Importance of Slavery Essay Example for Free

Importance of Slavery Essay Economic, geographic, and social factors all contributed to the rise of importance for slaves in the southern colonies as their position in American society changed from 1607 and 1775. Slaves not only influenced Jamestown in 1607, but they influenced America, all the way into the American Revolution in 1775. Slavery ultimately flourished and aided economic triumph in the southern colonies. With the hopes of making it big in the new colonies, indentured servants came through the headright system, usually people who lacked funds of any sort hoping to make money. During this time, English practiced mercantilism and since they lacked the proper agriculture to grow tobacco. John Rolfe made it a cash crop in the new colonies and they were able to sell it quite easily to their mother country, England. This lasted until about the time of Bacon’s Rebellion where indentured servants were mad due to them thinking they would get land after their 20 years of work. But with this the south turned to slavery as a viable option. Now they could tell by just the color of their skin what class they were in. The triangular trade made this even better. They got more and made slaves work on their large plantations. Since slaves were not citizens they had no rights. The South flourished with their labor. They had huge profits. America did not just depend on tobacco they also had rice and indigo that helped the economy an immense amount. Social factors in the south also encouraged growth. The American slave code is based off the barbatos slave code. Aristocrats who were at the top of the pyramid in social class had many slaves. The blacks were at the bottom and they had no rights. The slave owners often had there slaves reproduce to make them more slaves. The more slaves you had the more money, and the higher nobility you had. Racism was a huge social factor of slavery. The whites thought they were superior to the blacks and they showed it. with the social presser to hate blacks slavery would not have been so successful economically. The geography of the southern colonies was not suited to standard farming as that of the northern colonies. The soil of the land was not suited to the growing of standard crops like wheat and corn. Also, the hot weather of the south did not allow for easy farming, and its wet and temperate sub-tropical climates was best suited for the growing of tobacco, rice, and indigo. Along with this, the extensive river system which divided the southern colonies into tiny interconnected pieces provided the best transportation for mass goods and for wet soil. The many river parts of the south made it easy to transfer goods grown on plantations, and to facilitate the purchase of slaves.

Houghton Mifflin Company Essay Example for Free

Houghton Mifflin Company Essay World War 1 is the first war in history that I may say, involved the use of technology and advances in science. The ever famous â€Å"mustard gas† was developed by the Germans, and used against the allied forces. Mustard gas is an oily liquid that readily evaporates into a very noxious and toxic gas, and are used in chemical warfare, where it burns the skin and causes very fatal respiratory and lung damages. It was used effectively against bunkers and trenches, where escape was not easy, so the efficiency of the gas is very high. The Allied forces counteract and produced the first ever effective gas mask, made from very fine activated carbon; it absorbs the poisonous gas, preventing severe damage and effect to the allied soldiers. The drawback of this mask was it reduced visibility and made the soldier vulnerable to sniper attacks. World War 1 was also the setting for the first aerial warfare. Airplanes in the form of biplanes (the first type of airplane, it was very light and it resembled the first airplanes developed by the Wright brothers). They converted simple courier and transport planes into aerial and bomber planes, mass produced the most efficient design and further improved its applications. The Germans have early aerial advantage against the allied forces because of its high amount of available fighter planes and the ever famous Zeppelin, a large dirigible or flying balloon used in bombarding and raiding Britain. But the German advantage declined starting the mid-1916 because the British forces gained aerial superiority in the Western front. Aside trench warfare; tanks were also first widely used in World War 1. Light tanks were first manufactured on 1910 and used for small wars and revolts on the British Empire. The Germans also manufactured tanks to cope up with the allied forces. Armored tanks were used later to inflict damage to enemy trenches. Besides tanks, long range artillery was also developed. High powered howitzers and cannons were fired towards enemy trenches and were proven effective against concentrated enemy troops and tanks. On sea, naval warfare was also developed. Large sea vessels carried high powered bombs and can lay siege even to distant enemy camps. The Germans was the first to use submarines on a full scale war on the sea. They can damage enemy ships without being detected or even seen. The submarine was proven to be effective as patrol on enemy sea territory and can be used as a warning if enemy naval ships were mobilized. The famous German submarine was the U-boat. It was used on unrestricted submarine warfare, in which enemy ships were targeted and sunk, even civilian ships. This unrestricted submarine warfare leads the United States to join the war on 1917. The reason was because the German U-boat was a risk to the United States trade policies with European countries. The U-boat has sunk the Lusitania on 1915, a British liner en route to the United States. It carried American citizens, and reports were published that Americans were killed during the attack. These angered the United States, thus declaring war on Germany and the Central Powers. World War 1 was not fought only on Europe. The colonies of European nations involved also joined the war. Japan for instance, joined the Allied forces to obtain German colonies on the pacific. The British expeditionary forces battled the Ottoman Empire on the desert. The expeditionary force led by T. E. Lawrence pushed the Ottoman Empire troops back into Lebanon until its defeat by the Allied forces on September 1918. The Treaty of Versailles ended the war. When the Central powers were defeated, this treaty promised peace all throughout Europe and it was the one who outlined the land and territorial distribution of lands acquired from the Central powers. I was affected by the topic because World War 1 was a very devastating war. Over 20 million casualties were reported on both sides. May were killed and wounded. I know war was against morality. But sometimes, countries and governments were blinded by their ambitions, mostly to obtain power and territories. As stated earlier, war is inevitable. Although the United Nation exists now, war is still happening. Even now, as I write this article, a war is happening, somewhere out there. War can still be prevented up to a certain extent. Peace talks must be initiated to prevent further conflicts, even if war has already broke up. Living in peace is a very good thing. I can help to achieve that, in my own little way, by respecting others’ opinion and properties. If every nation on earth can learn that, I am sure war are sure to be found on History books only. No war will happen once again. Respect is the word. References Andrea, A. J, and Overfield J. H. (1990). The Human record: Sources of Global History. Vol. 2. Boston. Houghton Mifflin Company. Heilbroner, R. H. (1974). An Inquiry into the Human Prospect. New York. Norton and Company. Keilor W. R. (2007). â€Å"World War 1†. Microsoft ® Student 2008 [DVD]. Redmond. Microsoft Corporation

Ebola Virus: History, Symptoms and Treatment

Ebola Virus: History, Symptoms and Treatment Vijayatheeban Jeyanandan Ebola virus outbreaks: The deadly and incurable Hemorrhagic fever Contents (Jump to) 1.1 Introduction. 1.2 History of Ebola virus. 1.3 Characteristics of Ebola virus. 1.4 Symptoms of Ebola infection. 1.5 Diagnosis methods. 1.6 Treatment methods. 1.7 Conclusion Reference list 1.1 Introduction A reported by the World Health Organization (2014) Ebola virus disease once known as Ebola haemorrhagic fever is a serious, frequently deadly disease, with a case casualty rate of up to 90%. There are no authorized particular medications or vaccine accessible for utilization in individuals or creatures. Stanford education (2014) states that Ebola virus was initially recognized as a possible new strain of Marburg virus in 1976. Stanford education states that Ebola infection is initially wide spreading in Sudan and Zaire. Ebola virus is a member of filoviridae family. Farrar and Piot (2014) reported that as of September 14, 2014, a total of 4507 confirmed and likely instances of Ebola virus disease, and also 2296 deaths from the infection, had been accounted for from five nations in West Africa — Guinea, Liberia, Nigeria, Senegal, and Sierra Leon. Contact with body fluids demonstrated a solid affiliation. Francesconi et al. (2003) comments that Persons who had immediate physical contact with a infected person were more inclined to have gained the disease. 1.2 History of Ebola virus Peters and Leduc (1999) comments that biomedical science initially experienced the virus family filoviridae when Marburg virus showed up in 1967 and in the late 1970s, the global group was again startled, this time by the revelation of Ebola infection as the causative executor of significant flare-ups of hemorrhagic fever in the Democratic Republic of the Congo (DRC) and Sudan. History of Ebola infection can be found online (Stanfort education, 2014) The first outbreaks of infected in excess of 284 peoples, with a 53% death rate. After the few months the second Ebola infection caused from Yambuku, Zaire, Ebola-Zaire (EBOZ). EBOZ, with the most astounding death rate of any of the Ebola infection (88%), contaminated 318 peoples. In 1989, a novel infection, Reston Ebolavirus (REBOV) was secluded from commonly tainted cynomolgus macaques imported from the Philippines into United States. All shipments aside from one were followed to single supplier in the Philippines; however, the main beginning of the infection and mode of sullying for the office has never been learned. While pathogenic for regularly and tentatively tainted monkeys, constrained information demonstrate that REBOV may not be pathogenic for people as creature overseers without delivering clinical side effects. A review by Georges et al. (1999) reported that, in 1994, at Gabon, Occured in Mà ©kouka and other gold-mining camps profound in the downpour backwoods. At first thought to be yellow fever; recognized as Ebola hemorrhagic fever in 1995. Zuckerman(2008) reported that In 2000, Happened in Gulu, Masindi, and Mbarara areas of Uganda. The three most essential dangers connected with Ebola infection contamination were going to funerals of Ebola hemorrhagic fever patients, having contact with infected patients in ones family, and giving restorative forethought to Ebola infected patients without utilizing sufficient individual defensive measures. In this situation, reported number of human cases is 425 and reported number of deaths among cases is 224. 1.3 Characteristics of Ebola virus A review by Sullivan et al. (2003) comments that Ebola was found in 1976 and is a member of the Filovirus family, which are pleomophic, negative-sense RNA viruses whose genome organization is most similar to the paramyxoviridae. Geisbert et al. (2010) states EBOV particles contain a non-infectious RNA genome of roughly 19 kilobases that encodes seven structural proteins and one non-structural protein. The gene order is 3†² leader, nucleoprotein, virion protein 35 , virion protein 40, glycoprotein, virion protein 30, polymerase L protein, and 5†² trailer.3 Four of these proteins—nucleoprotein, virion protein30, virion protein35, and the polymerase L protein—are associated with the viral genomic RNA in the ribonucleoprotein complex.Crowley and Crusberg (2014) states Ebola viruses are long and filamentious, essentially bacilliform. However the viruses mostly get on a â€Å"U† shape. The particles of these viruses can be above 14,000 nm in long and average 80 nm in diameter. Visualscience.ru (2014) states Ebola has a layer envelope its shaped from the film of the host cell during virus budding. The viral molecule additionally catches various human proteins. Ebola surface protein, encoded by the gp gene. Transmission of the virus PHAC-ASPC.GC.CA (2014) states, that in an outbreak, it is theorized that the first patient gets to be infected as an aftereffect of contact with an infected animals. Person to person transmission happens by means of close personal contact with an infected individual or their body fluids during the late stages of disease or after death. Centers for Disease Control (2014) reported that Ebola is not spread through the air or by water, or in general, foods. However Ebola is spread through direct contact with blood or body fluids including but not limited to urine, salivation, dung, regurgitation, and semen of an individual who is infected by Ebola. And also Ebola virus can be transmitted by objects like needles and syringes that have been contaminated with the virus. 1.4 Symptoms of Ebola infection Smith (2014) stats that, the symptoms of Ebola may be shown out from 2 days to 21 days after the infection of Ebola virus, but the average is 8 to 10 days from the infection. The symptoms are quite similar to the flu, cholera, typhoid, and malaria. The symptoms usually include high fever, serious head pain, body weakness, retching, diarrhea, stomach torment, Lack of apptite, and sore throat. Symptoms of Ebola can be found online (Health24, 2014). Progression of Ebola fever causes bleeding inside the body, and from the eyes, ears, nose and anus. Some individuals will vomit or hack up blood, have wicked looseness of the bowels, have impaired kidney and liver function, have continues hiccups and get a rash. Diagnosing methods of Ebola can be found online (Cdc.gov, 2014). In the earlier stage is really very difficult because the early symptoms are quite similar to the symptoms of malaria and typhoid fever. In his analysis Zubay (2005,pp) says that tests with live virus must be performed in Biosafety Level 4 regulation research centers, due to the compelling harmfulness and infectiousness of disease. 1.5 Diagnosis methods Diagnosing methods of Ebola can be found online (Centers for disease control and prevention, 2014). In the earlier stage is really very difficult because the early symptoms are quite similar to the symptoms of malaria and typhoid fever. In his analysis Zubay (2005,p.71,72) says that tests with live virus must be performed in Biosafety Level 4 regulation research centers, due to the compelling harmfulness and infectiousness of disease. A review by Saijo et al, (2006) says after the isolation, the virus can be detected via various laboratory diagnostic methods like virus isolation, reverse transcription, real time quantitative method , antigen-capture enzyme-linked immune sorbent assay method (ELISA), antigen detection by immunostaining, or IgG-and IgM-ELISA using authentic virus antigens (9, 18, 28-30, 32, 48, 50, 53, 64). Diagnosing methods can differ with the time line of infection which can be found online (Centers for disease control and prevention, 2014). Within a few days after the symptoms shown out we could use Antigen-capture enzyme-linked immunosorbent assay (ELISA) testing or IgM ELISA or Polymerase chain reaction (PCR) or Virus isolation and for retrospectively in deceased patients we need to use Immunohistochemistry testing or PCR or virus isolation and later in the disease course or after recovery we could use IgM and IgG antibodies. In his analysis Bray (2014) says that as indicated by the WHO, people who no more have signs and indications of Ebola infection sickness can be released on the off chance that they have two contrary PCR tests on entire blood, differentiated by no less than 48 hours. 1.6 Treatment methods Schoenstadt (2014) says that there are no proven treatment methods to kill the Ebola virus therefore, treatment concentrates on giving easing of side effects as the body battles the virus. This is called supportive care. Ziady and Small (2004) stats that patients receive supportive treatments like balancing fluid and electrolytes, maintaining tissue and pulmonary oxygenation, maintaining blood circulation by replacing blood loss, and treating complications symptomatically. Gupta, (2014) comments that chronicled examples in medication improvement recommend that there is a slim likelihood of accomplishment with the current arrangement of potential Ebola treatments. Torrence (2005) stats that scientists have also examined the potential of heterologous live viral vectors in effectively preventing Ebola virus infection. And we also can say good nursing care and using antibiotics to prevent secondary infections from bacteria also supportive care for Ebola. Lamontagne et al. (2014) says General wellbeing mediations including describing the episode the study of disease transmission, contact following, social assembly, and state funded instruction are fundamental steps in ceasing Ebola and will at last spare a lot of people a larger number of lives than can be spared by individual patient forethought. (Geisbert, 2014) says that antibody therapies and several other methodologies mentioned here should ultimately be included in an arsenal of interventions for controlling future Ebola outbreaks. 1.7 Conclusion Ebola is infection and highly lethal and with no verifiably effective vaccine available. However the ebola hemorraghic fever can be control by spreading virus. First of all, the health ministry of government and who knows about the Ebola virus disease they should be Awareness to essential peoples. Because everyone must be attention about the Ebola infection. The ebola infection only can diagnosis under the advanced laboratory, but there are no lab facilities backwardness areas and also some essential countries. However who the person shows the ebola virus symptoms, we should be try to transfer to where can diagnose. In the future government should be provide advanced lab facilities for diagnose the infection when the infection highly spreading. The medical workers of ebola virus diagnosing or researching they should be wear protective clothing transport a man suffering from Ebola. Reference list Bray, M. (2014). Uptodate. Available at: http://www.uptodate.com/contents/diagnosis-and-treatment-of-ebola-and-marburg-virus-disease# (Accessed 30 October 2014). Centers for disease control and prevention (2014) Available at: http://www.cdc.gov/vhf/ebola/diagnosis/ (Accessed 29 October 2014). Centers for disease and prevention (2014). Transmission of Ebola Hemorrhagic Fever [online] Available at: http://www.cdc.gov/vhf/ebola/transmission/ (Accessed 27 September 2014). Crowley, J. and Crusberg, T. (2014). Genomic Structure, Comparative and Molecular Biology. Available at: http://www.mcb.uct.ac.za/ebola/ebolagen.html (Accessed: 28 September 2014). Farrar, J. and Piot, P. (2014). ‘Ebola Virus Disease in West Africa -The First 9 Months of the Epidemic and Forward Projections’, New England Journal Medicine, 371(16), pp.1481-1495 [Online]. Available at: http://www.nejm.org/doi/full/10.1056/NEJMoa1411100 (Accessed: 6 November 2014) Francesconi, P., Yoti, Z., Declich, S., Onek, P., Fabiani, M., Olango, J., Andraghetti, R., Rollin, P., Opira, C., Greco, D. and Salmaso, S. (2003). ‘Ebola Hemorrhagic Fever Transmission and Risk Factors of Contacts, Uganda’. Emerging Infectous Disease, 9(11), pp.1430-1437, National Center for Biotechnology Information [Online]. Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3035551/ (Accessed: 6 November 2014) Geisbert, T., Lee, A., Robbins, M., Geisbert, J., Honko, A., Sood, V., Johnson, J., de Jong, S., Tavakoli, I., Judge, A., Hensley, L. and MacLachlan, I. (2010). Postexposure protection of non-human primates against a lethal Ebola virus challenge with RNA interference: a proof-of-concept study. 375(9729), pp.1896-1905, The Lancet. (online). Available at: http://dx.doi.org/10.1016/s0140-6736(10)60357-1 (Accessed 28 September 2014) Geisbert, T. (2014). ‘Medical research: Ebola therapy protects severely ill monkeys’, Nature, 514(7520), pp.41-43, Nature Publishing Group [Online]. Available at: http://www.nature.com/nature/journal/vnfv/ncurrent/full/nature13746.html (Accessed:6 November 2014). Georges, A., Leroy, E., Renaut, A., Benissan, C., Nabias, R., Ngoc, M., Obiang, P., Lepage, J., Bertherat, E., Benoni, D. (1999). Ebola hemorrhagic outbreaks in Gabon. Journal of Infectious Diseases. 179(Supplement 1), pp.6575. [Online]. Available at: http://www.ncbi.nlm.nih.gov/pubmed/9988167 (Accessed: 6 Oct. 2014). Gupta, R. (2014). ‘Rethinking the development of Ebola treatments’, The Lancet Global Health, 2(10), pp.e563-e564 [Online]. Available at: http://www.thelancet.com/journals/langlo/article/PIIS2214-109X(14)70304-3/fulltext (Accessed: 6 November 2014). Health24 (2014). Available at: http://www.health24.com/Medical/infectious-diseases/Ebola/Signs-and-symptoms-of-Ebola-20140729 (Accessed 29 October 2014). Lamontagne, F., Clà ©ment, C., Fletcher, T., Jacob, S., Fischer, W. and Fowler, R. (2014). ‘Doing Todays Work Superbly Well — Treating Ebola with Current Tools’. New England Journal of Medicine, 371(17), pp.1565-1566 [Online]. Available at: http://www.nejm.org/doi/full/10.1056/NEJMp1411310 (Accessed: 6 November 2014) Mahy, B. and Van Regenmortel, M. (2010). Desk encyclopedia of human and medical virology. Google books [Online]. Available at: http://books.google.lk/books?id=nsh48WKIbhQCpg=PA382dq=ebola+virus+history+originhl=ensa=Xei=rCUyVP7wDcSjugTzs4GQDQved=0CDMQ6AEwBA#v=onepageq=ebola%20virus%20history%20originf=false (Accessed 4 Oct. 2014). Peters, C. and LeDuc, J. (1999). ‘An Introduction to Ebola: The Virus and the Disease’. The Journal of Infectious Diseases, 179(s1), p.Six-xvi. [Online]. Available at: http://dx.doi.org/10.1086/514322 (Accessed 4 Oct. 2014). Public Health Agency of Canada (2014). Available at: http://www.phac-aspc.gc.ca/lab-bio/res/psds-ftss/ebola-eng.php (Accessed 27 September 2014). Saijo, M., Niikura, M., Ikegami, T., Kurane, I., Kurata, T. and Morikawa, S. (2006). ‘Laboratory Diagnostic Systems for Ebola and Marburg Hemorrhagic Fevers Developed with Recombinant Proteins’. Clinical and Vaccine Immunology, 21, November [Online]. Available at: http://dx.doi.org/10.1128/cvi.13.4.444-451.2006 (Accessed 30 October 2014). Schoenstadt, A. (2014). eMedTV: Health Information Brought To Life. Available at: http://ebola.emedtv.com/ebola/ebola-treatment.html (Accessed: 6 November 2014) Smith,W. (2014).Webmd. Available at: http://www.webmd.com/a-to-z-guides/ebola-fever-virus-infection (Accessed 29 Oct. 2014). Sullivan, N., Yang, Z. and Nabel, G. (2003). Ebola Virus Pathogenesis: Implications for Vaccines and Therapies. 77(18), pp.9733-9737, Journal of Virology. [online]. Available at: http://dx.doi.org/10.1128/jvi.77.18.9733-9737.2003 (Accessed 28 September 2014). Torrence, P. (2005). Antiviral drug discovery for emerging diseases and bioterrorism threats. Google books [Online]. Available at: http://books.google.lk/books?id=QZl7GzhTsb8Cdq=Torrence,+P+Antiviral+drug+discovery+for+emerging+diseases+and+bioterrorism+threats.source=gbs_navlinks_s (Accessed: 6 November 2014). Visualscience.ru (2014). Available at: http://visualscience.ru/en/projects/ebola/poster/ (Accessed 28 September 2014). Web.stanford.edu (2005) Available at: https://web.stanford.edu/group/virus/filo/history.html (Accessed: 6 November 2014). World Health organization (2014). Ebola Virus Diseases (EVD) Implication of Introduction in the Americas. Jamaica: Jamaica information service [online]. Available at: http://jis.gov.jm/features/ebola-virus-diseases-evd-implication-introduction-americas/ (Accessed 6 November 2014). Ziady, L. and Small, N. (2004). Prevent and control infection. Google books [Online]. Available at: http://books.google.lk/books?id=kSKwP3v99dYCpg=PA256lpg=PA256dq=Ziady,+L.+and+Small,+N.+(2004).+Prevent+and+control+infectionsource=blots=DEOU4V_3gRsig=phk4sKUjV30cWcw7qv3Xo08Id1khl=ensa=Xei=yq5bVPGeGsr98AXShIKACAved=0CB0Q6AEwAQ#v=onepageq=Ziady%2C%20L.%20and%20Small%2C%20N.%20(2004).%20Prevent%20and%20control%20infectionf=false (Accessed: 6 November 2014) Zubay, G. (2005). Agents of bioterrorism. Google books [Online]. Available at: http://books.google.lk/books?id=AwkVgNPRnKoCdq=diagnosis+methods+ebola+Zubaysource=gbs_navlinks_s (Accessed 29 October 2014). Zuckerman, A. (2008). Principles and practice of clinical virology. Google books [Online]. Available at: http://books.google.lk/books?id=4il2mF7JG1sCpg=PA774lpg=PA774dq=Okware+SI,+Omaswa+FG,+Zaramba+S,+et+al.+An+outbreak+of+Ebola+in+Uganda.source=blots=NBElqYFkMRsig=o7MGwDL_xghUdwFQohFWtqj_TOohl=ensa=Xei=ZUEyVJC_G8aOuATxwoGoAQved=0CCMQ6AEwAQ#v=onepageq=An%20outbreak%20of%20Ebola%20in%20Ugandaf=false (Accessed 4 October 2014).

A Comparison of Corrupt Kings in Shakespeares Henry IV and Richard II

A successful monarchy relies upon a stable leader who is concerned with the satisfaction of those he rules over. Henry Bolingbroke the IV in Shakespeare's Henry the IV Part I follows a trend set by his predecessor in Richard II of self-indulgence and neglect of his kingdom. These leaders worry about the possibility of losing their kingdom or their soldiers to other nobles who were also concerned more with obtaining a higher position rather than governing. The king must also be wary of his own life, something that was once revered and guarded closely by other nobles. Wars once fought for gaining or protecting land are overshadowed by personal battles fighting for the position of king. Henry proved himself a powerful and fearless leader when he forcefully overthrew King Richard despite the divine rights bestowed upon him. While this was disruptive to the country, it appeared that this new leader would be successful because of confidence and military strength. However, shortly after he obtained his position, Henry became aware of the forces pulling the king away from his duties. He fails to either ignore or eliminate these distractions and becomes absorbed in them instead; "It seems then that the tidings of this broil/Brake off our business." (Henry, I, i, 47-48). Unfortunately, the king is not the only one neglecting the country. Most of the nobles realize their potential for additional power after the throne has been usurped. This disease, known as neglect, spreads through the ruling class unnoticed by the inflicted. John of Gaunt is one of the few nobles to see what the English peasants have seen; "That England that was wont to conquer others / Hath made a shamef ul conquest of itself." (Richard, II, i, 69-70). John of Gaunt sc... ...bination which proved to be impossible. Works Cited and Consulted Barber, C.L. "Rule and Misrule in Henry IV." William Shakespeare: Histories and Poems. Ed. Harold Bloom. New York: Chelsea House Publishers, 1986. 143-167. Bloom, Harold. Richard II, Part One: Bloom's Notes. New York: Chelsea House, 1996. Cruttwell,Patrick. Hernry IV. Shakespeare For Students, Vol. II. Detroit: Gale Publishing, 1999. Kantor, Andrea. Henry IV, Part One. London: Baron's Education Series, Inc, 1984. Princiss, G.M. Richard II Criticism. Shakespeare For Students, Vol.II. Detroit: Gale Publishing, 1999. Shakespeare, William. Richard II The Norton Shakespeare. Ed Stephen Greenblatt, et al. New York: W. W. Norton & Company, 1997. Shakespeare, William. Henry IV. In The Norten Anthology of English Literature. Eds. M.H. Abrams et all. 5th Ed. New York: Norton, 1987.

Guess Jeans E-commerce :: GCSE Business Marketing Coursework

Guess Jeans Ecommerce Guess?, Inc. designs, markets, and distributes clothing apparel and accessories for men and women. It was created by three brothers, known as the Marciano brothers who grew up in Southern France. Maurice Marciano oversees the company’s design direction, Paul Marciano is the Co-Chairman and Co-chief officer, and Armand Marciano is the Senior Executive Vice President . They were inspired by the American western tradition to begin the clothing designs of Guess ?. After Bloomingdale’s agreed to purchase two dozen of their jeans as a favor they were sold out with in hours. That’s when, in 1981, the official Guess ? label was born, and would become one of the most recognized brand names. Guess ? uses historical trends within the market to develop a sales plan for designs and as a guide to the number of sales per garmet. With the sales plan in mind they seek out the best quality product at the best possible price. Once the materials are gathered the cost of the item is determined. Including manufacturing labor, fabric, trims, and various other details included in the production of the clothing a rough cost is agreed upon. After the cost is found Guess ? then determines on a style merchandising cost, which is based on raising or lowering prices to maximize sales and profits. As of today Guess ? has product licenses all over the world. Also it has distributors in North America, South America, Europe, Asia, Africa, and Australia. Guess ? can be found in many department, retail, specialty, and factory stores and as of January 1995 online. Guess’s ? online store is created in Los Angeles, were its E-Commerce department is located. Their responsibility is to create texts, graphics, researches of new technologies, and track online sales. The Guess?.Com website is updated every two to three months so the most accurate information is always available to consumers. On the Guess ? website they support electronic security clearly stated at the bottom of the page. They have security measures set up to protect the consumer from any loss or misuse of information under their control. Credit card information and sign-in passwords are always stored in an unreadable, encrypted format. Also, the site is protected by a multi-layer firewall based security system. So any consumer information personal or not is well protected. Guess Jeans E-commerce :: GCSE Business Marketing Coursework Guess Jeans Ecommerce Guess?, Inc. designs, markets, and distributes clothing apparel and accessories for men and women. It was created by three brothers, known as the Marciano brothers who grew up in Southern France. Maurice Marciano oversees the company’s design direction, Paul Marciano is the Co-Chairman and Co-chief officer, and Armand Marciano is the Senior Executive Vice President . They were inspired by the American western tradition to begin the clothing designs of Guess ?. After Bloomingdale’s agreed to purchase two dozen of their jeans as a favor they were sold out with in hours. That’s when, in 1981, the official Guess ? label was born, and would become one of the most recognized brand names. Guess ? uses historical trends within the market to develop a sales plan for designs and as a guide to the number of sales per garmet. With the sales plan in mind they seek out the best quality product at the best possible price. Once the materials are gathered the cost of the item is determined. Including manufacturing labor, fabric, trims, and various other details included in the production of the clothing a rough cost is agreed upon. After the cost is found Guess ? then determines on a style merchandising cost, which is based on raising or lowering prices to maximize sales and profits. As of today Guess ? has product licenses all over the world. Also it has distributors in North America, South America, Europe, Asia, Africa, and Australia. Guess ? can be found in many department, retail, specialty, and factory stores and as of January 1995 online. Guess’s ? online store is created in Los Angeles, were its E-Commerce department is located. Their responsibility is to create texts, graphics, researches of new technologies, and track online sales. The Guess?.Com website is updated every two to three months so the most accurate information is always available to consumers. On the Guess ? website they support electronic security clearly stated at the bottom of the page. They have security measures set up to protect the consumer from any loss or misuse of information under their control. Credit card information and sign-in passwords are always stored in an unreadable, encrypted format. Also, the site is protected by a multi-layer firewall based security system. So any consumer information personal or not is well protected.

Evaluating a Health Promotion Website Essay -- Health Care, Nursing

Introduction This assignment intends to review the concept of nursing shift handover. Nursing handover can be defined as an important time to exchange information pertinent to the continued care of their patients (Pothier, Monteiro, Nooktlar et al. 2005). Methods of handover are varied, ranging from taped, verbal, by the bedside or with typed sheets. In 2010 there were 352,104 registered nurses, midwives and health visitors working in the NHS (RCN, 2011). All of these will partake in a handover of information on a regular basis, in hospitals this handover takes place at least twice day. In 2009/2010 there was 16,806,200 hospital stays in NHS hospitals (IC NHS, 2011). Information about their care would have been exchanged at shift changes, with the quality of each handover ensuring relevant care. Consequently, we can see that handovers effects thousands of nursing staff together with the thousands of patients in the hospital setting. The Health & Safety Executive (1996) stated that handover has several requisites, in particularly that communication between shifts should be accurate and without misunderstandings. The need to improve handovers is international recognized along with the obstacles that need to be overcome. Solutions need to address the healthcare professionals resistance to change, while understanding their time pressures. Additionally, issues relating to staffing levels, language differences and lack of research (WHO, 2007)need to be taken into account. According to Prouse (1995 cited by Carayon,) the cost of a handover in an UK hospice was approximately  £80, (with inflation  £125 (This is Money, 2011)). Additionally, Burke (1999) suggested using taped handovers saves a ward  £16,000 per annum, which may... ...400 results when refined with quantitative or qualitative keywords. Lastly, CINAHL produced best results when using a basic search with 'nursing handover' used, resulting in 23 articles. Each database requires different techniques, sometimes narrowing or opening the search parameters. Parameter of date and location were employed. Consequently, papers needed form 2001 onwards, original research and from the UK, thus avoiding cultural discrepancies and ensuring applicable to practice. Additionally, they needed to be hospital based and preferably in a ward setting. The qualitative paper selected was 'A qualitative study of shift handover practice and function' (Kerr, 2001) and the quantitative paper was 'A Pilot study to show the loss of important data in nursing handover'(Pothier D., Monteiro P., Nooktlar M. et al., 2005). These will now be critiqued in turn.

The Dark Side of Customer Analytics

HBR CASE STUDY AND COMMENTARYHow can these companies leverage the customer data responsibly? The Dark Side of Customer Analytics Four commentators offer expert advice. by Thomas H. Davenport and Jeanne G. Harris Reprint R0705A An insurance company finds some intriguing patterns in the loyalty card data it bought from a grocery chain—the correlation between condom sales and HIV-related claims, for instance. How can both companies leverage the data responsibly? HBR CASE STUDY The Dark Side of Customer Analytics COPYRIGHT  © 2007 HARVARD BUSINESS SCHOOL PUBLISHING CORPORATION. ALL RIGHTS RESERVED. by Thomas H. Davenport and Jeanne G. Harris Laura Brickman was glad she was almost done grocery shopping. The lines at the local ShopSense supermarket were especially long for a Tuesday evening. Her cart was nearly over? owing in preparation for several days away from her family, and she still had packing to do at home. Just a few more items to go: â€Å"A dozen eggs, a half gallon of orange juice, and—a box of Dip & Dunk cereal? † Her sixyear-old daughter, Maryellen, had obviously used the step stool to get at the list on the counter and had scrawled her high-fructose emand at the bottom of the paper in brightorange marker. Laura made a mental note to speak with Miss Maryellen about what sugary cereals do to kids’ teeth (and to their parents’ wallets). Taking care not to crack any of the eggs, she squeezed the remaining items into the cart. She wheeled past the ShopSense Summer Fun displays. â€Å"Do we need more sunscreen? † L aura wondered for a moment, before deciding to go without. She got to the checkout area and waited. As regional manager for West Coast operations of IFA, one of the largest sellers of life and health insurance in the United States, Laura ormally might not have paid much attention to Shop-Sense’s checkout procedures—except maybe to monitor how accurately her purchases were being rung up. But now that her company’s fate was intertwined with that of the Dallas-based national grocery chain, she had less motivation to peruse the magazine racks and more incentive to evaluate the scanning and tallying going on ahead of her. Some 14 months earlier, IFA and ShopSense had joined forces in an intriguing venture. Laura for years had been interested in the idea of looking beyond the traditional sources of customer data that insurers ypically used to set their premiums and develop their products. She’d read every article, book, and Web site she HBR’s cases, whic h are ? ctional, present common managerial dilemmas and offer concrete solutions from experts. harvard business review †¢ may 2007 page 1 H BR C A SE S T UDY †¢Ã¢â‚¬ ¢ †¢T he Dark Side of Customer Analytics Thomas H. Davenport ([email  protected] babson. edu) is the President’s Distinguished Professor of Information Technology and Management at Babson College, in Wellesley, Massachusetts, and the director of research for Babson Executive Education. Jeanne G. Harris (jeanne. g. [email  protected] com) is an executive research fellow and a director of research at the Accenture Institute for High-Performance Business. She is based in Chicago. Davenport and Harris are the coauthors of Competing on Analytics (Harvard Business School Press, 2007). page 2 could ? nd on customer analytics, seeking to learn more about how organizations in other industries were wringing every last drop of value from their products and processes. Casinos, credit card companies, even s taid old insurance ? rms were joining airlines, hotels, and other service-oriented businesses in gathering nd analyzing speci? c details about their customers. And, according to recent studies, more and more of those organizations were sharing their data with business partners. Laura had read a pro? le of ShopSense in a business publication and learned that it was one of only a handful of retailers to conduct its analytics in-house. As a result, the grocery chain possessed sophisticated data-analysis methods and a particularly deep trove of information about its customers. In the article, analytics chief Steve Worthington described how the organization employed a pattern-based approach to issuing coupons. The marketing department understood, for instance, that after three months of purchasing nothing but WayLess bars and shakes, a shopper wasn’t susceptible to discounts on a rival brand of diet aids. Instead, she’d probably respond to an offer of a free doughnut or pastry with the purchase of a coffee. The company had even been experimenting in a few markets with what it called Good-Sense messages—bits of useful health information printed on the backs of receipts, based partly on customers’ current and previous buying patterns. Nutritional analyses of some customers’ most recent purchases were eing printed on receipts in a few of the test markets as well. Shortly after reading that article, Laura had invited Steve to her of? ce in San Francisco. The two met several times, and, after some fevered discussions with her bosses in Ohio, Laura made the ShopSense executive an offer. The insurer wanted to buy a small sample of the grocer’s customer lo yalty card data to determine its quality and reliability; IFA wanted to and out if the ShopSense information would be meaningful when stacked up against its own claims information. With top management’s blessing, Steve and his team had agreed to provide IFA with ten ears’ worth of loyalty card data for customers in southern Michigan, where ShopSense had a high share of wallet—that is, the supermarkets weren’t located within ? ve miles of a â€Å"club† store or other major rival. Several months after receiving the tapes, analysts at IFA ended up ?nding some fairly strong correlations between purchases of unhealthy products (highsodium, high-cholesterol foods) and medical claims. In response, Laura and her actuarial and sales teams conceived an offering called Smart Choice, a low-premium insurance plan aimed at IFA customers who didn’t indulge. Laura was ? ing the next day to IFA’s headquarters in Cincinnati to meet with members of the senior team. She would be seeking their approval to buy more of the ShopSense data; she wanted to continue mining the information and re? ning IFA’s pricing and marketing efforts. Laura understood it might be a tough sell. After all, her industry wasn’t exactly known for embracing radical change—even with proof in hand that change could work. The make-or-break issue, she thought, would be the reliability and richness of the data. â€Å"Your CEO needs to hear only one thing,† Steve had told her several days earlier, while they were comparing notes. Exclusive rights to our data will give you information that your competitors won’t be able to match. No one else has the historical data we have or as many customers nationwide. † He was right, of course. Laura also knew that if IFA decided not to buy the grocer’s data, some other insurer would. â€Å"Paper or plastic? † a young boy was asking. Laura had ? nally made it to front of the line. â€Å"Oh, paper, please,† she replied. The cashier scanned in the groceries and waited while Laura swiped her card and signed the touch screen. Once the register printer had stopped chattering, the cashier curled the long strip of aper into a thick wad and handed it to Laura. â€Å"Have a nice night,† she said mechanically. Before wheeling her cart out of the store into the slightly cool evening, Laura brie? y checked the total on the receipt and the information on the back: coupons for sunblock and a reminder about the importance of UVA and UVB protection. Tell It to Your Analyst â€Å"No data set is perfect, but based on what we’ve seen already, the ShopSense info could be a pretty rich source of insight for us,† Archie Stetter told the handful of executives seated around a table in one of IFA’s recently renovated conference rooms. Laura nodded in agreement, silently cheering on the insurance harvard business review †¢ may 2007 T he Dark Side of Customer Analytics †¢Ã¢â‚¬ ¢ †¢H BR C A SE S T UDY company’s uberanalyst. Archie had been invaluable in guiding the pilot project. Laura had ? own in two days ahead of the meeting and had sat down with the chatty statistics expert and some members of his team, going over results and gauging their support for continuing the relationship with ShopSense. â€Å"Trans fats and heart disease—no surprise there, I guess,† Archie said, using a laser pointer to direct the managers’ attention to a PowerPoint slide projected on the wall. How about this, though: Households that purchase both bananas and cashews at least quarterly seem to show only a negligible risk of developing Parkinson’s and MS. † Archie had at ? rst been skeptical about the quality of the grocery chain’s data, but ShopSense’s well of informati on was deeper than he’d imagined. Frankly, he’d been having a blast slicing and dicing. Enjoying his moment in the spotlight, Archie went on a bit longer than he’d intended, talking about typical patterns in the purchase of certain over-the-counter medications, potential leading indicators for diabetes, and other statistical curiosities. Laura noted that as Archie’s presentation wore on, CEO Jason Walter was jotting down notes. O. Z. Cooper, IFA’s general counsel, began to clear his throat over the speakerphone. Laura was about to rein in her stats guy when Rusty Ware, IFA’s chief actuary, addressed the group. â€Å"You know, this deal isn’t really as much of a stretch as you might think. † He pointed out that the company had for years been buying from information brokers lists of customers who purchased speci? c drugs and products. And IFA was among the best in the industry at evaluating external sources of data (credit histories, demographic studies, analyses f socioeconomic status, and so on) to predict depression, back pain, and other expensive chronic conditions. Prospective IFA customers were required to disclose existing medical conditions and information about their personal habits—drinking, smoking, and other high-risk activities—the actuary reminded the group . The CEO, meanwhile, felt that Rusty was overlooking an important point. â€Å"But if we’re ?nding patterns where our rivals aren’t even looking, if we’re coming up with proprietary health indicators—well, that would be a huge hurdle for everyone else to get over,† Jason noted. arvard business review †¢ may 2007 Laura was keeping an eye on the clock; there were several themes she still wanted to hammer on. Before she could follow up on Jason’s comments, though, Geneva Hendrickson, IFA’s senior vice president for ethics and corporate responsibility, posed a blue-sky question to the group: â€Å"Take the fruit-and-nut stat Archie cited. Wouldn’t we have to share that kind of information? As a bene? t to society? † Several managers at the table began talking over one another in an attempt to respond. â€Å"Correlations, no matter how interesting, aren’t conclusive evidence of causality,† someone said. Ev en if a correlation doesn’t hold up in the medical community, that doesn’t mean it’s not useful to us,† someone else suggested. Laura saw her opening; she wanted to get back to Jason’s point about competitive advantage. â€Å"Look at Progressive Insurance,† she began. It was able to steal a march on its rivals simply by recognizing that not all motorcycle owners are created equal. Some ride hard (young bikers), and some hardly ride (older, middle-class, midlife crisis riders). â€Å"By putting these guys into different risk pools, Progressive has gotten the rates right,† she said. â€Å"It wins all the business with the safe set by offering low remiums, and it doesn’t lose its shirt on the more dangerous set. † Then O. Z. Cooper broke in over the speakerphone. Maybe the company should formally position Smart Choice and other products and marketing programs developed using the Shop-Sense data as opt in, he wondered. A lot of people signed up when Progressive gave discounts to customers who agreed to put devices in their cars that would monitor their driving habits. â€Å"Of course, those customers realized later they might pay a higher premium when the company found out they routinely exceeded the speed limit—but that’s not a legal problem,† O. Z. noted. None of the states that IFA did business in had laws prohibiting the sort of data exchange ShopSense and the insurer were proposing. It would be a different story, however, if the company wanted to do more business overseas. At that point, Archie begged to show the group one more slide: sales of prophylactics versus HIV-related claims. The executives continued taking notes. Laura glanced again at the clock. No one seemed to care that they were going a little over. â€Å"Exclusive rights to our data will give you information that your competitors won’t be able to match. No one else has the historical data we have. † page 3 H BR C A SE S T UDY †¢Ã¢â‚¬ ¢ †¢T he Dark Side of Customer Analytics Data Decorum â€Å"Customers find out, they stop using their cards, and we stop getting the information that drives this whole train. † page 4 Rain was in the forecast that afternoon for Dallas, so Steve Worthington decided to drive rather than ride his bike the nine and a half miles from his home to ShopSense’s corporate of? ces in the Hightower Complex. Of course, the gridlock made him a few minutes late for the early morning meeting with ShopSense’s executive team. Lucky for him, others had been held up by the traf? c as well. The group gradually came together in a lightly cluttered room off the main hallway on the 18th ? oor. One corner of the space was being used to store prototypes of regional instore displays featuring several members of the Houston Astros’ pitching staff. â€Å"I don’t know whether to grab a cup of coffee or a bat,† Steve joked to the other s, gesturing at the life-size cardboard cutouts and settling into his seat. Steve was hoping to persuade CEO Donna Greer and other members of the senior team to approve the terms of the data sale to IFA. He was pretty con? dent he had majority support; he had already spoken individually with many of the top executives. In those one-onone conversations, only Alan Atkins, the grocery chain’s chief operations of? cer, had raised any signi? cant issues, and Steve had dealt patiently with each of them. Or so he thought. At the start of the meeting, Alan admitted he still had some concerns about selling data to IFA at all. Mainly, he was worried that all the hard work the organization had done building up its loyalty program, honing its analytical chops, and maintaining deep customer relationships could be undone in one fell swoop. â€Å"Customers ? nd out, they stop using their cards, and we stop getting the information that rives this whole train,† he said. Steve reminded Alan that IFA had no interest in revealing its relationship with the grocer to customers. There was always the chance an employee would let something slip, but even if that happened, Steve doubted anyone would be shocked. â€Å"I haven’t heard of anybody canceling based on any of our other card-driven marketing p rograms,† he said. â€Å"That’s because what we’re doing isn’t visible to our customers—or at least it wasn’t until your recent comments in the press,† Alan grumbled. There had been some tension within the group about Steve’s contribution to everal widely disseminated articles about ShopSense’s embrace of customer analytics. â€Å"Point taken,† Steve replied, although he knew that Alan was aware of how much positive attention those articles had garnered for the company. Many of its card-driven marketing programs had since been deemed cuttingedge by others in and outside the industry. Steve had hoped to move on to the ? nancial bene? ts of the arrangement, but Denise Baldwin, ShopSense’s head of human resources, still seemed concerned about how IFA would use the data. Speci? cally, she wondered, would it identify individual consumers as employees of particular companies? She reminded the group that some big insurers had gotten into serious trouble because of their pro? ling practices. IFA had been looking at this relationship only in the context of individual insurance customers, Steve explained, not of group plans. â€Å"Besides, it’s not like we’d be directly drawing the risk pools,† he said. Then Steve began distributing copies of the spreadsheets outlining the ? ve-year returns ShopSense could realize from the deal. â€Å"‘Directly’ being the operative word here,† Denise noted wryly, as she took her copy and passed the rest around. Parsing the Information It was 6:50 pm, and Jason Walters had canceled his session with his personal trainer— again—to stay late at the of? ce. Sammy will understand, the CEO told himself as he sank deeper into the love seat in his of? ce, a yellow legal pad on his lap and a pen and cup of espresso balanced on the arm of the couch. It was several days after the review of the ShopSense pilot, and Jason was still weighing the risks and bene? ts of taking this business relationship to the next stage. He hated to admit how giddy he was— almost as gleeful as Archie Stetter had been— about the number of meaningful correlations the analysts had turned up. Imagine what that guy could do with an even larger data set,† O. Z. Cooper had commented to Jason after the meeting. Exclusive access to ShopSense’s data would give IFA a leg up on competitors, Jason knew. It could also provide the insurer with proprietary insights into the food-related drivers of disease. The deal was cer tainly legal. And even in the court of public opinion, people understood that insurers had to perform risk analyses. It wasn’t the same as when that harvard business review †¢ may 2007 T he Dark Side of Customer Analytics †¢Ã¢â‚¬ ¢ †¢H BR C A SE S T UDY online bookseller got into trouble for charging ustomers differently based on their shopping histories. But Jason also saw dark clouds on the horizon: What if IFA took the pilot to the next level and found out something that maybe it was better off not knowing? As he watched the minute hand sweep on his wall clock, Jason wondered what risks he might be taking without even realizing it. †¢Ã¢â‚¬ ¢Ã¢â‚¬ ¢ Donna Greer gently swirled the wine in her glass and clinked the stemware against her husband’s. The two were attending a wine tasting hosted by a friend. The focus was on varieties from Chile and other Latin American countries, and Donna and Peter had yet to ? nd a sample they didn’t like. But despite the lively patter of the event and the plentiful food. Donna couldn’t keep her mind off the IFA deal. â€Å"The big question is, Should we be charging more? † she mused to her husband. ShopSense was already selling its scanner data to syndicators, and, as her CFO had reminded her, the company currently made more money from selling information than from selling meat. Going forward, all ShopSense would have to do was send IFA some tapes each month and collect a million dollars annually harvard business review †¢ may 2007 of pure pro? t. Still, the deal wasn’t without risks: By selling the information to IFA, it ight end up diluting or destroying valuable and hard-won customer relationships. Donna could see the headline now: â€Å"Big Brother in Aisle Four. † All the more reason to make it worth our while, she thought to herself. Peter urged Donna to drop the issue for a bit, as he scribbled his comments about the wine they’d just samp led on a rating sheet. â€Å"But I’ll go on record as being against the whole thing,† he said. â€Å"Some poor soul puts potato chips in the cart instead of celery, and look what happens. † â€Å"But what about the poor soul who buys the celery and still has to pay a fortune for medical overage,† Donna argued, â€Å"because the premiums are set based on the people who can’t eat just one? † â€Å"Isn’t that the whole point of insurance? † Peter teased. The CEO shot her husband a playfully peeved look—and reminded herself to send an e-mail to Steve when they got home. What if IFA took the pilot to the next level and found out something that maybe it was better off not knowing? How can these companies leverage the customer data responsibly? †¢ Four commentators offer expert advice. See Case Commentary page 5 T he Dark Side of Customer Analytics †¢ H BR C A SE S T UDY C ase Commentary by George L. Jones How can these companies leverage the customer data responsibly? The message coming from both IFA and ShopSense is that any marketing opportunity is valid—as long as they can get away with it. page 6 Sure, a customer database has value, and a company can maximize that value in any number of ways—growing the database, mining it, monetizing it. Marketers can be tempted, despite pledges about privacy, to use collected information in ways that seem attractive but may ultimately damage relationships with customers. The arrangement proposed in this case study seems shortsighted to me. Neither company seems to particularly care about its customers. Instead, the message coming from the senior teams at both IFA and ShopSense is that any marketing opportunity is valid—as long as they can get away with it legally and customers don’t ? gure out what they’re doing. In my company, this pilot would never have gotten off the ground. The culture at Borders is such that the managers involved would have just assumed we wouldn’t do something like that. Like most successful retail companies, our organization is customer focused; we’re always trying to see a store or an offer or a transaction through the customer’s eyes. It was the same way at both Saks and Target when I was with those companies. At Borders, we’ve built up a signi? cant database through our Borders Rewards program, which in the past year and a half has grown to 17 million members. The data we’re getting are hugely important as a basis for serving customers more effectively (based on their purchase patterns) and as a source of competitive advantage. For instance, we know that if somebody buys a travel guide to France, that person might also be interested in reading Peter Mayle’s A Year in Provence. But we assure our customers up front that their information will be handled with the utmost respect. We carefully control the content and frequency of even our own ommunications with Rewards members. We don’t want any offers we present to have negative connotations—for instance, we avoid bombarding people with e-mails about a product they may have absolutely no interest in. I honestly don’t think these companies have hit upon a responsible formula for mining and sharing cust omer data. If ShopSense retained control of its data to some degree—that is, if the grocer and IFA marketed the Smart Choice program jointly, and if any offers came from ShopSense (the partner the customer has built up trust with) rather than the insurance company (a stranger, so to speak)—the relationship could work. Instead of ceding complete control to IFA, ShopSense could be somewhat selective and send offers to all, some, or none of its loyalty card members, depending on how relevant the grocer believed the insurance offer would be to a particular set of customers. A big hole in these data, though, is that people buy food for others besides themselves. I rarely eat at home, but I still buy tons of groceries—some healthy, some not so healthy— for my kids and their friends. If you looked at a breakdown of purchases for my household, you’d say â€Å"Wow, they’re consuming a lot. † But the truth is, I hardly ever eat a bite. That may e an extreme example, but it suggests that IFA’s correlations may be ? awed. Both CEOs are subjecting their organizations to a possible public relations backlash, and not just from the ShopSense customers whose data have been dealt away to IFA. Every ShopSense customer who hears about the deal, loyalty card member or not, is going to lose trust in the company. IFA’s customers might also think twice about their relationship with the insurer. And what about the employees in each company who may be uncomfortable with what the companies are trying to pull off? The corporate cultures suffer. What the companies are proposing here is ery dangerous—especially in the world of retail, where loyalty is so hard to win. Customers’ information needs to be protected. George L. Jones is the president and chief executive officer of Borders Group, a global retailer of books, music, and movies based in Ann Arbor, Michigan. harvard business review †¢ may 2007 T he Dark Side of Customer Analytics †¢ H BR C A SE S T UDY C ase Commentary by Katherine N. Lemon How can these companies leverage the customer data responsibly? Customer analytics are effective precisely because firms do not violate customer trust. harvard business review †¢ may 2007 As the case study illustrates, companies will o on be able to create fairly exhaustive, highly accurate pro? les of customers without having had any direct interaction with them. They’ll be able to get to know you intimately without your knowledge. From the consumer’s perspective, this trend raises several big concerns. In this ? ctional account, for instance, a shopper’s grocery purchases may directly in? uence the availability or price of her life or health insurance products—and not necessarily in a good way. Although the customer, at least tacitly, consented to the collection, use, and transfer of her purchase data, the real issue here is the nintended and uncontemplated use of the information (from the customer’s point of view). Most customers would probably be quite surprised to learn that their personal information could be used by companies in a wholly unrelated industry and in other ways that aren’t readily foreseeable. If consumers lose trust in ? rms that collect, analyze, and utilize their information, they will opt out of loyalty and other data-driven marketing programs, and we may see more regulations and limitations on data collection. Customer analytics are effective precisely because ? rms do not violate customer trust. People believe that retail and other organizations will use their data wisely to enhance their experiences, not to harm them. Angry customers will certainly speak with their wallets if that trust is violated. Decisions that might be made on the basis of the shared data represent another hazard for consumers—and for organizations. Take the insurance company’s use of the grocer’s loyalty card data. This is limited information at best and inaccurate at worst. The ShopSense data re? ect food bought but not necessarily consumed, and individuals buy food at many stores, not just one. IFA might end up drawing rroneous conclusions—and exacting unfair rate increases. The insurer’s general counsel should investigate this deal. Another concern for consumers is what I call â€Å"battered customer syndrome. † Market analytics allow companies to identify their best and worst customers and, consequently, to pay special attention to those deemed to be the mo st valuable. Looked at another way, analytics enable ? rms to understand how poorly they can treat individual or groups of customers before those people stop doing business with them. Unless you are in the top echelon of customers— those with the highest lifetime value, say—you ay pay higher prices, get fewer special offers, or receive less service than other consumers. Despite the fact that alienating 75% to 90% of customers may not be the best idea in the long run, many retailers have adopted this â€Å"top tier† approach to managing customer relationships. And many customers seem to be willing to live with it—perhaps with the unrealistic hope that they may reach the upper echelon and reap the ensuing bene? ts. Little research has been done on the negative consequences of using marketing approaches that discriminate against customer segments. Inevitably, however, customers will ecome savvier about analytics. They may become less tolerant and take their business (and information) elsewhere. If access to and use of customer data are to remain viable, organizations must come up with ways to address customers’ concerns about privacy. What, then, should IFA and ShopSense do? First and foremost, they need to let customers opt in to their data-sharing arrangement. This would address the â€Å"unintended use of data† problem; customers would understand exactly what was being done with their information. Even better, both ? rms would be engaging in trust-building—versus trust-eroding—activities with customers. The esult: improvement in the bottom line and in the customer experience. Katherine N. Lemon (kay. [email  protected] edu) is an associate professor of marketing at Boston College’s Carroll School of Management. Her expertise is in the areas of customer equity, customer management, and customer-based marketing strategy. page 7 T he Dark Side of Customer Analytics †¢ H BR C A SE S T UDY C ase Commentary by David Norton How can these companies leverage the customer data responsibly? Would customers feel comfortable with the data-sharing arrangement if they knew about it? page 8 Transparency is a critical component of any loyalty card program. The value proposition must be clear; customers must know what they’ll get for allowing their purchase behavior to be monitored. So the question for the CEOs of ShopSense and IFA is, Would customers feel comfortable with the data-sharing arrangement if they knew about it? ShopSense’s loyalty card data are at the center of this venture, but the grocer’s goal here is not to increase customer loyalty. The value of its relationship with IFA is solely ? nancial. The company should explore whether there are some customer data it should exclude from the transfer—information that could be perceived as exceedingly sensitive, such as pharmacy and lcohol purchases. It should also consider doing market research and risk modeling to evaluate customers’ potential reaction to the data sharing and the possible downstream effect of the deal. The risk of consumer backlash is lower for IFA than for ShopSense, given the information the insurance company already purchase s. IFA could even put a positive spin on the creation of new insurance products based on the ShopSense data. For instance, so-called healthy purchases might earn customers a discount on their standard insurance policies. The challenge for the insurer, however, is that there is no proven correlation between the urchase of certain foods and fewer health problems. IFA should continue experimenting with the data to determine their richness and predictive value. Some companies have more leeway than others to sell or trade customer lists. At Harrah’s, we have less than most because our customers may not want others to know about their gaming and leisure activities. We don’t sell information, and we don’t buy a lot of external data. Occasionally, we’ll buy demographic data to ? ne-tune our marketing messages (to some customers, an offer of tickets to a live performance might be more interesting than a dining discount, for example). But we think the internal transactional data are much more important. We do rely on analytics and models to help us understand existing customers and to encourage them to stick with us. About ten years ago, we created our Total Rewards program. Guests at our hotels and casinos register for a loyalty card by sharing the information on their driver’s license, such as their name, address, and date of birth. Each time they visit one of our 39 properties and use their card, they earn credits that can be used for food and merchandise. They also earn Tier Credits that give them higher status in the program and ake them eligible for differentiated service. With every visit, we get a read on our customers’ preferences—the types of games they play, the hotels and amenities they favor, and so on. Those details are stored in a central database. The company sets rules for what can be done with the information. For instance, managers at any one of our properties can execute th eir own marketing lists and programs, but they can target only customers who have visited their properties. If they want to dip into the overall customer base, they have to go through the central relationship-marketing group. Some of the information captured in ur online joint promotions is accessible to both Harrah’s and its business partners, but the promotions are clearly positioned as opt in. We tell customers the value proposition up front: Let us track your play at our properties, and we can help you enjoy the experience better with richer rewards and improved service. They understand exactly what we’re capturing, the rewards they’ll get, and what the company will do with the information. It’s a win-win for the company and for the customer. Companies engaging in customer analytics and related marketing initiatives need to keep â€Å"win-win† in mind when collecting and andling customer data. It’s not just about what the information can do for you; it’s about what you can do for the customer with the information. David Norton ([email  protected] com) is the senior vice president of relationship marketing at Harrah’s Entertainment, based in Las Vegas. harvard business review †¢ may 2007 T he Dark Side of Customer Analytics †¢ H BR C A SE S T UDY C ase Commentary by Michael B. McCallister How can these companies leverage the customer data responsibly? When the tougher, grayarea decisions need to be made, each person has to have the company’s core principles and values in ind. harvard business review †¢ may 2007 Companies that can capitalize on the information they get from their customers hold an advantage over rivals. But as the ? rms in the case study are realizing, there are also plenty of risks involved with using these data. Instead of pulling back the reins, organizations should be nudging customer analytics forward, keeping in mind one critical point: Any collection, anal ysis, and sharing of data must be conducted in a protected, permission-based environment. Humana provides health bene? t plans and related health services to more than 11 million embers nationwide. We use proprietary datamining and analytical capabilities to help guide consumers through the health maze. Like IFA, we ask our customers to share their personal and medical histories with us (the risky behaviors as well as the good habits) so we can acquaint them with programs and preventive services geared to their health status. Customer data come to us in many different ways. For instance, we offer complimentary health assessments in which plan members can take an interactive online survey designed to measure how well they’re taking care of themselves. We then suggest ways they can reduce their health risks or treat their existing conditions more effectively. We closely monitor our claims information and use it to reach out to people. In our Personal Nurse program, for example, we’ll have a registered nurse follow up with a member who has ? led, say, a diabetes-related claim. Through phone conversations and e-mails, the RN can help the plan member institute changes to improve his or her quality of life. All our programs require members to opt in if the data are going to be used in any way that would single a person out. Regardless of your industry, you have to start with that. One of the biggest problems in U. S. health care today is obesity. So would it be useful for our company to look at grocery-purchasing patterns, as the insurance company in the case study does? It might be. I could see the upside of using a grocer’s loyalty card data to develop a wellness-based incentive program for insurance customers. (We would try to ? nd a way to build positives into it, however, so customers would look at the interchange and say â€Å"That’s in my best interest; thank you. †) But Humana certainly wouldn’t enter into any kind of datatransfer arrangement without ensuring that our customers’ personal information and the ntegrity of our relationship with them would be properly protected. In health care, especially, this has to be the chief concern—above and beyond any patterns that might be revealed and the sort of competitive edge they might provide. We use a range of industry standard security measures, including encryptio n and ? rewalls, to protect our members’ privacy and medical information. Ethical behavior starts with the CEO, but it clearly can’t be managed by just one person. It’s important that everyone be reminded often about the principles and values that guide the organization. When business opportunities come along, they’ll be screened according to those standards—and the decisions will land right side up every time. I can’t tell people how to run their meetings or who should be at the table when the tougher, grayarea decisions need to be made, but whoever is there has to have those core principles and values in mind. The CEOs in the case study need to take the â€Å"front page† test: If the headline on the front page of the newspaper were reporting abuse of customer data (yours included), how would you react? If you wouldn’t want your personal data used in a certain way, chances are your customers wouldn’t, either. Michael B. McCallister ([email  protected] com) is the president and CEO of Humana, a health benefits company based in Louisville, Kentucky. 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