilizes similar elements as other short half-hour shows, but goes about it in a different way. This outlandish style is seen in literature, more specifically short stories, as well. Even though other short stories employ the same literary devices, â€Å"The Beast In The Cave† by H.P. Lovecraft is uniquely mysterious because of the story’s suspenseful plot, compelling diction, and, most important, overshadowing theme. In â€Å"The Beast In The Cave†, H.P. Lovecraft develops a suspenseful plot in order to build tension throughout the story that inevitably leaves the reader feeling disturbed and the story hanging. The plot itself is seems simple, but is complicated at the same time. Victoria Nelson talks about how Lovecraft’s stories tease the reader â€Å"with the tantalizing prospect of utter loss of control, of possession or engulfment, while remaining at the same time safely contained within the girdle of a formalized, almost ritualized narrative†. With â€Å"The Beast In The Cave†, the protagonist faces only one conflict throughout the story making it a simple plot line; however, the predicament he is in provides the complexity and tension that Lovecraft creates in other stories as well. The complexity of the plot starts when the reader is introduced to a man lost in a cave and his source of light goes out and continues when the man realizes that â€Å"starving would prove [his] ultimate fate† (1). Readers get a sense of hopelessness the man is feeling, and this is where the tensions begins to build. Alt... ...s. Design215 Inc., 2005-2011. Web. 10 Dec. 2011. . Fahy, Thomas Richard. The Philosophy of Horror. Lexington, KY: University of Kentucky, 2010. Print. King, Stephen. â€Å"Gramma.† Skeleton Crew. New York: Signet, 1986. 464-494. Lovecraft, H.P.. â€Å"The Beast in the Cave.† The Transition of H.P. Lovecraft: The Road to Madness. New York: Ballantine Books, 1996. 1-6. Nelson, Victoria. The Secret Life of Puppets. Cambridge, MA: Harvard UP, 2001. WNC Database. Web. 7 Dec. 2011. Tibbetts, John C. The Gothic Imagination: Conversations on Fantasy, Horror, and Science Fiction in the Media. Basingstoke: Palgrave Macmillan, 2011. Print. "The Use of Force--William Carlos Williams (1883-1963)." Classic Short Stories. B&L Associates, Bangor, Maine, U.S.A., 1995-2007. Web. 10 Dec. 2011. .

Google: Human Resource Strategy Essay

Developing an effective human resource strategy to manage an organization’s human assets requires considering employees as investments. Such an approach helps ensure that HR practices and principles are clearly coordinated with the organization’s overall business strategy. It also forces the organization to invest in its best opportunities and ensures that performance standards are met. Google is one company that has reinvented their approach to human resource strategies. Google has renamed their human resources to people operations. Several human resource strategies have made Google what it is in today’s market. The top HR strategies that have made Google a success include strategies in management, hiring, and recruitment, training and development, compensation and their 70/20/10 rule. The rationale behind each of these strategies is easily revealed through their overall business strategy. Keywords: human resource strategies, people operations Google: Human Resource Strategy Google has renamed human resources to people operations. This encourages employees to participate in running the company and building effective teams. One philosophy that Google focuses on is what they consider people management when it comes to human resource strategies. Sullivan (2013a) reveals a top priority for Google. They believe that innovations come from people and you cannot maximize innovations unless you are capable of recruiting and retaining innovators. Google uses a human resource strategy called databased decision-making strategy. This human resource strategy has been highly successful in attracting innovators and managing them within the company. â€Å"Almost everyone has heard about Google’s free food, 20% time, and wide range of fun activities but realize that each of these was implemented and are maintained based on data† (Sullivan, 2013a). The following will be a  brief description of some human resource strategies that Google uses for their people management practices as it relates to a data-driven approach. Management HR Strategy Human resource managers at Google have determined that great managers are essential for top performance and retention. One practice they use to keep manager’s performance high is to have their employees rate managers twice a year. The researched data proved that Google could maintain its success not by superior technical knowledge but by one-on-one coaching with management, which included expressing interest in employees and providing personalized feedback to those employees. Google also uses the PiLab. The PiLab conducts applied experiments within Google to determine the most effective approaches for managing people and maintaining a productive environment (Sullivan, 2013b). This data driven strategy has provided results to human resources on the approaches of how to be successful in their HR strategy. Hiring and Recruitment HR Strategy Google is also unique in its strategic approach to hiring because its hiring decisions are made by a group in order to prevent individual hiring managers from hiring people for their own short-term needs. They are explicitly seeking to attract the kinds of people to the company who will be successful in their open, collaborative culture (Zhong, 2011). Hiring the right people is a key HR strategy at Google. Their retention rate and turnover data proves that the organization has been successfully able to attract, retain, and motivate a younger generation of workers who would otherwise be more apt to leave an organization. Training and Development HR Strategy Another important HR strategy for Google is in its training and development program. Google employees are offered tremendous opportunities to learn and grow. Some of the professional development opportunities include classes on individual and team presentation skills, content development, business writing, executive speaking, delivering feedback, and management and leadership (Lawler, 2014). Google pays special attention to training for engineers due to their level of importance to the success of the company. They want to ensure the engineers as well as other employees have received  the mandatory training and development sessions for a minimum of 120 hours per year. This is about three times the industry average in North America of 43 hours per year. Despite the cost to Google, this is an essential part of their HR strategy and contributes to their overall business strategy. Compensation HR Strategy Google has an unusual HR strategy when it comes to its compensation structure. Google is often known as one of the most sought after and yet one of the most underpaying employers in the industry. Despite this, employees are still attracted to working their dream job at Google. More frequently than not employees are attracted to the support system, that can help them create anything rather than monetary returns. Therefore, the work hives at Google have day care and elder care centers, have spa and hair salons, car wash and oil check facilities, and virtually everything that a technology obsessed geek would like to worry least about, in the form of an all-inclusive liberal benefits package, but the actual take†out cash component is negligible (Sullivan, 2013b). Google offers all employees unlimited sick leave as well as 27 days of paid time off after one year of employment. This is highly unusual for most organizations but Google believes in an even work live balance and keeping their valued employees returning to work happy. 70/20/10 Rule HR Strategy Another important HR strategy for Google is the 70/20/10 rule. This HR strategy ensures creativity remains a top priority at Google. Employees are required to divide their time into the following three parts: 70 percent is spent on search and advertising 20 percent (1 day of the work week) on a project of their own choice 10 percent to far-out ideas  HR believes that with this strategy, employees will remain motivated and committed to innovation and novelty and therefore production will increase. Because of this rule, some very successful ideas have emerged such as Gmail, and Google Talk. HR Strategy Rationale Google is continuing to grow every year, and some of these HR strategies are  becoming more challenging. Behind every strategy comes rationale for using it and how it provides continued success within the company. It is important to note that HR strategies, activities, and policies are actually driving Google’s corporate business success. Google’s HR strategies reveal that the company’s approach helped in increasing employee productivity. The average Google employee generates more than $1 million in revenue each year (Lawler, 2014). The following will give rationale for each strategy previously discussed. People Operations Rationale People operations focus on the idea that HR is not just administrative functions but ideally focuses on the meat of the company. The meat of the company is people or human capital. Human capital is the stock of knowledge, skills, and abilities among employees that provide economic value to the organization (McShane, 2013). This rationale was developed as part of the overall business strategy at Google. Google takes pride in their human capital by ensuring they are part of the team and actively involved in the decision making process (Bock, 2011). Human capital can also consist of employee capability, employee satisfaction, and employee sustainability. These three components of human capital are considered an essential part of organizational growth. Employee capability is the creativity and knowledge that an employee contributes to the organization. Employee satisfaction refers primarily to an employee’s emotional or affective state. An employee’s overall satisfaction relates positively to job satisfaction, reflecting the difference between what the employees want from their job and what they perceive it as offering to their overall success within the organization. If employee satisfaction is high, then an employee’s commitment to the organization is high which will result in a greater retention of that employee. Management Style Rationale The main philosophy at Google that backs up their management style is open door policy. Top management leaves their office door open in order for workers to feel free to come and talk directly versus phone or email communication. The official policy states in part  Google desires to maintain a friendly, cooperative atmosphere between  employees and all levels of management. Consequently, the company provides opportunities for you to express yourself without recrimination. If you have a problem with your manager that, despite your mutual efforts, cannot be resolved, you may discuss this with the next higher level of management or with human resources. While Google prides itself on being an open organization where you can approach any member of management directly, we recommend you first attempt to resolve the issue through your manager or human resources (Gupta, 2009). This open style of management allows better communication between staff and management, and can help ensure staff is more productive at solving problems that may arise. Hiring and Recruitment Rationale The rationale for using small teams to do all the hiring for Google is quite simple. These teams seek to recruit and hire the most qualified individuals out of thousands of applicants. The hiring decisions are made by a team in order to prevent individual hiring managers from hiring people for their own short-term needs. Human resources also approach recruiting scientifically. They have developed a way to predict which candidates have the highest probability of succeeding after they are hired. This rationale saves time and money, and provides a greater success rate for new applicants turning into long-term employees. Training and Development Rationale A properly trained employee is an essential part of maintaining a successful organization. Research has shown that a majority of people learn by on the job training, including a hands-on approach. Google has adopted this rationale for their training programs by not focusing only on classroom training but by placing emphasis on hands-on training. Google has increased discovery and learning through project rotations, and learning from failures (Sullivan, 2013a). They believe a well-trained employee will increase production as well as increase the company’s reputation. As productivity and reputation rises the profits will also rise. Compensation Rationale Rationale behind the lower compensation packages offered at Google has to do with the importance of work/life balance philosophy. As previously discussed Google places a significant amount of importance on the benefits offered  instead of the actual monetary salaries. Money is important to survive but Google also wants to make everyday life easier for employees by offering in house daycares, and free meals along with many other benefits. If they can keep the employees from spending their work time performing life chores, then they will increase productivity by improving the employee’s job satisfaction. 70/20/10 Rule Rationale This concept allows the employee to grow in their abilities as an employee and as a person. By allowing this concept, Google is reinforcing its relationship with its staff and developing brand strength externally. Good news spreads quickly. As a happy employee who enjoys spending time creating their own projects, shares with outside friends and family, this increases customer satisfaction for the brand name of Google. This rule is part of Google’s HR strategy as well as their business model strategy. Analysis of HR Strategy Google has developed an effective HR strategy that does align with their overall organizational strategy. One of the biggest parts of their organizational business strategy is to focus on people. Google executives have learned that continuous innovation cannot occur until a firm makes a strategic shift toward a focus on great people management (Sullivan, 2013b). By shifting to this idea of hiring great people versus hiring mediocre people, the business decisions will reflect their knowledge, skills, and ability. Executives at Google have a clear understanding of strategies in the human resource department, and have a clear understanding of how they effectively tie into the overall business strategy of the company. One thing they have done successfully is to focus all business decisions on data and analytics. This is evident in the HR department with how they make their decisions. A mission goal that they highlight is to bring the same level of rigor to people-decisions than they do to engineering decisions (Sullivan, 2013b). Reinventing the HR strategy at Google has been a success. Top executives coached effective ways to measure human resources so they can improve in  this area. One deficient area Google was able to recognize was the areas of predictive analytics, statistics, and mathematics that would be needed to transition into the databased model of a HR strategy. Change can be difficult, and some HR managers are not open to this idea of a data based approach when they consider HR to be a people based function. The transition to the data based approach of HR could have been introduced in a more effective manner among current HR managers at Google. When this concept was first introduced, it was done ineffectively. Management decided to change the strategy and without warning made it effective. Open communication is key to effective strategies within an organization. A change of this magnitude needs to be tested, and employees should be coached and eased into before it can be an effective change. HR’s Effectiveness and Metrics HR metrics is important because it allows organizations to make the connection between the value of what HR is doing and the outcomes of the business. One of the key metrics within Google that make their HR strategies effective is the revenue factor. It indicates the effectiveness of company operation with the use of the employees as their human capital. Without this key metric, human resources would be the same as any other organization. Changes and Alternatives After researching Google, it is hard to think of many needed changes to their already effective HR strategies. I would recommend to HR and management that they continue to stress the importance of training and development with all current employees as well as any new employees. I would also recommend that HR take full advantage of continuing to implement the job rotation strategy. This will provide employees insight to each department, and the job duties of other employees as well as the different jobs available at Google. Call to Action In order to implement these recommended changes it will be necessary to call to action all management and the human resources department. One way for training and development to remain a top priority to all employees is to develop a reward system for completing the required number of hours of training, and additional rewards for extra training in the employees’ area of expertise. These rewards should be monetary. Human resources should develop a rotation schedule with the help of the employee’s on-site manager. Once the employee is properly trained in their area of expertise they should then be rotated through each department that works directly with their department. This will not only help employees learn about the other departments but they will also gain an understanding of the duties of other employees. This will make requests from other departments less stressful to all employees, as they will know what it takes to generate and submit that information. Conclusion Google has placed great emphasis on the people within their organization and made these valued people part of their HR strategies. This strategy has been highly successful to this organization. Many organizations could benefit from the simple HR strategies that Google has focused on in their company. Sometimes it is not what you know but whom you hire. This is a common philosophy at Google as they strive to continue to hire great people to do a great job. References Bock, L. (2011). Yale Insights. What’s the Google approach to human capital?. Retrieved August 11, 2014, from http://insights.som.yale.edu/insights/whats-google-approach-human-capital. Gupta, A. (2009). Strategic HR Planning at Google Inc. Scribd. Retrieved August 17, 2014, from http://www.scribd.com/doc/13286610/Strategic-HR-Planning-at-Google-In. Lawler, E. (2014). What Should HR Leaders Focus On In 2014?. Forbes. Retrieved August 17, 2014, from http://www.forbes.com/sites/edwardlawler/2014/01/15/what-should-hr-leaders-focus-on-in-2014/. McShane, S. L., & Von Glinow, M. A. (2013). Organizational Behavior Emerging Knowledge Global Reality. (6th ed). New York: McGraw-hill Irwin. Sullivan, J. (2013a). How Google Became the #3 Most Valuable Firm by Using People Analytics to Reinvent HR. Retrieved from http://www.ere.net/2013/02/25/how-google-became-the-3-most-valuable-firm-by-using-people-analytics-to-reinvent-hr/. Sullivan, J. (2013b). How Google Is Using People Analytics to Completely Reinvent HR. TLNT. Retrieved August 19, 2014, from http://www.tlnt.com/2013/02/26/how-google-is-using-people-analytics-to-completely-reinvent-hr/. Zhong, R. (2011). Human Resource Management Issues at Google. Human Resource Management Issues at Google. Retrieved August 15, 2014, from http://www.slideshare.net/rachelzhong814/human-resource-management-issues-at-google.

Statistics Coursework

1st Hypothesis – For my first hypothesis I will investigate the relationship between the number of TV hours watched per week by the pupils against their IQ. I am going to use the columns â€Å"IQ† and â€Å"Average number of hours TV watched per week† taken from the Mayfield high datasheet. I think that there will be a relationship between them and will attempt to reveal it. 2nd Hypothesis – For my second hypothesis I will investigate the relationship between â€Å"Average number of TV hours watched per week† and â€Å"weight (kg)†. I think that there will not be any major relationship between as they will not affect each other greatly. I will present my analysis and the results in graphs and tables and explain the results using the correlation of the graphs and arrangements of the figures. I will select a number of pupils to base my data on and will use random sampling to ascertain the correct number of male and female pupils needed to make the investigation fair. Stratified Sampling I do not want to use all of the data in the database for my analysis so I will need to take a sample of the number of people in the school. I would like to take about 10% of the overall figure. I will also need to use stratified sampling to make it an equal proportion of the number of males and females in the school to make it fair. The total number of pupils at the school is 813 so I will need to take 10% as my number, 81.3 is rounded down to 81. The overall ratio for boys and girls in the school is: 414:399 Now I will need to do my sampling Males = 414 multiplied by 81 = 41 813 Females = 399 multiplied by 81 = 40 813 Random Sampling Now I have the number of samples I will need to select the samples I will be taking. To do this I will use random sampling. I will take random samples until I have 81. I can do this on Excel using the following formula: = round(round()*120. Once I have gathered the samples I am ready to start analyzing my samples. Analysis Hypothesis 1 Males The first thing I need to do in my analysis is to analyze my graphs which are the source of the investigation. I have created scatter graphs to show the relationship if the two data sources for my first hypothesis. I have separated them into male and female graphs as there is a separation in the numbers. First male scatter graph: This first graph presented a bit of a problem. There was an anomalous result that affected the trend line and the scale of the graph. I decided to create a new graph that didn't include that 1 piece of data. This way it would help me to analyze the rest of the data. Second male scatter graph: This graph showed the data much clearer and I could then start analyzing it. There is no correlation between the 2 sets of data. This means that it is unlikely that there is a relationship between IQ and Average number of TV hours watched per week. In this it may be that my hypothesis is incorrect. There is only a very slight gradient on the trendline that leans towards a negative correlation, but the gradient is not steep enough to draw any conclusions about the relationship between the two sets of data. I will have to use the cumulative frequency graphs and boxplots to see if any conclusions can be made. Cumulative frequency graphs for IQ and Average number of TV hours watched per week: From these graphs I could create box plots and compare the two sets of data. Before that I analyzed the cumulative frequency graphs to draw initial conclusions. The majority of the IQs for males are between 90 – 105, this shows that the data is quite spread out as this section only covers a small area of the graph. For the TV hour's graph, again the data is spread among 1 main area; in this case it is between 5-25. There is almost a straight line near the top of the graph; this shows that there is likely to be some anomalous results and 0 pupils in between that result and the main bulk. Now I will create box plots so I can compare the two graphs together. Box plots for cumulative frequency graphs of IQ and average number of TV hours watched per week: (for interquartile ranges look at copies of graphs at the back) From the box plots I can see that the data spread is relatively the same apart from a possible anomalous result in the TV hour's data. This similarity is the reason why the scatter graph had no correlation and therefore no relationship. This means that my hypothesis is wrong. Hypothesis 1 Females Again I will start with the scatter graphs. As with the male graph I had an anomalous result that spread out the data and scale down the graph so most of the relevant data couldn't be analyzed. I then did another graph without that specific piece of data. Scatter Graphs 1 and 2 to show the relationship between IQ and average number of TV hours watched per week for Females: As you can see on both the graphs there is no correlation between the two sets of data. This again means that my first hypothesis is unlikely to be correct. There is only a slight gradient on the trend line which is not steep enough to draw any conclusions from it. There is another anomalous result on the graph but it doesn't affect the trend line and my conclusions so I left it on the graph. I will now crate cumulative frequency graphs to see if they can help me to draw conclusions. Cumulative frequency graphs for the IQ and number of TV hours watched per week: I will now analyze the graphs before drawing box plots to compare the graphs. The IQs graph is much more erratic which means that the data is spread over a larger range. Although there is 1 area where the data is concentrated and the gradient very steep, between 95-105. The TV hours graph is much smoother and the data less spread. The data number of hour's increases steadily to a certain point then it goes flat until the end. This means that there is a n anomalous result somewhere. I know that it can only be 1 or 2 anomalous because the point where it goes flat is at about 38 and there are only 39 sets of data in the graph. I will now look at the box plots to compare the two cumulative frequency graphs. Box plots for cumulative frequency graphs of IQ and number of TV hours watched for females: The box plots for these graphs show me that the IQ data has a much larger range and that it is quite evenly spread. I can see this because the interquartile range is quite large and the median evenly spread. There may be a few exceptions as 1 pupil is likey to have a very low IQ which is why the lowest value is so low. The TV hour's data seems to be much more concentrated and the data is generally lower. This shows that there can't be any relationship between them as they each grouped in certain areas. Also the box plot for TV hours shows that there is likely to bge an anomalous result as the highest value is so far out of the upper quartile. Hypothesis 2 Males In this hypothesis I will be comparing the Average number of TV hours watched per week and Weight, to see if there is any relationship between them. I will again start with Males and the Scatter graphs. Scatter graphs 1 and 2 to show the relationship between Weight and the Average number of TV hours watched per week for males: In these scatter graphs there is a slight negative correlation. This means that as the number of TV hours goes up Weight goes down. This may not be an accurate graph as there are a few anomalous results that may have caused the trend line to be that gradient. If this is so my hypothesis would have been correct, if it is not the gradient of the trend line isn't steep enough to say that it is 100% certain that it is accurate. I will need to use the cumulative frequency graphs to draw complete conclusions. Cumulative frequency graphs for the number of TV hours watched and Weights of males: These two graphs look quite different; the weights graph has most of its data concentrated in the middle of the range, between 30-50 and looks like a normal cumulative frequency curve. Whereas the number of TV hours has most of its data concentrated at the beginning between 0-30, showing that there is likely to be an anomalous result at the end of the range. These anomalous results on the TV hours graph are what caused the slight negative correlation on the trend line. I will be able to make complete conclusions after looking at the female sample and seeing if that graph follows suit. The box plots for these graphs will look quite different and will make it easy to make a simple comparison. Box plots for Cumulative frequency graphs IQ and Weight for males: From the box plots I can see that the two sets of data are almost identical in range which would cause a straight line on the scatter graph it is because of the anomalous results on the TV hours which caused the slight negative correlation. The weights box plot shows me that the data is quite evenly spread in the middle of the range apart from a very heavy person at the end which is why the highest figure is so far apart from the upper quartile. Overall the box plots show me that the similarity in the data means there is no relationship and hypothesis was correct. Hypothesis 2 Females Again I will start with the scatter graphs to show the relationship between Number of TV hours watched and weight. The graphs should be similar to the males and the conclusions the same. Again I had an anomalous result and had to create a second scatter graph without it there. Scatter graphs 1 and 2 to show the relationship between the Number of TV hours watched per week and Weight: The second scatter graph in this section, without the anomalous result completely changed the trend line. The first graph looks a lot more like the male graph whereas the second follows my hypothesis a lot better. In graph 1 there is a slight gradient on the graph which points towards a negative correlation, like those of the male sample. On the graph without the anomalous result there is clearly no correlation whatsoever as the line is nearly horizontal. I will take the results of the male sample to be wrong as I said earlier there are a few anomalous results which caused the trend line to be at that gradient. Now I will look at the cumulative frequency graphs to see what results I get from them. Cumulative frequency graphs for Average number of TV hours watched per week and Weight for Females: As on the males graph the TV hours for females have a lot of anomalous results. But for the scatter graphs I cancelled them all out which gave no correlation. If the line at the top of the TV hours graph is blanked out the two graphs look almost identical. This is why the scatter graph got a near horizontal trend line. The box plots for these to graphs will look alike apart from there will be a much longer line at the end of the TV hours graph because of the anomalous results. Box plots of cumulative frequency graphs for Number of TV hours watched and weights of females: These box plots show me the same as the males did, that the data is almost identical if placed 1 on top of the other. This is what caused the horizontal line in my scatter graphs and proves my hypothesis. Conclusion Hypothesis 1: My first hypothesis has been proved incorrect. The scatter graphs show that there is no correlation between the two sets of data. For my hypothesis to have been correct there would have needed to be a strong positive correlation. The cumulative frequency graphs and box plots again proved my hypothesis incorrect, the similarities in the two sets of data's box plots showed that there was no relationship and showed why the scatter graphs showed a straight line. Both the male and female samples showed that my hypothesis was incorrect although some anomalous results created a slight negative correlation in both it was obvious that it was still wrong. Hypothesis 2: My second hypothesis was proved correct. The scatter graphs showed that there was absolutely no correlation on the graphs which means no relationship. Although the male graphs did show a a negative correlation it was proved to be made by a few anomalous results by the cumulative frequency and later the inconsistency with the female sample. The female scatter graph showed a near horizontal trend line which was what I needed to prove my hypothesis. The similarities on the cumulative frequency graphs and box plots further proved my hypothesis was correct. Evaluation The investigation went quite well although my first hypothjesis was incorrect it showed that careful analysis of data is needed before drawing conclusions. When I next do an investigation into data I will use histograms to aid me in my analysis as they come in useful when looking for relationships in two sets of data as the cumulative frequency graphs do. I could have made the cumulative frequency graphs a little better as the program I used did not put a scale on the x axis but only the length of the range. Statistics Coursework 1st Hypothesis – For my first hypothesis I will investigate the relationship between the number of TV hours watched per week by the pupils against their IQ. I am going to use the columns â€Å"IQ† and â€Å"Average number of hours TV watched per week† taken from the Mayfield high datasheet. I think that there will be a relationship between them and will attempt to reveal it. 2nd Hypothesis – For my second hypothesis I will investigate the relationship between â€Å"Average number of TV hours watched per week† and â€Å"weight (kg)†. I think that there will not be any major relationship between as they will not affect each other greatly. I will present my analysis and the results in graphs and tables and explain the results using the correlation of the graphs and arrangements of the figures. I will select a number of pupils to base my data on and will use random sampling to ascertain the correct number of male and female pupils needed to make the investigation fair. Stratified Sampling I do not want to use all of the data in the database for my analysis so I will need to take a sample of the number of people in the school. I would like to take about 10% of the overall figure. I will also need to use stratified sampling to make it an equal proportion of the number of males and females in the school to make it fair. The total number of pupils at the school is 813 so I will need to take 10% as my number, 81.3 is rounded down to 81. The overall ratio for boys and girls in the school is: 414:399 Now I will need to do my sampling Males = 414 multiplied by 81 = 41 813 Females = 399 multiplied by 81 = 40 813 Random Sampling Now I have the number of samples I will need to select the samples I will be taking. To do this I will use random sampling. I will take random samples until I have 81. I can do this on Excel using the following formula: = round(round()*120. Once I have gathered the samples I am ready to start analyzing my samples. Analysis Hypothesis 1 Males The first thing I need to do in my analysis is to analyze my graphs which are the source of the investigation. I have created scatter graphs to show the relationship if the two data sources for my first hypothesis. I have separated them into male and female graphs as there is a separation in the numbers. First male scatter graph: This first graph presented a bit of a problem. There was an anomalous result that affected the trend line and the scale of the graph. I decided to create a new graph that didn't include that 1 piece of data. This way it would help me to analyze the rest of the data. Second male scatter graph: This graph showed the data much clearer and I could then start analyzing it. There is no correlation between the 2 sets of data. This means that it is unlikely that there is a relationship between IQ and Average number of TV hours watched per week. In this it may be that my hypothesis is incorrect. There is only a very slight gradient on the trendline that leans towards a negative correlation, but the gradient is not steep enough to draw any conclusions about the relationship between the two sets of data. I will have to use the cumulative frequency graphs and boxplots to see if any conclusions can be made. Cumulative frequency graphs for IQ and Average number of TV hours watched per week: From these graphs I could create box plots and compare the two sets of data. Before that I analyzed the cumulative frequency graphs to draw initial conclusions. The majority of the IQs for males are between 90 – 105, this shows that the data is quite spread out as this section only covers a small area of the graph. For the TV hour's graph, again the data is spread among 1 main area; in this case it is between 5-25. There is almost a straight line near the top of the graph; this shows that there is likely to be some anomalous results and 0 pupils in between that result and the main bulk. Now I will create box plots so I can compare the two graphs together. Box plots for cumulative frequency graphs of IQ and average number of TV hours watched per week: (for interquartile ranges look at copies of graphs at the back) From the box plots I can see that the data spread is relatively the same apart from a possible anomalous result in the TV hour's data. This similarity is the reason why the scatter graph had no correlation and therefore no relationship. This means that my hypothesis is wrong. Hypothesis 1 Females Again I will start with the scatter graphs. As with the male graph I had an anomalous result that spread out the data and scale down the graph so most of the relevant data couldn't be analyzed. I then did another graph without that specific piece of data. Scatter Graphs 1 and 2 to show the relationship between IQ and average number of TV hours watched per week for Females: As you can see on both the graphs there is no correlation between the two sets of data. This again means that my first hypothesis is unlikely to be correct. There is only a slight gradient on the trend line which is not steep enough to draw any conclusions from it. There is another anomalous result on the graph but it doesn't affect the trend line and my conclusions so I left it on the graph. I will now crate cumulative frequency graphs to see if they can help me to draw conclusions. Cumulative frequency graphs for the IQ and number of TV hours watched per week: I will now analyze the graphs before drawing box plots to compare the graphs. The IQs graph is much more erratic which means that the data is spread over a larger range. Although there is 1 area where the data is concentrated and the gradient very steep, between 95-105. The TV hours graph is much smoother and the data less spread. The data number of hour's increases steadily to a certain point then it goes flat until the end. This means that there is a n anomalous result somewhere. I know that it can only be 1 or 2 anomalous because the point where it goes flat is at about 38 and there are only 39 sets of data in the graph. I will now look at the box plots to compare the two cumulative frequency graphs. Box plots for cumulative frequency graphs of IQ and number of TV hours watched for females: The box plots for these graphs show me that the IQ data has a much larger range and that it is quite evenly spread. I can see this because the interquartile range is quite large and the median evenly spread. There may be a few exceptions as 1 pupil is likey to have a very low IQ which is why the lowest value is so low. The TV hour's data seems to be much more concentrated and the data is generally lower. This shows that there can't be any relationship between them as they each grouped in certain areas. Also the box plot for TV hours shows that there is likely to bge an anomalous result as the highest value is so far out of the upper quartile. Hypothesis 2 Males In this hypothesis I will be comparing the Average number of TV hours watched per week and Weight, to see if there is any relationship between them. I will again start with Males and the Scatter graphs. Scatter graphs 1 and 2 to show the relationship between Weight and the Average number of TV hours watched per week for males: In these scatter graphs there is a slight negative correlation. This means that as the number of TV hours goes up Weight goes down. This may not be an accurate graph as there are a few anomalous results that may have caused the trend line to be that gradient. If this is so my hypothesis would have been correct, if it is not the gradient of the trend line isn't steep enough to say that it is 100% certain that it is accurate. I will need to use the cumulative frequency graphs to draw complete conclusions. Cumulative frequency graphs for the number of TV hours watched and Weights of males: These two graphs look quite different; the weights graph has most of its data concentrated in the middle of the range, between 30-50 and looks like a normal cumulative frequency curve. Whereas the number of TV hours has most of its data concentrated at the beginning between 0-30, showing that there is likely to be an anomalous result at the end of the range. These anomalous results on the TV hours graph are what caused the slight negative correlation on the trend line. I will be able to make complete conclusions after looking at the female sample and seeing if that graph follows suit. The box plots for these graphs will look quite different and will make it easy to make a simple comparison. Box plots for Cumulative frequency graphs IQ and Weight for males: From the box plots I can see that the two sets of data are almost identical in range which would cause a straight line on the scatter graph it is because of the anomalous results on the TV hours which caused the slight negative correlation. The weights box plot shows me that the data is quite evenly spread in the middle of the range apart from a very heavy person at the end which is why the highest figure is so far apart from the upper quartile. Overall the box plots show me that the similarity in the data means there is no relationship and hypothesis was correct. Hypothesis 2 Females Again I will start with the scatter graphs to show the relationship between Number of TV hours watched and weight. The graphs should be similar to the males and the conclusions the same. Again I had an anomalous result and had to create a second scatter graph without it there. Scatter graphs 1 and 2 to show the relationship between the Number of TV hours watched per week and Weight: The second scatter graph in this section, without the anomalous result completely changed the trend line. The first graph looks a lot more like the male graph whereas the second follows my hypothesis a lot better. In graph 1 there is a slight gradient on the graph which points towards a negative correlation, like those of the male sample. On the graph without the anomalous result there is clearly no correlation whatsoever as the line is nearly horizontal. I will take the results of the male sample to be wrong as I said earlier there are a few anomalous results which caused the trend line to be at that gradient. Now I will look at the cumulative frequency graphs to see what results I get from them. Cumulative frequency graphs for Average number of TV hours watched per week and Weight for Females: As on the males graph the TV hours for females have a lot of anomalous results. But for the scatter graphs I cancelled them all out which gave no correlation. If the line at the top of the TV hours graph is blanked out the two graphs look almost identical. This is why the scatter graph got a near horizontal trend line. The box plots for these to graphs will look alike apart from there will be a much longer line at the end of the TV hours graph because of the anomalous results. Box plots of cumulative frequency graphs for Number of TV hours watched and weights of females: These box plots show me the same as the males did, that the data is almost identical if placed 1 on top of the other. This is what caused the horizontal line in my scatter graphs and proves my hypothesis. Conclusion Hypothesis 1: My first hypothesis has been proved incorrect. The scatter graphs show that there is no correlation between the two sets of data. For my hypothesis to have been correct there would have needed to be a strong positive correlation. The cumulative frequency graphs and box plots again proved my hypothesis incorrect, the similarities in the two sets of data's box plots showed that there was no relationship and showed why the scatter graphs showed a straight line. Both the male and female samples showed that my hypothesis was incorrect although some anomalous results created a slight negative correlation in both it was obvious that it was still wrong. Hypothesis 2: My second hypothesis was proved correct. The scatter graphs showed that there was absolutely no correlation on the graphs which means no relationship. Although the male graphs did show a a negative correlation it was proved to be made by a few anomalous results by the cumulative frequency and later the inconsistency with the female sample. The female scatter graph showed a near horizontal trend line which was what I needed to prove my hypothesis. The similarities on the cumulative frequency graphs and box plots further proved my hypothesis was correct. Evaluation The investigation went quite well although my first hypothjesis was incorrect it showed that careful analysis of data is needed before drawing conclusions. When I next do an investigation into data I will use histograms to aid me in my analysis as they come in useful when looking for relationships in two sets of data as the cumulative frequency graphs do. I could have made the cumulative frequency graphs a little better as the program I used did not put a scale on the x axis but only the length of the range.

Marketing Strategy Goals and Objectives

Marketing Strategy Goals and Objectives Our company seeks to become successful in the ice cream business. The company targets to develop a unique set of goals and objectives that will make it a leading player in the market. The company plans to improve the lifestyles of its targeted consumers through training and awareness. This will encourage the consumers to embrace the best health practices.Advertising We will write a custom essay sample on Marketing Strategy: Goals and Objectives specifically for you for only $16.05 $11/page Learn More By so doing, the company will encourage its customers to embrace the best lifestyles. This discussion presents the company’s objectives and goals.  The first goal is to provide high-quality products to its customers. There are various aspects used to describe a â€Å"high-quality† product. To begin with, the ice creams marketed by the company will provide a new image to the consumers. The company will achieve this goal using proper promotional st rategies. The company will sensitize the customers about the quality of its products thus making its business successful. The quality of any given product plays a significant role towards its success in the market. The second goal is to change the people’s attitude about ice cream and similar products. It is agreeable that many people in different societies consider ice cream as a bad product because it affects human health. The company targets to use awareness strategies and training procedures in order to change the people’s views about the products. The company’s marketing strategy will be successful after changing the people’s perception about ice cream. The third goal is to increase the company’s brand equity. Brand equity is what determines the success of a product in the market. Companies with the best brand equities find it easier to succeed after introducing new services or products in a given market. Our company also seeks to change the i mage of its ice cream trucks and products. The approach will make it possible for the company to become profitable. This will be a critical approach towards a successful marketing strategy.  The other important goal is to re-invent the mobile ice cream industry. Many people today do not understand or embrace the nature of the â€Å"mobile† ice cream industry. That being the case, the company will present new ideas and strategies that will encourage more people to purchase the products. The strategy will make the company’s business successful.  The other important objective is to embrace the idea of corporate social responsibility (CSR). Corporate social responsibility is an important practice that helps businesses realize their potentials by providing adequate support to different communities.Advertising Looking for essay on business economics? Let's see if we can help you! Get your first paper with 15% OFF Learn More It will also be necess ary to produce healthy products. The company will encourage the people to conserve the environment in order to promote sustainability.  The company will also focus on the best ways to produce unique products that are acceptable in the society. This goal will make it easier for our company to diversify its â€Å"ice creams† thus becoming successful in the business. The company will produce new flavors in order to address the changing needs of the customers.  The above goals and objectives will help the company focus on its goals and eventually become successful. The ice creams will fulfill the needs of the customers. The other goal is to embrace the best business practices in the industry. The approach will ensure the business engages in a competitive business. The company will also involve its employees and stakeholders in the decision-making process. Such practices and goals will definitely make the company successful.

External and Internal Environments Essay Example | Topics and Well Written Essays - 2000 words

External and Internal Environments - Essay Example The company is engaged in the business of running retail stores that come in various formats like discount stores, supercentres, neighborhood markets, etc. worldwide. The products of the company are also offered through different e-commerce websites that includes samsclub.com and walmart.com. Wide range of merchandise products are also offered by the company which comes at every day low price (EDLP). The company's operation is divided into three broad segments namely, Wal-Mart International, Wal-Mart US and Sam's Club. External Environment Analysis The external environment in which Wal-Mart operates its business activities can have a significant impact on its growth and sustainability in future. The various external environmental factors that can have an impact on the company and its corresponding retail industry can be better understood through the PESTEL analysis. It stands for Political, Economical, Social, Technological, Environmental and Legal factors concerning the organization . Of all these six environmental factors the Economical and Social factors can have a significant impact on the organization and the industry in which operates its business. A detailed analysis of these two factors has been discussed below: a. Economical Factors: United States is considered to be one of the largest economies of the world with gross domestic product (GDP) of around $15.09 trillion and per capita GDP of around $49,000 in 2011 (CIA, 2012a). The recent global financial crisis (GFC) had a significant negative impact on the US economy but it recovered well. The US retail savings which also suffered a setback due to GFC is expected to have a steady growth. The disposable income of the US population is also expected to increase. All these factors can have a positive impact on Wal-Mart in increasing its sales in the forthcoming years through its low and competitive pricing strategy. b. Social Factors: The increasing healthcare costs and the ever increasing aging population o f US are major concerns for the country at present. Another major social concern for the country is the rising inequality of income. United States has been ranked 42 out of 136 nations with respect to the income equality parameter as evaluated by the Gini coefficient (CIA, 2012b). Although US economy as a whole has experienced consistent growth it has not translated into redistributive social policies and increased wages. All these social concerns can have a significant impact on Wal-Mart because it employs large number of laborers and the wages issues associated with them can hamper the future growth prospect of the company. Industry Analysis Porter’s five forces model helps an organization to assess the competitive forces which exists within the industry (Hill & Jones, 2012, p. 49). The forces which help out in the process are named as a) threat of new entrants, b) threat from the substitute products or services, c) bargaining power of the suppliers, d) bargaining power of the consumers and finally e) competition within the industry (Society for Human Resource Management (U.S.), 2006, p.38-39). Out of the five competitive forces mentioned above two most important forces that can have a significant impact on Wal-Mart has been described below: a. Buyer Power: The retailers that operate in the retail industry vary greatly in their size with respect to companies like Wal-Mart who are having large chain of supermarkets

Same Sex Marriage Essay Example | Topics and Well Written Essays - 1500 words

Same Sex Marriage - Essay Example Efforts to amend various sections of the Constitution in different States gained momentum to incorporate amendments to prohibit the same-sex marriages. States such as Nevada, Alaska, and Nebraska made changes to their constitution to disallow lesbian and gay relationships. This happened in 1990. Massachusetts State was the first state to legalize and recognize the same sex-marriage in 2003. Civil unions came into full force to advocate States to grand the lesbians and gays their most much-needed rights. Out of their efforts, several States have approved homosexuality, namely, New York, Rhode Island, and the District of Columbia. There is a lot of optimism in the gay and lesbian community, going by the past trends, that they will gain victories in many other states in the United States (Confessore and Barbaro A1). In the United States, many groups show their deeper concerns about their fears and speculation over the consequences of this new social order (Ambrosino 84). Some have supported and others bitterly opposed this new practice. Different legal and religious communities such as Christianity, Muslims, and Buddhism have voiced in their varied views on this matter. Catholic and evangelistic churches are in the forefront to oppose the move to legalize same-sex marriage. Division on homosexuality in the Protestant faith is evident, a section of them feels that the same-sex marriages should have freedom to marry, others completely object (Taylor A25). The Muslim community feels this is a violation of religious beliefs. Buddhists have differing stances about same-sex marriage. The liberals have no objections while the conservatisms greatly object the issue. The number of the opponents has out-numbered that of supporters with significant margins. The opponents raise many concerns about the same- sex marriages. To start with, they doubt whether there is any commitment in these relationships. They argue that the marriages are due to break sooner than later. They further point out that gay and lesbians’ couples are quite unhappy which is on contrary to a heterosexual marriages. Social conservatives believe that marriage is a health foundation