BUSU610 Data-Driven Decision Making Project

BUSU610 Data-Driven Decision Making Project

Assignment Overview

Length: 15-20 slides + Excel file with all accompanying analyses

Due: Friday Midnight of Week 8

Value: 290 points for 29% of the total course grade

Online Delivery: Kaltura video presentation of the project

Blended Delivery: In-class presentation of the project

PLOs: PLO 1, PLO 2

CLOs: CLO 1, CLO 2, CLO 3, CLO 4, CLO 5

Background

Making data-driven decisions is a key step to achieving the Business Function/Processes and Strategic Planning MBA program learning outcomes as well as a very sought-after professional competency across all industries. The World Economic Forum lists Complex Problem Solving as the most important skill for thriving in the age of the Fourth Industrial Revolution we are going through, and Judgment and Decision Making as a top-ten skill (Gray, 2016). Using data analytics to inform your decisions and solve problems gives you many advantages, such as the ability to explore and compare alternatives, to test your own assumptions and come up with an objective solution, and to gather convincing evidence in support of your proposals. This assignment provides you the opportunity to experiment with all data analyses covered in the course, demonstrate sophisticated comprehension of each method and ultimately - to celebrate your improved decision-making through data analytics.

Summary

For this project you need to think of an opportunity or challenge your organization or department is currently facing and ask a management question to address it. You will also need to collect data that is relevant to your question ana analyze it; thus, it is important to focus on a topic you can investigate through available to you data. Examples of organizational opportunities include: increase market share, reach out to new customers, attract talent, expand product/service portfolio, serve customers more efficiently, etc. Examples of organizational challenges include: profit loss, customer loss, high turnover rate, non-attractive compensation and benefits package, etc. You can build a dataset for the assignment either by collecting/using data from your organization or by downloading an existing dataset (refer to the Resources Folder posted under week 1 for ready to use datasets and links to others).

Step-by-step Directions

1. Articulate Your Management Question (1-2 slides)
   1. Identify one management opportunity for improving your organization (or department) or one challenge it is facing. Explain why it is important to address it.
   2. State your opportunity/challenge as a management question.
2. Collect Data (1 slide)
   1. Find a dataset that is relevant to your management question. You can use data from a free dataset (refer to Week 1 Resources Folder for available data, links to free online data and tips for searching online for data). Introduce your dataset and describe it.
   2. Choose 4 variables that you are interested in and copy-paste them in a new Excel file, which you will work on for the rest of the assignment.
   3. Explain your choice of 4 variables; explicitly argue how each is related to your management question.
3. Describe Your Data (2-5 slides)
   1. Identify the type of each variable and describe how they are measured.
   2. Describe each of the 4 variables in your dataset by finding their (1) mean, (2) median, (3) mode, (4) range (5) quartiles.
   3. Explain thoroughly what the descriptive statistics tell you about each of the variables.
   4. Decide which measure(s) of central tendency represent your variables most accurately and why. These will be the measures you will use for your final argumentation.
4. Visualize Your Data (2-5 slides)
   1. Choose a method to visualize your variables (e.g. pie chart, bar chart, segmented bar chart, stacked bar chart, histogram, frequency table, boxplot, time series plot)
   2. Explain the motivation of your choice.
   3. Visually present each of your 4 variables.
5. Formulate a Hypothesis and Test It (1slide)
   1. Hypothesize a relationship between two of the variables in your dataset. Build an argument about the association you foresee and support it with a minimum of 2 academic articles.
   2. Run a hypothesis testing analysis.
   3. Describe your results and elaborate on them: Do the results confirm your prediction? If yes, what conclusion can you make? Do they reject your prediction? If yes, how can you explain the result? Your argument should be founded in both analytics - population, sample, variables, procedures, and research - what we already know about the hypothesized relationship.
   4. Draw a conclusion how the hypothesis tests informs your decision on your management question.
6. Run a Linear and Multiple Regression Analyses (2 slides)
   1. Run a linear regression analysis between two of your variables. Interpret the results.
   2. Run a multiple regression analysis using all 4 of your variables. Explain which is the dependent variable in your analysis and why. Interpret the results.
   3. Elaborate how the multiple regression improves your understanding of the data compared to your linear regression.
   4. Draw conclusions about your management question based on your regressions.
7. Build Your Argument and Propose Recommendations (1-2 slides)
   1. Build a comprehensive argument about your management question referring to the conducted analyses.
   2. Make two recommendations for further action in regards to your management question, e.g. emphasize the need for additional analysis or propose a specific action step.
8. Attach all your data analyses in an Excel file, which includes:
   1. 1 spreadsheet with the raw data of the four variables in your dataset
   2. 1 spreadsheet with all five descriptive statistics for each of the four variables
   3. 1 spreadsheet with the visualization of each of the four variables
   4. 1 spreadsheet with the hypothesis test
   5. 1 spreadsheet with the linear and multiple regression analyses

References:

Gray, A. (2016, January 19). The 10 skills you need to thrive in the Fourth Industrial Revolution. Retrieved from: https://www.weforum.org/agenda/2016/01/the-10-skills-you-need-to-thrive-in-the-fourth-industrial-revolution/

Grading Checklist

• Management Question (20 points)
  • Management opportunity/challenge is clearly identified (10 points)
  • Management opportunity/challenge is well-motivated (5 points)
  • Management question is explicitly stated (5 points):                                  

Total for Management Question:    /20

• Data Presentation (20 points)
  • 4 variables are presented (8 points, 2 for each variable)
  •  the choice for each variable as it relates to the management question is well explained (12 points, 3 for each variable)

Total for Data Presentation:    /20

• Data Description (40 points)
  • The type of each variable and the way they are measured is clearly described (10 points, 2.5 for each variable)
  • The (1) mean, (2) median, (3) mode, (4) range and (5) quartiles for each of the four variables are presented (20 points, 1 for each of the 20 measures)
  • The descriptive statistics results are well explained (10 points)
  • A decision on which measure(s) of central tendency represent the variables most accurately is well motivated (10 points)

Total for Data Description:    /50

• Data Visualization (30 points)
  • Each variable is visualized through at least one method (20 points, 5 for each variable)
  • The choice of visualization method/s is well-motivated (10 points)

Total for Data Visualization:    /30

• Hypothesis Testing (30 points)
  • A relationship between two variables is hypothesized (5 points)
  • The hypothesized relationship is supported with a minimum of 2 references to academic research (15 points)
  • The result of the analysis is comprehensively discussed and explained (10 points)
  • A conclusion is drawn on how the hypothesis test informs the decision on the management question (10 points)

Total for Hypothesis Testing:    /40

• Regression Analyses (40 points)
  • The results of the linear regression are well interpreted (10 points)
  • The results of the multiple regression are well interpreted (10 points)
  • The choice of dependent variable is well motivated (10 points)
  • A comparison of the results of the two regression analysis is made (10 points)
  • A conclusion is drawn on how the regression analyses inform the decision on the management question (10 points)

Total for Regression Analyses:    /50

• Argument & Recommendation (30 points)
  • A comprehensive argument about the management question is presented based on the conducted in the assignment analyses (20 points)
  • Two recommendations for further action in regards to the stated management question are made (20 points)

Total for Argument & Recommendation:    /40

• Excel Analyses (40 points)
  • All  descriptive statistics for each of the four variables are correct (10 points, 0.5 for each)
  • All visual presentations of each of the four variables are correct (10 points, 2.5 for each)
  • The hypothesis test is correct (10 points)
  • The linear and multiple regression analyses are correct (10 points, 5 for each)

Total for Excel Analyses:    /40

Final Grade:         /290