25 Aug What was the position of Maybank in 2008? What were its challenges and objectives at the time?
Requirements: 10 page
Activity 2:
AI is a topic that is bandied about more often today than ever before, yet it is often completely misunderstood. While robots and systems that act without regular human inputs do indeed exist, many newer tools are based on more rudimentary elements of AI, not self-aware, intelligent machines that learn from every interaction. The term ‘artificial intelligence is an overarching category with several more targeted terms falling under that heading, including:
Machine Learning
Natural Language Processing
Deep Learning
Neural Networks
Each of these individual technologies is powerful, but when combined, they create opportunities to eliminate wasted time, improve productivity and drive better results. Critically discuss these components and how they relate to AI, examine their distinctiveness from each other, evaluate their common uses and business applications, and their future in the business world.
Requirements:
There is no minimum or maximum required number of pages. Your analysis will be considered complete if it addresses the components outlined above.
Use of proper APA formatting and citations. If supporting evidence from outside resources is used, those must be properly cited. A minimum of 5 sources (excluding the course materials) from scholarly articles or business periodicals is required.
Include your best critical thinking and analysis to arrive at your justification.
Approach the assignment from the perspective of the senior executive leadership of the company.
Activity 3: Ask for the file
Demand for systems analysts in the consulting industry is greater than ever. Graduates with a combination of business and computer knowledge—some even from liberal arts programs—are getting great offers from consulting companies. Once these people are hired, they frequently switch from one company to another as competing companies lure them away with even better offers. One consulting company, D&Y, has collected data on a sample of systems analysts with undergraduate degrees they hired several years ago. The data are in the file attached. The variables are as follows:
Starting Salary: employee’s starting salary at D&Y
On Road Pct: percentage of time employee has spent on the road with clients
State Univ: whether the employee graduated from State University (D&Y’s principal source of recruits)
CIS Degree: whether the employee majored in Computer Information Systems (CIS) or a similar computer-related area
Stayed 3 Years: whether the employee stayed at least three years with D&Y
Tenure: tenure of an employee at D&Y (months) if he or she moved before three years
D&Y is trying to learn everything it can about the retention of these valuable employees. You can help by solving the following problems and then, based on your analysis, presenting a report to D&Y.
Although starting salaries are in a fairly narrow band, D&Y wonders whether they have anything to do with retention.
Calculate a 95% confidence interval for the mean starting salary of all employees who stay at least three years with D&Y. Do the same for those who leave before three years. Then calculate a 95% confidence interval for the difference between these means.
Among all employees whose starting salary is below the median ($37,750), calculate a 95% confidence interval for the proportion who stay with D&Y for at least three years. Do the same for the employees with starting salaries above the median. Then calculate a 95% confidence interval for the difference between these proportions.
D&Y wonders whether the percentage of time on the road might influence who stays and who leaves. Repeat the previous problem, but now do the analysis in terms of percentage of time on the road rather than starting salary. (The median percentage of time on the road is 54%.)
Find a 95% confidence interval for the mean tenure (in months) of all employees who leave D&Y within three years of being hired. Why is it not possible with the given data to calculate a confidence interval for the mean tenure at D&Y among all systems analysts hired by D&Y?
State University’s students, particularly those in its nationally acclaimed CIS area, have traditionally been among the best of D&Y’s recruits. But are they relatively hard to retain? Calculate one or more relevant confidence intervals to help you make an argument one way or the other.
Discussion 5:
provide a graduate-level response to each of the following questions:
People crave personal connections when searching for a job. A quick phone call, a handwritten note, or a thoughtful text can make the difference between an outstanding talent experience and a transactional one. The problem, however, is delivering this level of personalization consistently and at scale isn’t sustainable for most talent teams. In view of this, discuss how automation and AI are making a huge difference in conversational recruiting for the proactive companies embracing it.
[Your post must be substantive and demonstrate insight gained from the course material. Postings must be in the student’s own words – do not provide quotes!]
[Your initial post should be at least 450+ words and in APA format (including Times New Roman with font size 12 and double spaced). Post the actual body of your paper in the discussion thread then attach a Word version of the paper for APA review]
Activity 5: Ask for file
From the case discussion, students will learn how human capital strategy relates to the implementation of business strategy, how alignment is achieved between the human resources function and the business to support organisational outcomes, how HR drives organisational transformation by defining the priorities and building the processes and capabilities for the change, what factors enable human resources management to play a strategic role and how organisations can prepare for emerging challenges in HR. After a critical review of the case, respond to the questions below:
1. What was the position of Maybank in 2008? What were its challenges and objectives at the time?
2. Identify the three key business strategies that were employed by Maybank to achieve its objectives. For these key business strategies identified – namely, acquisition, internationalization and organic growth – what were the human capital strategies that were applied to carry out the business strategy? Discuss in terms of the four elements of culture, structure, leadership, and talent management. In addition, for each of these areas, do you think the human capital strategy implemented was the best option? Why or why not? How could it have been improved?
3. How did Wahid initiate the organizational transformation and Nora effect the change process through human capital transformation at Maybank?
4. What were the different roles played by the HR function during the strategic organizational transformation at Maybank?
5. What were the critical factors that facilitated strategic human capital management at Maybank?
6. How can HR set the stage and prepare to address future challenges – e.g., millennials, automation, the gig economy?
Requirements:
There is no minimum or maximum required number of pages. Your analysis will be considered complete, if it addresses each of the 6 components outlined above.
Use of proper APA formatting and citations. If supporting evidence from outside resources is used those must be properly cited. A minimum of 5 sources (excluding the course materials) from scholarly articles or business periodicals is required.
Include your best critical thinking and analysis to arrive at your justification.
Approach the assignment from the perspective of the senior executive leadership of the company
Discussion 6:
provide a graduate-level response to each of the following questions:
The widely known 70–20–10 model, a staple of workplace learning theory, estimates that 10 per cent of learning at work happens from formal learning, 20 per cent from social experiences and collaboration, and a whopping 70 per cent from experiential activities and the flow of work itself. Discuss the merit this model using empirical evidence.
Activity 6: Ask for file
In this assignment, you are to critically read and evaluate a scholarly article’s strengths, weaknesses, and contributions to the study field. Learning how to critique a journal article has several benefits, including preparing you for publishing in the future and keeping you current on the literature in your field of study. The practical application is developing the ability to look at research within your organization and industry with a knowledgeable, critical eye.
Discussion 7
provide a graduate-level response to each of the following questions:
How will the demand for hard or soft skills fluctuate based on the increasing capabilities of bots, algorithms and machines? Will soft skills become the currency of the future?
Final project: Ask for file
ScaleneWorks People Solutions LLP (ScaleneWorks), is a Bangalore-based talent management company, which commenced its operations in the summer of 2010 with a vision to build an organization of great value and be among the most respected talent acquisition solution providers globally. Sanjay Shelvankar, CEO of ScaleneWorks was considering the use of an analytical approach to predict renege. Past data from Indian IT companies revealed that 30% of the candidates did not join the company after offer acceptance, which significantly increased the overall cost of recruitment. Sanjay wondered if Analytics could possibly help in identifying the key drivers that influence a candidate in either joining/not-joining a company after accepting the offer, as it would largely help clients save both cost and time. However, there was a risk involved: any error in this prediction could turn out to be a costly affair, as the client could ”wrongly” reject a potential candidate even without interviewing him/her.
The primary objective of the case is to demonstrate how logistic regression model can be used to establish a relationship between the probability of the candidate not joining a company after accepting the job offer given the candidates’ personal, education and employment details recorded before the interview. The case can also be used for teaching analytics project lifecycle. Other learning objectives include the following:
1. Demonstrate the application of logistic regression in solving classification problems.
2. Illustrate the use of dummy variables and interaction variables in model building.
3. Understand the use of sensitivity, specificity, and Youden’s Index in solving classification problems.
4. Understand the usage of Cook’s distance and standard residual.
5. Validate the model using several measures such as the Wald’s test and likelihood ratio test
After a critical review of the case, respond to the questions below:
1. What are the various activities performed in the analytics project lifecycle? What data challenges are faced while executing an analytics project?
2. Develop a logistic regression model that can be used by ScaleneWorks for predicting candidates who are unlikely to join after accepting the offer. Which are the variables having statistical significance on renege?
3. Devise a predictive algorithm to calculate the probability of acceptance of an offer and finally joining the company after offer acceptance.
4. How would you interpret sensitivity, specificity, and model accuracy? How is it determined?
5. What cut-off probability should ScaleneWorks use to classify joining and not joining the firm after accepting the offer?
6. How should we use Cook’s distance and standardized residual in logistic regression?
Requirements:
There is no minimum or maximum required number of pages. Your analysis will be considered complete, if it addresses each of the 6 components outlined above.
Use of proper APA formatting and citations. If supporting evidence from outside resources is used those must be properly cited. A minimum of 5 sources (excluding the course materials) from scholarly articles or business periodicals is required.
Include your best critical thinking and analysis to arrive at your justification.
Approach the assignment from the perspective of the senior executive leadership of the company.
Submission: Upload/attach your completed paper to this assignment by the due date.
Week 1 case study: Ask for file
In “Prediction Machines,” economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explore the advancement and growing use of artificial intelligence (AI). The key to AI is not actually intelligence but prediction. This text looks at the value of prediction and data, the importance of trade-offs, and the impact of AI in the workplace. Beneficial to business leaders, financial analysts, policy makers, and students, “Prediction Machines” offers insights, tools, and strategies on how to adapt businesses to the world’s ever-growing use of AI. Chapters 1 and 2 provide an introduction to the concept of prediction, discuss the economic cost of prediction machines, and describe how businesses can use prediction machines in their business strategy.
Five of the most common AI debates are listed blow. Apply the knowlege gained from the readings to critically examine how these questions affect society more broadly.
Will there still be jobs?
Will this generate more inequality?
Will few large companies control everything?
Will countries engage in race-to-the-bottom policy making and forfeit our privacy and security to give their domestic companies a competitive advantage?
Will the world end?
Requirements:
There is no minimum or maximum required number of pages. Your analysis will be considered complete, if it addresses each of the 5 components outlined above.
Use of proper APA formatting and citations. If supporting evidence from outside resources is used those must be properly cited. A minimum of 5 sources (excluding the course materials) from scholarly articles or business periodicals is required.
Include your best critical thinking and analysis to arrive at your justification.
Approach the assignment from the perspective of the senior executive leadership of the company.
Week 2: Ask for file.
you are required to install python following the steps in the attached. Once installed, reproduce the codes in the attached in your newly installed python and document your understanding of each line of code
Submit your understanding in a document (750 to 1000 words). Be sure to use APA style to cite your sources as necessary.
Week 3 regression: ask for file.
An asset management company must replace the manager of its two signature mutual funds, who is about to retire. Two candidates have been short-listed. The management team is divided and cannot decide which of the two candidates would make the better mutual fund manager. The retiring manager presents a linear regression model to examine the success factors of mutual fund managers. Click on the access link below to access the full case or article. After a critical review of the case, respond to the questions below.
1. a) Why do you disagree with Jack’s comments about the uselessness of the regression due to the low R-squared?
(b) Can you think of a situation in which a useless regression has a high R-squared?
(c) There are techniques to determine the validity of a regression model—in particular, whether the relationship is linear and the error terms display equal variance (homoskedasticity). Does the regression in Table 1 violate either of these two assumptions? Justify your answer
Jack is soon convinced that a low R-squared does not render his regression useless and begins bombarding you with questions. Use Table 1 in the readings to answer Questions 2 through 6.
2. (a) Estimate the excess return (RET) of the funds that Bob and Putney currently manage. Assume that Princeton’s average composite SAT score is 1355, while Ohio State’s is 1042. Between Bob and Putney, who is expected to obtain higher returns at their current funds, and by how much?
(b) Between Bob and Putney, who is expected to obtain higher returns if hired by AMBTPM, and by how much?
3. (a) Can you prove at the 5 percent significance level that if Bob had attended Princeton instead of Ohio State, then the return of his current fund would be greater?
(b) Can you prove at the 10 percent level of significance that if Bob were managing a growth fund instead of a growth and income fund, then he would achieve at least 1 percent higher average returns?
4. (a) Does the regression in Table 1 provide strong evidence for the claim that fund managers with MBAs perform worse than managers without MBAs? What is being held constant in this comparison? Discuss.
(b) It has been suggested that fund managers without MBAs get higher expected returns because they invest in riskier stocks. If this were true, what effect would including an independent variable, Beta (with higher values corresponding to higher levels of systematic risk in the fund’s portfolio), have on the coefficient of MBA in the regression of Table 1?
5. (a) What is the lowest level of significance at which you can prove that the manager’s age has a negative impact on his or her fund’s performance holding the type of the fund, the manager’s education, and years of experience at the fund constant?
(b) A survivorship bias is thought to be present in analyzing fund manager performance in which a younger manager’s survival in the industry is more closely linked to his/her performance than an older manager’s survival. In other words, if a new manager does not perform successfully, he or she is not tolerated in the industry for long, but a more experienced manager may be forgiven a year or two of poor performance. Would the presence of this survivorship bias dampen or exacerbate the effect seen in Part (a)?
6. (a) “Streamline” the regression given in Table 1, that is, eliminate all variables that are not significant at the 15 percent level. Write down the new regression equation and check whether the specification satisfies the assumptions of linearity and homoskedasticity.
(b) Compare the coefficient of AGE in the new and the old regressions. What can explain the sign (direction) of the change in this estimator? Discuss
7. (a) You receive the prospectus of a growth fund started in the current year by a Princeton alum. What is the estimated RET (excess return relative to the return of the benchmark market portfolio) for this fund?
(b) Are you confident that this fund will “beat the market”, that is, provide a return in excess of that of the benchmark market portfolio? Which standard error do we have to use in order to answer this question?
(c) Suppose that you manage to identify a large number of growth funds started recently by Princeton graduates. By investing equally in all of these funds, how likely is it that your return will exceed that of the benchmark market portfolio by more than 1.5 percent? Which standard error did you use in your answer?
8. Suppose that you gain access to a much larger sample of random observations of the same variables that you have in the current dataset. Do you expect that any of your answers to Parts (a)–(c) of Question 8 will change, and if so, how? Discuss.
9. (a) Based on the dataset, can you prove at the 5 percent level of significance that among fund managers with the same educational background and same experience with the same fund, those managing growth and income funds are, on average, older?
(b) Using the regression developed in part a, provide an 80 percent confidence interval for the average age difference between managers who graduated from the same college in the United States and have managed a growth fund for the same number of years but differ in whether or not they have an MBA. Are the (otherwise comparable) managers with MBAs younger or older, on average? Discuss (conjecture) why this is the case.
10. Based on your analysis of the case, which candidate do you support for AMBTPM’s job opening: Bob or Putney? Discuss.
Week 4/5 case study: ask for file
Case Summary: Champo Carpets is one of the largest carpet manufacturing companies based in India, with customers across the world, including some of the most reputed stores and catalog companies. Champo Carpets is based out of Bhadohi, Uttar Pradesh, which is one of the most famous clusters of carpet weaving in India. This cluster is spread over 1,000 sq. km and comprises many villages and districts in and around it. The company is a vertically integrated manufacturer and exporter of carpets and floor coverings, with more than 52 years of existence. At the beginning of 2020, the company employed 1,500 people with a capacity to produce 200,000 pieces of carpets and floor coverings per month. As part of sales and marketing, Champo Carpets shared sample designs with its potential customers, based on which the customer placed an order. The sample design selection was done in various ways and the process itself is costly and elaborate. To capture industry trends, a team of the company visited various trade shows and events and sent samples to the client as per the latest fiber and color trends. However, their sample-to-order conversion ratio was low compared to the industry average. This had cost repercussions as well as lost opportunities. The company identified the cause as inaccurate targeting of products to their customers. It subsequently implemented an enterprise resource planning (ERP) application and has been capturing data at every point of production as well as sales. They believe this accumulated data can help target their products accurately to the right clients and design an appropriate recommender system.
Learning Objectives The primary objective of the case is to illustrate how machine learning algorithms can be used to manage business-to-business (B2B) sales. The learning objectives include the following:
Click on the access link below to access the full case or article. After a critical review of the case, respond to the questions below.
For a better understanding of the issues related to the problem, knowledge of data visualization using Tableau, R, or Python programming will be useful.
1. With the help of data visualization, provide key insights using exploratory data analysis.
2. What kind of analytics and machine learning algorithms can be used by Champo Carpets to solve their problems and in general, for value creation?
3. Discuss the data strategy for building customer segmentation using clustering. What are the benefits Champo Carpets can expect from clustering?
4. Discuss clustering algorithms that can be used for segmenting Champo Carpets’ customers.
5. Discuss the data strategy that can be used for building recommender system models.
6. What will be your final recommendations to Champo Carpets?
Requirements:
There is no minimum or maximum required number of pages. Your analysis will be considered complete, if it addresses each of the 9 components and subcomponents outlined above.
Use of proper APA formatting and citations. If supporting evidence from outside resources is used those must be properly cited.
Include your best critical thinking and analysis to arrive at your justification.
Approach the assignment from the perspective of the senior executive leadership of the company.
Week 6 fishbone assignment: ask for file
Fishbone Charts/Diagrams (also known as Ishikawa diagrams, herringbone diagrams, or cause-and-effect diagrams) are causal diagrams created by Kaoru Ishikawa, a Japanese quality control expert that show the potential causes of a problem. Essentially, it is a visualization tool for categorizing the potential causes of a problem. “The value of using the fishbone diagram is to dig deeper, to go beyond the initial incident report, to better understand what in the organization’s systems and processes are causing the problem, so they can be addressed”. Source:
“It is a more structured approach than some other tools available for brainstorming causes of a problem (e.g., the Five Whys tool). The problem or effect is displayed at the head or mouth of the fish. Possible contributing causes are listed on the smaller “bones” under various cause categories. A fishbone diagram can be helpful in identifying possible causes for a problem that might not otherwise be considered by directing the team to look at the categories and think of alternative causes. Include team members who have personal knowledge of the processes and systems involved in the problem or event to be investigated”. Source:
Fishbone Diagram Procedure
Agree on the problem statement (also referred to as the effect). This is written at the mouth of the “fish.” Be as clear and specific as you can about the problem. Beware of defining the problem in terms of a solution (e.g., we need more of something).
Agree on the major categories of causes of the problem (written as branches from the main arrow). Major categories often include equipment or supply factors, environmental factors, rules/policy/procedure factors, and people/staff factors.
Brainstorm all the possible causes of the problem. Ask “Why does this happen?” As each idea is given, the facilitator writes the causal factor as a branch from the appropriate category (places it on the fishbone diagram). Causes can be written in several places if they relate to several categories.
Again asks “Why does this happen?” about each cause. Write sub-causes branching off the cause branches.
Continues to ask “Why?” and generate deeper levels of causes and continue organizing them under related causes or categories. This will help you to identify and then address root causes to prevent future problems.
Source:
For this assignment, identify a possible or actual problem in your organization. Note that having personal knowledge of the processes and systems involved in the problem to be investigated will help present a more realistic problem statement. Once you establish a problem statement, brainstorm to identify the possible causes of the problem. Using a fishbone diagram and the steps outlined above display the cause and effect of the identified problem. Finally, write a brief report on your diagram identifying the possible ramifications of the identified problem if unresolved soon.
Week 7: ask for file
a. An international manufacturer of electronic products is contemplating introducing a new type of compact disk player. After some analysis of the market, the president of the company concludes that, within 2 years, the new product will have a market share of 5%, 10%, or 15%. The subjective probabilities of these events are .15, .45, and .40, respectively. If the product captures only a 5% market share, the company will lose $28 million. A 10% market share will produce a $2 million profit, and a 15% market share will produce an $8 million profit. If the company decides not to begin production of the new compact disk player, there will be no profit or loss. Based on the expected value decision, what should the company do?
b. The owner of a clothing store must decide how many men’s shirts to order for the new season. For a particular type of shirt, she must order in quantities of 100 shirts. If she orders 100 shirts, her cost is $10 per shirt; if she orders 200 shirts, her cost is $9 per shirt; and if she orders 300 or more shirts, her cost is $8.50 per shirt. Her selling price for the shirt is $12, but any shirts that remain unsold at the end of the season are sold at her famous “half-price, end-of-season sale.” For the sake of simplicity, she is willing to assume that the demand for this type of shirt will be 100, 150, 200, or 250 shirts. Of course, she cannot sell more shirts than she stocks. She is also willing to assume that she will suffer no loss of goodwill among her customers if she understocks and the customers cannot buy all the shirts they want. Furthermore, she must place her order today for the entire season; she cannot wait to see how the demand is running for this type of shirt.
a. Construct the payoff table to help the owner decide how many shirts to order.
b. Draw the decision tree.
