External Factor Evaluation For Costco Company Essay Example

Introduction

The EFE Matrix is an important evaluation tool for achieving the organization goals. This helps identify the balance between the available opportunities and the prevailing threats in the industry from an external perspective. The purpose of detecting opportunities and threats is to take advantage of the advantages and reduce the risk that threats entail. In other words, knowing the environment where we are, increases the degree of probability of achieving the objectives and achieving a successful business (Wijayati et al., 2019). This study presents the EFE evaluation for Costco Wholesale Corp.

Costco Wholesale Corp. is an American wholesale company based in Seattle in the state of Washington. Costco is the world’s largest cash and carries company and the third-largest grocery retailer in North America (Rahman, 2020). The statistics show the number of branches of the grocery retailer Costco in the financial years 2006/07 up to and including 2020/21. In the fiscal year 2020/21, Costco had 815 locations worldwide, as of August 30, 2021 (Johnson, 2021).

External environment evaluation

The success of a strategy is not only about recognizing the internal factors of a brand, but also knowing the external environment, evaluating the latent threats that exist and that can affect the scalability of a company or brand and the opportunities that can arise and take advantage to increase growth. The objective of this external analysis is to form a list of opportunities that the company can take advantage of and threats that must be overcome. This list should be limited to those key factors that are feasible to manage and for which strategies can be generated. Differing from the EFI Matrix, this instrument allows us to understand, anticipate and know the environment in which our business or activity is carried out. In addition, it allows the detection of courses of action aimed at increasing the chances of success (Zulkarnain, et al., 2018).

To develop an EFE matrix, we will first identify 10 factors relating to Costco company are selected, where opportunities and threats must be included, which influence the brand and the sector it is dedicated to, this is one of the main differences between the EFI and EFE matrix, since the matrix EFE must evaluate the entire environment, including competitors or neighbours who are located in the same sector. It is recommended to write the opportunities and then the threats, since you can focus on looking for the factors that you can exploit, however my recommendation is that on a separate sheet or document you write the details that arise, regardless of whether they are opportunities or threats.

A mandatory aspect is that each factor must be as specific as possible, and if it has reports with supporting figures, it would be excellent if you included it in the analysis. The opportunities and threats that can affect Costco Company will be defined, it should be noted that this case study was used for the development of the EFE matrix: The analysis of Costco com will be carried out, where it will focus on wholesale services (Wijayati et al., 2019). At first, the brand had a great presence and the works were sold without investing much effort or time. However, in recent years, due to socioeconomic problems, sales have dropped suddenly, affecting the profitability of the brand. Therefore, it was decided to hire professionals in the areas of entrepreneurship, finance, and marketing to refresh the brand image and, of course, boost sales.

Identifying opportunities and threats

Opportunities:

  1. Exploration of current digital technology, to boost wholesales volumes.
  2. Make alliances with other wholesalers.
  3. Use the presence of each location to boost the presence of the business.
  4. Accept different payment methods (transfer, deposit, check, payment platforms, TDC) and currencies (dollars, euros, crypto currencies, among others).
  5. Creating experiential service categories, this means that not only the products will be sold but also an experience will be sold to the buyer.

Threats:

  1. Stiff competition in the industry by large wholesale firms which have a presence in digital media.
  2. The wholesale industry has become a bloody competition as giant firms from different branches emerge every day.
  3. Shipping has become much more tedious, since the pieces are delicate and sometimes arrive with details or completely damaged.
  4. Wholesale business is subjective, this means that the value of the goods is very variable and depends a lot on the specialist who evaluates and determines the value, and more so if it is a serial work; the value can also be influenced by the reputation and reputation of manufacturers.
  5. Not having enough space to store goods before sale.

Assigning relative weights and rating to each factor

The weight of each factor ranges from 0.0, less important, to 1.0, very important. It should be emphasized that the weight indicates the importance of the factor and its influence on achieving success in the sector. Opportunities mostly have a high weight over threats, however if the threat can threaten the stability and growth of the brand, its weight is just as high as an opportunity. In order to determine with more certainty the weight for each factor, it is recommended to make a comparison with the competitors that are more successful in the area to define the impact they have made. The sum of all the factors must give 1.0, it cannot be less or more.

We then attribute a rating to each one, which is divided into four values between 1 and 4 for each of the factors, in order to indicate whether the factor represents a major weakness (score = 1), a minor weakness (score = 2), a minor force (rating = 3) or a major force (rating = 4) . Thus, the ratings refer to the effectiveness of the strategies while the weights of step 2 are based on the sector or area.

It is important that you know that opportunities usually have higher weights than threats, but these, in turn, can have high weights if they are especially serious or threatening. Appropriate weights can be determined by comparing successful competitors with unsuccessful ones or by analyzing the factor as a group and reaching a consensus (Wijayati et al., 2019). The sum of all the weights assigned to the factors must add up to 1.0. An important fact is that the weight assigned in this step is based on the whole industry.

External Factor Evaluation (EFE) matrix
Key external factor Weight Rating Weighted score
Opportunities
1. Exploration of current digital technology, to boost wholesales volumes. 0.14 4 0.56
2. Make alliances with other wholesalers. 0.1 4 0.40
3. Use the presence of each location to boost the presence of the business. 0.2 4 0.80
4. Accept different payment methods (transfer, deposit, check, payment platforms, TDC) and currencies (dollars, euros, crypto currencies, among others). 0.1 3 0.30
5. Creating experiential service categories, this means that not only the products will be sold but also an experience will be sold to the buyer. 0.1 3 0.30
Threats
1. Stiff competition in the industry by large wholesale firms which have a presence in digital media. 0.08 2 0.16
2. Shifting consumer preference towards retail shopping which increases competition as giant firms from different branches emerge every day. 0.08 2 0.16
3. Shipping has become much more tedious, since the pieces are delicate and sometimes arrive with details or completely damaged. 0.08 2 0.16
4. Wholesale business is subjective, this means that the value of the goods is very variable and depends a lot on the specialist who evaluates and determines the value, and more so if it is a serial work; the value can also be influenced by the reputation and reputation of manufacturers. 0.06 1 0.06
5. Not having enough space to store goods before sale. 0.06 1 0.06
Total 2.96

Discussion

To complete the analysis, it is necessary to evaluate and obtain the total value of the opportunities, which gives a value of 2.36 and the total value of the threats is 0.60. If the value of the opportunities is higher than the threats, it means that the external environment is favourable for Costco, but if it is the opposite, the weaknesses of the brands must be analysed and reinforced and the strengths of the brand strengthened to create a shield against the external environment (Wijayati et al., 2019).

Regardless of the number of factors considered in the evaluation, the highest score will be 4, which means that the organization is addressing all factors in an extraordinary way, taking advantage of all opportunities and keeping all threats under control. The lowest possible score is 1, where the organization is not addressing any factor analysed and therefore has a long way to go to develop plans and actions to improve. Although there are several aspects in which the organization can improve, at this moment it is above average in terms of addressing the external factors that create opportunities and threats (Leliga et al., 2019).

Conclusion

The EFE Matrix is an important evaluation tool for achieving the organization goals. When organizations establish strategies, it is not enough to know and describe the internal factors of the brand, without considering the external environment. The EFE matrix serves this role. Every industry environment is made up of threats that can affect a company or brand, and opportunities that can arise and take advantage of for exponential growth. The external factors evaluation matrix (EFE) allows information to be summarized and evaluated. This information can be of an economic, social, cultural, demographic, environmental, political, governmental, legal, technological and competitive nature.

References

Johnson, E. A. (2021). Costco Wholesale’s Dominance in the Market.

Rahman, M. H. (2020). Financial Analysis Of Costco Wholesale Corporation: Exploring The Strengths And Weaknesses. The Bangladesh Journal of Agricultural Economics41(1), 17-34.

Zulkarnain, A., Wahyuningtias, D., & Putranto, T. S. (2018, March). Analysis of IFE, EFE, and QSPM matrix on business development strategy. In IOP Conference Series: Earth and Environmental Science (Vol. 126, No. 1, p. 012062). IOP Publishing.

Leliga, F. J., Koapaha, J. D., & Sulu, A. C. (2019). Analysis of Internal Factor Evaluation Matrix, External Factor Evaluation Matrix, Threats-Opportunities-Weaknesses-Strengths Matrix, and Quantitative Strategic Planning Matrix on Milk Products and Nutrition Segment of Nestlé India. East African Scholars Journal of Economics, Business and Management, 2(4), 186-191.

Wijayati, I. F., Setio, I., & Tanupatra, S. M. (2019). Strategic Analysis of Internal, External Factor Evaluation Matrix and Strategic Planning in BTPN bank, Indonesia. Strategic Analysis.

Factors Associated With Medication Administration Errors And Why Nurses Fail To Report Them Free Sample

Problem Statement

As the nurse manager of *hypothetical unit*, I have identified that nurses’ failure to report errors arising during medication administration is a problem within my unit. I have reviewed the literature for evidence-based strategies to improve the rate of reporting errors that occur during medication administration and reduce the chance of these errors happening. I will review my findings and plan in this presentation.

Introduction

In a health care institution, the aim is to help a patient recover from any illness, and therefore patient receiving wrong medication is a significant concern. This prompted the author of the article, Factors associated with medication administration errors and why nurses fail to report them, to discuss factors that cause errors during medication administration and analyze why nurses choose not to report these errors when they occur. Administration of drugs is a critical process in supplementing any patient’s recovery from an illness. The article was written to outline why errors occur during medication administration and reduce these errors. Additionally, the article explains to nurses their role in the medication administration process and why it is vital in ensuring patient safety. The article discusses three research questions; are the percentages of different medication errors reported by nurses, are the reasons underlying MAEs from the nurse’s perspective, and are the most common barriers to medication error reporting by nurses. The author is concerned about patient safety in hospitals and writes the article to address factors that cause medical administration errors and the role of nurses in these factors.

Results

This research focused on nurses’ understanding of their role in medical administration, and thus nurses were the research sample. Feedback was acquired from nurses through a questionnaire. The questionnaire was tailored to answer questions on the demographic data of the sampled participants and medical administration errors. The variables measured that concerned the demographic data of participants were;

  • Age
  • Sex
  • Education Level
  • Working Unit
  • Years of Experience
  • Current Position

The variables measured to answer on medical administration errors were;

  • Reasons why medication errors occur
  • Reasons why errors are not reported
  • Percentage of errors reported

The questionnaire used a six-point Linkert-type scale to measure the variables concerning the medical administration errors, except for the percentage of errors reported where the questionnaire used a 10 point scale. The sample size consisted of 500 nurses, with 367 providing feedback (Hammoudi et al., 2018). The sample was selected based on a registered nurse with a valid MOH license who has worked in the same hospital for more than six months. The data collected from the questionnaire were analyzed using SPSS software, and descriptive analysis was used to answer the research questions. These are the variables measured by the research instrument and how the results were analyzed.

The research was dependent on the demographic of the sample size and the analysis of medication administration errors made. The results of the demographic data showed that 89.9% of the sample size were women. Of the total sample size, 63.5% were aged between 35 and 25 years, 27.5% were between 45 and 35 years, 5.2% were above 45 years of age, and 3.8% were under 25 years. This stat was directly proportional to the participants’ years of experience as of the total sample size, 37.6% had between 5 and 10 years of experience, 26.7% had between 2 and 5 years of experience, and 4.6% had less than two years of experience. Most of the participants had a bachelor’s degree in nursing, represented by 75.7%, with 22.1% holding a diploma degree in nursing, and only 2.3% had a master’s or doctoral degree in nursing. This is the summary of the demographic data based on age and years of experience.

Regarding position held, 84.7% of the participants had a normal staff nurse position, 11.2% were either supervisors or charge nurses, 2.2% held a position involving nurses’ education, and 1.9% of the participants were either head nurses or nurse managers. Additionally, the demographic data showed that 73% of the nurses had worked for more than one year at the same hospital, while the remaining percentage had worked for between 6 to 12 months at the same hospital. 22.6% of the sample did not specify the working unit they were involved in, while 59.4% were involved with the general unit, and 18% were involved with closed nursing units (Hammoudi et al., 2018). This is the summary of the results involving the participants’ demographic data.

The answers to the questions asked grouped the medication administration error research results. The results were based on five subscales: medication packaging, transcription-related reasons, nurse staffing, pharmacy procedures, and doctor communication. The subscale of medication packaging focused on similarities in medicine packages, with the highest point being awarded to answers of whether there was a similarity in the package and the lowest point being awarded to answers for the similarity between names. The mean for this subscale was 4.34, with a standard deviation of 1.35. The second subscale focused on errors made during transcribing, and the highest point was awarded to questions that answered whether errors are made on the medication sheet. The lowest point was awarded to questions that answered whether there was a failure of reporting delayed schedules for medication. The mean for this subscale was 3.15, with a standard deviation of 1.51. The mean for the subscale on communication between doctors and nurses was 3.96, with a standard deviation of 1.36. The mean for the subscale of procedures in the pharmacy was 3.43, with a standard deviation of 1.45. Lastly, the mean for the number of available staff subscale was 3.4, with a standard deviation of 1.50 (Hammoudi et al., 2018). This is the summary of the medication administration error survey results.

Conclusion

It can be concluded that the factors that cause errors in medication administration are communication between doctors and nurses, available staff, packaging of medicine, transcription issues, and processes that take place in the pharmacy. The plan to use the results of these findings involves implementing a health informatics system. This will eliminate the errors that occur due to human fault. The article was influential in solving the problem as it clearly outlines how and why the factors that cause errors in medication administration areas. This can help any researcher in the future to identify any of these issues as they arise in their nursing unit. I would suggest that our leadership ensure that all our nurses are conversant with the health informatics systems and improve the awareness of the importance of patient safety.

References

Hammoudi, B. M., Ismaile, S., & Abu Yahya, O. (2018). Factors associated with medication administration errors and why nurses fail to report them. Scandinavian journal of caring sciences, 32(3), 1038-1046.

Fashion Industry In China Analysis Report Essay Example For College

For over the last two decades fashion industry has grown tremendously as a result of technological advancement and the popping up of new brands (Viziteu & Curteza, 2021). At present, the fashion industry is competitive and requires a new entrant to conduct systematic analysis. Besides, the industry growth is attributed to changing consumer tastes and preferences on the usefulness and quality of fashion products (Son et al., 2017). Also, the development of the fashion industry is attributed to demography as more youths prefer modern and trendy products (Viziteu & Curteza, 2021). The cultural, political, and social factors have impacted the fashion industry positively (Viziteu & Curteza, 2021). For instance, most youths judge others based on their clothing patterns, and some prefer a specific mode of dressing to relay information (Son et al., 2017). Due to the impact of social, cultural, and political aspects on the fashion industry, there is a rise in the number of new collections and designer clothing. This report will analyze the fashion industry in China and Australia and its impact on culture, politics, society, and government regulations. The information will finally provide recommendations to businesses trying to venture into the fashion industry.

The Australian government first relaxed its regulation and policies in 1922, which facilitated international trade boosting its economy (Ki & Kim, 2016). One of the industries that have grown in Australia is the fashion industry (Tuite, 2019). The fashion industry in Australia constitutes men’s and women’s clothing markets, and as of 2008, the menswear clothing market generated revenue in a total of $3.52 billion. The industry grew by 3.9% in the 2004-2008 period (Ki & Kim, 2016). Also, women wear generated $6.7 billion in revenue within the same period and a 5.2% growth (Statista, 2021). As of 2001, the number of retailers in the Australian fashion industry was 10,600 and were majorly located in Perth, Victoria, Sydney, and Brisbane (Son et al., 2017). As of 2020, the number of retailers has increased by over 60% and is widely spread across Australia (Statista, 2021).

The major products sold in the Australian fashion industry are designer wear, industrial workwear, female outwear, children’s clothing, etc. Like any other market, the Australian markets are highly segmented based on demography, body type, income, and lifestyle (Tuite, 2019). The segmentation resulted in increased revenue generated due to consumers spending their income on products that meet their lifestyles. Moreover, the fashion industry in Australia has grown tremendously, and it’s estimated to have employed over 489,000 workers (Tuite, 2019). The most significant percentage of jobs in the fashion industry is the retail sector which employs 170,000 workers (Tuite, 2019). The employment caused by the fashion industry crosses over multiple economic sectors and positively impacts economic growth.

China is another country whose fashion industry has grown tremendously. The Chinese fashion industry is dependent on demography, mainly due to the majority of youths consuming fashion products (Ki & Kim, 2016). Over ten years ago, the Chinese fashion industry turnover was lower than the current fashion turnover. At present, China is the most promising fashion industry globally based on statistics. According to World Bank, China’s fashion industry had grown from $65 billion in 2010 to $400 billion in 2020.

Despite China’s fashion industry’s continuous expansion and growth, several political, social, legal, and economic factors affect business operations. In the case of economic factors, the Chinese government relaxed its policies and state control on the production of products (Samsioe, 2014). The economic reforms aimed to liberalize foreign investments and trade activities (Ki & Kim, 2016). The easing of state control in the economy boosted China’s economic growth. The other benefits of relaxed state control are providing social amenities and infrastructural developments. It is now easier to invest or start up a business in China due to conducive economic aspects such as better inflation rates, relaxed foreign direct investment policies, and better infrastructure.

Before starting up a business in a region, it is critical to understand the rules. The country’s government is responsible for setting up business operations regulations (Ki & Kim, 2016). The government has tried reforming its regulations to make it a preferred destination for investors in China (Samsioe, 2014). Despite relaxing the foreign direct investment regulation, their investors continue to face problems such as unclear legislation and controlling the market behavior (Ki & Kim, 2016). Also, China lacks anti-trust laws, and instead, their laws only govern and control unfair competition to only retailers and ultimately fail to solve the threats faced by producers (Tuite, 2019). Also, the trade principles in China are strong and have weak enforcement strategies. For instance, foreign investors are taxed highly compared to domestic producers, yet the regulations do not specify the taxation of different categories (Samsioe, 2014). Lastly, it’s costly and procedural to conduct the legal business process in China.

Moreover, the political stability in a country plays a significant role in investment in a foreign county. In the case of political instability, a business would likely incur political risk. In the case of the Chinese market, the laws and rules governing the country are made in the people’s congress, and the laws are influenced mainly by the communist party (Ki & Kim, 2016). The enacted laws by the communist party have made foreign businesses operations difficult (Samsioe, 2014). For instance, a political risk of starting up a business in China is a form of governance that comprises local government and central government (Ki & Kim, 2016). A company must seek and secure permission from these governments, and the process is often complicated.

However, for a business to thrive in China, especially in the fashion industry, it must consider the political, social, economic, and legal factors and their impacts. A business should first consider the political stability of the country and the risks associated (Samsioe, 2014). The company should understand its connection to China’s politics and adhere to the rules and regulations (Tuite, 2019). Also, the business should consider cultural differences and supply products that meet the tastes and preferences of Chinese demography (Samsioe, 2014). Besides, before venturing into the fashion market in China, the business should understand the Chinese values and their economic state (Ki & Kim, 2016). For instance, they should understand the country’s inflation rates, infrastructural developments, and economic policies.

In conclusion, the fashion industry will continue to grow and expand shortly as long as it satisfies the tastes and preferences of its consumers. This report has analyzed the Australian and China’s fashion industry and the political, social, and economic issues a business can face in performing business in China. Some of the problems faced are strict legal regulations with weak enforcement methods and political risks such as political alignment to the communist party.

References

Ki, C., & Kim, Y. K. (2016). Sustainable Luxury Fashion Consumption and the Moderating Role of Guilt. Fashion, Industry and Education14(1), 18–30. https://doi.org/10.7741/fie.2016.14.1.018

Samsioe, E. (2014). The Chinese Fashion Industry: An Ethnographic Approach. By Jianhua Zhao. Fashion Theory18(1), 107–109. https://doi.org/10.2752/175174114×13788166350902

Son, M. Y., Kim, Y. J., & Ji, H. K. (2017). Utilizing of the Chinese Fashion Market for Globalization of Korean Fashion Industry -Focused on the Competitiveness of Korean and Chinese Fashion Industry by applying the Double Diamond Model-. Journal of the Korean Society of Clothing and Textiles31(4), 507–518. https://doi.org/10.5850/jksct.2007.31.4.507

Statista. (2021) . Fashion industry employment in Australia 2021, by economic sector. https://www.statista.com/statistics/1263636/australia-fashion-industry-employment-by-economic-sector/#::text=Infinancialyear2021the,thousandworkersinthistime.

Tuite, A. (2019). What is Independent Fashion? An Australian Perspective. Fashion Practice11(1), 5–25. https://doi.org/10.1080/17569370.2019.1565368

Viziteu, D. R., & Curteza, A. (2021). 3D PRINTING TECHNOLOGY IN TEXTILE AND FASHION INDUSTRY. Fashion Industry3, 41–44. https://doi.org/10.30857/2706-5898.2020.3.2