Data-Driven Decision Analysis

e decisions is an essential skill that is useful in any facet of an operation. The dynamic environment offers daily challenges that require the talents of the operations manager; working in this field is exciting and rewarding.

In  Module Seven, you will submit your  selection of statistical tools and data analysis, which are critical elements III and IV of your final project. You will submit a 3- to 4-page paper that provides justification for the appropriate statistical tools needed to analyze the company’s data.

Specifically, the following  critical elements must be addressed:

III. Identify  statistical methods to collect data:

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Data-Driven Decision Analysis

 

A. Identify the appropriate  statistical methods that you will use to perform your analysis. What are your statistical assumptions concerning the data that led you to selecting the methods? In other words, why did you select this method for statistical analysis?

B. Justify why you chose these  methods to analyze the data. Be sure to include how these methods will help predict the use of the data in driving decisions using cited evidence.

IV. Data-Driven Decisions to determine the appropriate decision for the identified problem:

A. Outline the  process needed to utilize your statistical analysis to reach a decision regarding the given problem.

B. Explain how  data mining is used to develop a solution to the case. In your response, consider the concepts of metadata.

C. Explain if the problem is a  structured or unstructured problem.

D. Assess how the  variables have potential for answering the problem.

What to Submit

Data-Driven Decision Analysis

Your paper must be submitted as a 3-to 4-page Microsoft Word document with double spacing, 12-point Times New Roman font, one-inch margins, and at least six sources cited in APA format.

Part 2

A good marketing plan needs to translate into quantifiable measures. Without such quantification, a plan will often fall apart. Thus, defining objectives and respective key performance indicators (KPIs) to measure the effectiveness of the plan is essential.

Your CMO has asked you to create a strategic marketing plan and share it with other regional marketing directors, so that each park follows a similar strategy. Considering the different challenges in each park, the marketing objectives must be broad enough to address each park’s challenges, with minimum or no customization.

Defining the marketing objectives and relevant KPIs will help you, the other regional marketing directors, and the CMO to pre-assess the effectiveness of the plan you have proposed and to address gaps, if any.

Prompt

Create a PowerPoint presentation for the CMO and your fellow regional marketing directors in the course scenario. The goal of this presentation will be to share marketing objectives, associated success criteria, and methods to monitor and measure the results.

Specifically, you must address the following criteria:

1. Identify  two SMART objectives (Slides 1–2)

· Choose two of the marketing methods identified in Milestone Two and identify SMART objectives for each.

· Begin this part by restating the identified marketing strategies and then state the SMART objectives. How does each objective align with the SMART framework?

2. Identify  two KPIs—one for each marketing objective—to measure the success of the marketing strategies (Slides 3–4).

· What are your reasons for choosing each KPI?

3. Determine  two methods to monitor the results of the identified KPIs (Slides 5–6).

· Why have you chosen these methods?

4. Describe the  feedback loops to be implemented in this case (Slides 7-8).

· Identify the specific feedback loops you will monitor and how often.

· How should results be reported to the key stakeholders needing this information?

What to Submit

Submit a narrated PowerPoint presentation with 8-10 slides

Data-Driven Decision Analysis

  1. What statistical methods are appropriate for analyzing the company’s data?,

  2. Why were these statistical methods chosen?,

  3. What process is needed to utilize statistical analysis for decision-making?,

  4. How is data mining used to develop solutions, considering metadata?,

  5. Is the problem structured or unstructured, and how do variables address it?