Discussion 1 Prior to beginning work on this discussion forum, read Chapter

Discussion 1
Prior to beginning work on this discussion forum, read Chapter 10 of your textbook and Macnish and Ana’s (2019) article, Case Study—Customer Relation Management, Smart Information Systems and Ethics (Links to an external site.).
Based on the content presented in these readings, describe the strategic importance of CRM, and discuss how the digital world has transformed CRM practices and relationships between customers and companies.
Guided Response: Respond to at least two of your classmates’ postings with substantive comments. When responding to your peers, consider the following to further the conversation: How can CRM business ethics, technological advances, and information systems be used to create greater profits for the firm? Do these profits always align with customer satisfaction? Explain why or why not.
Discussion 1 Response 1 Doctavious
Good Day Class, 
CRM (Customer Relationship Management) has become one of the leading business strategies invested to build and maintain profitable customer relationships. All forms of CRM seek to meet customer satisfaction, which firms can benefit financially and more. The reason behind implementing this program is to help firms gain the competitive advantage. Although some companies are behind the curb of implementing, they must remain cautious due to many CRM programs failing to meet expectations. The digital world has brought some success to firms looking to building customer relationships by using past purchases to predict future purchases. Some corporations utilize databases where customers’ purchases, credit, and personal information can be found. The information collected is used to created direct marketing activities. This CRM tactic in the digital world has brought success to many firms.
Resources:
Wisner, J. D., Tan, K.-C., & Leong, G. K. (2019). Principles of supply chain management: A balanced approach (5th ed.). Cengage.
Discussion 1 Response 2 Ebony Bogan
Good afternoon everyone, 
Customer relationship management (CRM) involves business strategies and technologies that help organizations improve customer satisfaction to build and retain long-term customer relationships (Wisner et al., 2019). Consumers are loyal to companies that go above and beyond to meet their needs and provide a great customer experience. CRM is important because it helps organizations understand those needs and preferences to improve and close the gaps in how they interact with customers and provide support. CRM helps companies offer a personalized customer experience based on information gathered with automated systems and data mining software (Wisner et al., 2019). Lastly, CRM tools help companies effectively use resources to market products and services to the right customers at the right time and boost sales (Wisner et al., 2019). My company is aware that farmers prepare for harvest season months in advance. We typically market reward programs for agriculture tires before harvest season that offer customers big savings. Marketing, supply planning, and manufacturing use sale history to ensure we can meet demand during the promotional period. Our customers appreciate the savings and plan their future orders accordingly.
The digital world has transformed CRM practices with software products that allow employees to access company information in real-time on and off-site. Sales representatives working for my company can access pricing and stock information on their computing devices to complete sales anywhere. The digital world provides various channels of communication which improves the relationship between companies and customers. For example, customers enjoy the convenience of using computing devices to purchase products and get support anytime through websites and mobile applications. Social media has also become another communication tool to market new products and share information about promotions. 
Reference 
Wisner, J. D., Tan, K.-C., & Leong, G. K. (2019). Principles of supply chain management: A balanced approach (5th ed.). Cengage
Discussion 1 Response 3 Chris Gram
Good evening classmates and instruction Escandón,
            Customer relationship management (CRM) is critical for organizations’ business. CRM is how organizations interact with their customers using technology and data analysis. Customer relationship management is focused on using the data it receives to create long-term customer relationships. By using data mining and predicting customers’ behaviors and customer relationship management strategies, organizations can learn what products to purchase more of and what products to sell to eliminate inventory. By understanding and utilizing the data provided, the CRM system aims to provide the best customer service experience possible. Organizations understand that consumers have many options for buying products and want to ensure they stand out from other providers. To do this, CRM systems used personalized communications to target particular consumers. By tailoring advertisements to a specific demographic and sending personalized emails to make customers feel valued, the CRM system is trying to do everything possible to retain its customers. Customers in the digital age expect to receive these ads as they browse the internet. They also can cross reference the pricing of products at the tip of their fingers. Organizations understand this, so they have to take things further by offering discount events such as Amazon Prime Day to draw in consumers. Organizations understand good customer experience is more critical now than ever, so many have invested heavily in CRM.  
Discussion 2
Prior to beginning work on this discussion forum, read Chapter 9 of your textbook, the Villena and Gioia’s article (2020), A More Sustainable Supply Chain: Companies Tend to Focus on their Top-Tier Suppliers, But the Real Risks Come Lower Down (Links to an external site.). Lastly, watch the video, The Breakdown of Global Supply Chain (Links to an external site.).
When making purchasing decisions, should a corporation reduce its ethical standards in order to allow the company to compete internationally? Take a position and defend your answer.
Guided Response: Respond to at least two of your classmates’ postings with substantive comments. When responding to your peers, think about companies’ procuring sustainable materials and services worldwide, as well as their commitment to fair labor practices and environmental protections. Do companies benefit from these practices? Do they align with customer satisfaction? Explain why or why not.
Discussion 2 Response 1 Regina Crosson
Good morning,
In my honest opinion, corporations should not reduce their ethical standards in order to allow the company to compete internationally.  First of all, it’s unethical and companies are constantly preaching about how ethical they are and being proud that they believe in fair treatment and healthy working environments.  Dropping what you stand for to improve business, is not ethical.  Multination Supply Chain (MNS) is defined as a multinational company that operates in its home country, as well as in other countries around the world.  It is great to do business or present business in other countries, this allows more resources, and could also lower costs.  The reduction of ethical standards can lead to a downfall in business profits and reputation.  While companies are wanting cost stability, mass bulk quantities, and flexibility in logistics, it should not come at the cost of unethical practices. 
When you consider big-name companies such as Nike and Adidas being affected because they chose to use suppliers that dumped toxins into rivers in China, this was a big scandal (Villena & Gioia 2020).  I am sure many people had no idea of the scandal and had no idea how much it hurt the companies.  While it was not Nike or Adidas directly, the suppliers they chose to use had a reflection on them as a company.  No matter who the suppliers are, it is the responsibility of these companies to make sure that the supplier is providing ethical standard services.  Consumers do not put blame on the supplier, the public finger-pointing blame will be on the big-name business.
Companies have to ask themselves when it is all said and done, was cutting corners worth it?  Having a successful business is not about cutting corners to make the biggest buck and faster production.  It can not only cost you money but could cost you lives. While you may seem on top at that time, can quickly come tumbling down.  The advice given across the world, “what is done in the dark, will come to light”.  It’s better to do things right and honestly, in life and in business, the reward is greater.  
 
Villena, V. H., & Gioia, D. A. (2020, November 16). A more sustainable supply chain. Harvard Business Review. Retrieved from https://hbr.org/2020/03/a-more-sustainable-supply-chainLinks to an external site.
Alonso Alfaro-Ureña, Isabela Manelici, Jose P Vasquez, The Effects of Joining Multinational Supply Chains: New Evidence from Firm-to-Firm Linkages, The Quarterly Journal of Economics, Volume 137, Issue 3, August 2022, Pages 1495–1552, https://doi.org/10.1093/qje/qjac006Links to an external site.
Discussion 2 Response 2 Heather Wyatt
Good afternoon, Class 
When making purchasing decisions, should a corporation reduce its ethical standards in order to allow the company to compete internationally?
No, I do not think any corporation should reduce its ethical standards in order to compete internationally. A company must follow legal and ethical rules in order to be successful. Not only for obvious reasons such as to maintain morals and good standing however when you reduce your ethical standards you are also reducing your marketability, your trust, and your quality. Ethical companies are more profitable and create better brands and have a much higher likely hood of buy-in from shareholders. “To encourage ethical sourcing, executives must cultivate a supportive organizational culture, create rules outlining the firm’s commitment to ethical sourcing, convey these principles to supply chain trading partners and devise tactics outlining how ethical sourcing will be executed” (Wisner, 2019). 
Resources 
Wisner, J. D., Tan, K.-C., & Leong, G. K. (2019). Principles of supply chain management: A balanced approach (5th ed.). Cengage
Discussion 2 Response 3 Zshmara Harrison
Hello class,
We are almost at the end!
I do not think it’s a problem when a business changes its fundamental ethical standards to expand and increase income worldwide. Depending on where we are talking about ethical norms, they can have varied connotations. Moral clarity frequently becomes unclear when people leave home and cross foreign borders. Uncertainty is elusive without a foundation of accepted beliefs, well-established laws, and established judicial systems that establish ethical behavior standards (Burja, 2019). Therefore, if they merely follow the rules and customs of that foreign country, it would not technically be regarded as reducing ethical standards. According to Wisner et al. (2022), corporate ethics strengthen the law by defining appropriate behavior outside the reach of the state. Businesses develop business ethics to promote integrity among their employees and win over key stakeholders like clients and investors. Although they are commonplace, corporate ethics programs are not of the same caliber.
The supply chain location of a facility has a long-term effect, so it must be a vital component of the company’s supply chain strategy. Companies can locate everywhere in the world, contrary to earlier belief, because of greater globalization and technological infrastructure investments, faster transportation, better communications, and open markets (Wisner et al., 2022). Please look at the earnings and benefits firms have already reaped from outsourcing, which has significantly helped them. A slothful executive would seize the chance to shift manufacturing as soon as they realized the actual cost savings, believing that doing so would instantly boost the company’s profitability (Wisner et al., 2022). Moving globally to cut costs is crucial, but it is still doable. In the long run, it will be a wise investment to put effort and strategies into place to achieve this change successfully. In the long run, moral standards changed, expenses were reduced, and profits increased.
References
Burja s. (2019) The breakdown of global supply chains. Retrievedhttps://www.youtube.com/watch?v=S0TTAcV2JiwLinks to an external site.
BUS461
Discussion Response 1 Leon Louis
Hello everybody,
This week we learned powerful techniques like regression analysis and forecasting that form the basis for many real-world decision-making processes. These statistical concepts help analyze and use data at scale. Decision Support Tools “assist decision-making in an organization.” (Alyoubi, 2015, p.278) In this post, we discuss their uses and explain outliers.
Assess the use of various decision support tools
Decision Support Tools (DST) are used in almost every industry because of their versatility. Some of their uses are listed below:
DST is used to create
Statistical models that analyze and establish relationships between variables. (Albright & Winston, 2020, p.413)
Sensitivity analysis to study the impact of changing parameters. This makes it great to conduct what-if scenarios.
Optimization analysis to find the optimum solution for a problem given all the constraints. Goal-seeking is used when working backward from a target solution. For example, say a company wants to create a market share of 35% for their product, they determine a set target and then determine input variables/values needed.
Forecasting models to project future values based on data collection and business knowledge. (Albright & Winston, 2020, p.525)
DST identifies realistic management choices. Decision Trees taught us the importance of creating an exhaustive list of decisions. (Albright & Winston, 2020, pp.242-280)
DST creates a framework for analysis considering constraints and impact without studying the entire population. Imagine the nightmare of a company trying to understand the market without decision-making tools and methods. DST considers a variety of parameters, assumptions, and data for decision-making. (Sullivan, 2002, p.2)
DST provides visual summaries like boxplots, scatter plots, etc., that aid decision-making.
Explain why outliers are sometimes called influential observations.
Outliers are data points that are unusual values in a dataset. Since outliers can “make a big difference in slope and intercept of the regression line” (Albright & Winston, 2020, p.499), they are called influential observations. This means they can dramatically change the regression model leading to a possible error in regression outputs.
Discuss what could happen to the slope of a regression of Y versus a single X when an outlier is included versus when it is not included
The slope of the equation can change drastically (increase or decrease) when an outlier is included in the analysis. (Albright & Winston, 2020, p.499) Outliers can be higher or lower than the rest of the data, and this can cause the slope of the regression line to shift, making it less accurate to predict data. To show this phenomenon, let’s consider an example of estimating the wheat crop yield (in kg) based on rainfall (in mm). The data collected has 26 observations with one outlier. (Arimie et.al, 2020, Methodology section, para.1).
In our example dependent variable, y= Wheat (in kg) and independent variable, x = Rain (in mm). (Attached file Wheat Rain-Week 4 DQ1.xlsx has detailed calculations).
The scatter plots from the attached file are pasted below:
Figure 1
Scatter plot with Outlier
Figure 2
Scatter plot without Outlier
We notice very clearly an outlier (50mm rain data point from Figure 1). This causes our slope and regression to change, resulting in a lower R sq value of 0.72. Removing the outlier gives us a higher R sq value of 0.95, resulting in higher model accuracy.
Will this necessarily happen when a point is an outlier?
Outliers don’t always have a big effect on the slope of a regression equation. When the data set is huge, a single outlier may not have a big effect. Outliers are not always easy to catch. Let’s look at a made-up example where the outlier will not affect the slope of regression slope and output. Consider two variables, x and y, with values (1,1) (5,5), (2,2), (4,4), (3,3), (2,2), (3,3) and (500,500). Clearly, the last pair is an outlier, but this doesn’t change the regression line. Regression analysis is a great technique to understand the impact of outliers when analysts must make include/exclude decisions.
More Examples:
We are estimating the average height of men in a city based on age categories. An athlete at 7 feet in this data set is an outlier and might change the regression output.
While studying the average run time per mile for female vs. male airmen in the U.S Air Force, a run time of 2 mins/mile is an outlier as other observations found were between 7.44 to 15 mins/mile. This was caused by a measuring error in the stopwatch.
 
References
Albright, S.C. & Winston, W.L. (2020). Business analytics: Data analysis and decision making (7th ed.). Boston, MA: Cengage Learning.
Alyoubi, B.A. (2015). Decision Support System and Knowledge-based Strategic Management. Procedia Computer Science, 65. Retrieved from https://doi.org/10.1016/j.procs.2015.09.079 (Links to an external site.).
Arimie, C., Biu, E. & Ijomah, M. (2020). Outlier Detection and Effects on Modeling. Open Access Library Journal, 7. Retrieved from https://www.scirp.org/journal/paperinformation.aspx?paperid=102884.
Sullivan, T. (2002). Evaluating Environmental Decision Support Tools. Retrieved from https://www.bnl.gov/isd/documents/30163.pdf.
 
Wheat Rain-Week 4 DQ1.xlsx
Discussion 1 Response 2 John Wessel
Sometimes outliers can be called influential observations since they can significantly tilt a regression line towards them. An outliner is an extreme value for at least one variable, as our textbook mentioned. “For example, if salaries in a data set are mostly in the $40,000 to $80,000 range, but one salary is $350,000, this observation is clearly an outlier with respect to salary” For discussion, we are asked, what could happen to the slope of a regression of Y versus a single X when an outlier is included versus when it is not included. Having an outliner is no big deal, “If you can argue that the outlier isn’t really a member of the relevant population, then it is appropriate and probably best to delete it. But if no such argument can be made, then it is not appropriate to delete the outlier just to make the analysis come out nicer” Most times, you will run the analysis with and without the outliner. If the data at the end comes out the same and nothing was really affected, keep the outline in. If the data at the end is significantly affected then report the results with and without the outliner, along with a verbal explanation.
Albright, S. C., & Winston, W. L. (2020). Business analytics: Data analysis and decision making (7th ed.). Cengage Learning.
 
Discussion 1 3 Lovonte
Assess the use of various decision support tools and explain why outliers are sometimes called influential observations.
Many organizations use decision support tools to assist them with the decision-making process. They are used for multiple situations due to how resourceful they are. Some ways that decision support tools are used are to gather information, organize data, create simulation models and excel sheets, and provide visual representations of data. (IFM, n.d.)
Outliers are often called influential observations because of the significant impact that they can have on the results of statistical analysis. While outliers can be identified in different forms, there is no definitive way to deal with them. The text states that the best advice is to run the analysis with the outlier and then rerun it without it, and if the key outputs do not change, then it does not matter whether the outliers are included or not (Albright & Winston, 2020).
Discuss what could happen to the slope of a regression of Y versus a single X when an outlier is included versus when it is not included.
When an outlier is included, it can radically change the slope of the analysis. If the outlier is drastically higher or lower than the rest of the data, it can tilt the regression line toward it (Albright & Winston, 2020). As stated in the previous paragraph, if the outlier is not included and does not change key outputs, it does not matter whether the outlier is included or not.
Will this necessarily happen when a point is an outlier?
It is important to note that just because the data point is an outlier, it does not necessarily mean that it will greatly influence the regression line.
 
The following are examples of regressions with and without outliers:
 
 
 
References
Albright, S.C. & Winston, W.L. (2020). Business analytics: Data analysis and decision making (7th ed.). Boston, MA: Cengage Learning.
IFM. (n.d.). Decision support tools. Retrieved August 4, 2022, from https://www.ifm.eng.cam.ac.uk/research/dstools/
Discussion 2 Response 4 Jeremy Paro
In this instance the reporter’s conclusion to this data is wrong. Correlations are often measured in their strength between -1 and +1. The closer the correlation is to +1, the stronger the variables are correlated (Albright & Winston, 2020, p 423 paragraph 3). The findings from the data in this example show that there is a 0.84 correlation between yearly wine consumption and deaths from heart disease. The conclusion for this correlation should be that there is a strong correlation between heavier consumption of wine and deaths from heart disease. The reporter has interpreted the data backward and made the wrong conclusion. If the reporter were to look at the data on a scatterplot, they may see a clearer picture of where they went wrong as the regression line would show a positive slope towards more deaths from heart disease as the amount of wine consumption is increased.
Albright, S. C., & Winston, W. L. (2020). Business analytics: Data analysis and decision making (7th ed.). Cengage Learning.
Discussion 2 Response 5 Jordan Edwards
Consider the relationship between yearly wine consumption (liters of alcohol from drinking wine, per person) and yearly deaths from heart disease (deaths per 100,000 people) in 19 developed countries. Suppose that you read a newspaper article in which the reporter states the following:
Researchers find that correlation between yearly wine consumption and yearly deaths from heart disease is 0.84. Thus, it is reasonable to conclude that increased consumption of alcohol from wine causes fewer deaths from heart disease in industrialized societies.
According to Albright & Winston, “The closer the magnitude is to 1, the stronger the linear relationship is,” (p. 423). A correlation that is close to or equal to 0 means there is little to no evidence of correlation between the two factors. Here, the correlation is 0.84 between yearly wine consumption and yearly deaths from heart disease. The reporter believes that this is proof of correlation. The issue with this assessment is that when dealing with nonlinear variables, the understanding of these correlations can be misleading. Yearly deaths from heart disease is not solely caused by wine consumption so these two variables are nonlinear. The reporter’s assessment here is flawed. 
References:
Albright, S.C. & Winston, W.L. (2020). Business analytics: Data analysis and decision making (7th ed.). Boston, MA: Cengage Learning.
Discussion 2 Response 6 John Wessel
According to our textbook, “All correlations are between -1 and +1, inclusive” (p.423). The article said that “Researchers find that correlation between yearly wine consumption and yearly deaths from heart disease is 0.84” When the findings are close to or equal to 0, it means there is little to no evidence of a correlation between the two factors. I believe that the reporter cannot determine yearly deaths from heart disease from drinking wine. There are too many factors that the reporter did not use to determine the result.
Albright, S. C., & Winston, W. L. (2020). Business analytics: Data analysis and decision making (7th ed.). Cengage Learning.