Determine how the company′s employee demographics compare with industry peers and competitors.

To complete this project, you then needed to take what you learned to perfrom analysis on the data for the purpose of identifying at least one pattern of interest. This requires comparing subsets of the population to each other or comparing the population to other similar populations. You might compare the rate at which men and women have been hired each year. You might look at all the cyber analysts with 5 years with the company and a bachelors degree and then compare salaries of the men/women or by racial groups to see if there is any evidence of discrimination and if so…can you find at least two other examples to show that there is a pattern. You might compare this company′s information to the census data from the US Government or compare to industry statistics. You might compare the data toother tech companies such as Microsoft or Apple. Also, the basic instructions require a minimum of 2-3 paragraphs with each paragraph dedication to a single topic: Paragraph 1: Identify the pattern of interest Paragraph 2: Explain why that pattern you identified is relevant or significant Some of you are not reading the announcements and the following will hopefully keep you from failing Project 4…so I am both posting it and emailing it: As you enter the second and final week of project 4, you should have hopefully completed steps 1 – 8 and have moved into the analysis phase of the project. I cannot stress the following enough…what you did in steps 1 – 8 was NOT analysis. Steps 1 – 8 were a guided tour or walk-through of using Excel. You were shown how to create some basic formulas, perform cell references, build graphics, and use some built-in tools to generate statistical data for a population. These are some of the things you will perform daily in the cyber field to analyze data and generate information. This is the next phase of project 4. You will take what you have learned and analyze the raw data to answer specific concerns from senior leadership. Specific concerns…or questions…are the key to analysis. You analyze data for a purpose. You analyze data to answer questions. Sometimes you come up with the question on your own while at other times, the question is given to you. In this project…it’s a combination of both. Leadership has framed the question to some extent within the scenario as well as in the questions asked in the worksheet. For example, we know from question 4 that the CEO wants the company to become more diverse. From the scenario, we know the following:  Pat asks you to analyze data about the company′s workforce and to prepare an analysis of its current composition  The analysis will be used to advise the company′s management on the cost of doing business, and how to achieve success and income revenues, as well as make recommendations on the allocation of salaries across the company.  The report must consider personnel by organizational roles, salaries, length of service, level of education, age, race, gender, marital status, and region.  Determine how the company′s employee demographics compare with industry peers and competitors.  Draw relevant conclusions based on quantitative reasoning As with every project, there are certain constraints. The first constraint is space. You are tasked with writing a 3 or 4 paragraph essay. That is NOT nearly enough space to address everything above. The second is a limitation with the data. If you have taken a business course, you should realize that there is no information from which to analyze the cost of doing business, and how to achieve success or income revenues. There is no market analysis, no costing information, billable rates, demand, etc. Do not focus on this area. Third…this is a quantitative project. Your essay will focus on an analysis that looks at numbers and will include numbers. Failure to provide numbers in your essay will result in a failing grade for the entire project. I also mentioned that Steps 1 – 8 were not analysis AND that your essay is based on your analysis of the data…this means that if you base your essay entirely on the data you generated in steps 1 – 8 of the project, you will receive a failing grade. If you think that having a workforce comprised of 21% women is significant all on its own…think again. Dig deeper. Analysis requires comparing one thing to something else. You can look at subsets of a population. For example, you might compare Male Cyber Analysts with master’s degrees who have been with the company for 7 to 10 years and live in the Midwest with Female Cyber Analysts with master’s degrees who have been with the company for 7 to 10 years 2 and live in the Midwest. These are two subpopulations who, on paper and in a perfect world should be compensated equitably. The standard deviations for the salaries of these subgroups should be fairly small and nearly identical with the standard deviation for the larger group of everyone in the category of Cyber Analysts with master’s degrees who have been with the company for 7 to 10 years and live in the Midwest. There should be some deviations based on performance, but on the face of things, it should not matter if you are male/female, African American/Hispanic/Caucasian/Asian, Married/Single, or any given age. If there is a significant difference, there might be a problem. Dig deeper. The other option with analysis is to look externally from your data. Compare your company’s data with other companies. Maybe you can find public information from competitors or industry leaders. Compare your data with regional data such as the national census. Compare with data from the U.S. Bureau of Labor Statistics or similar industry reporting from U.S. News. In these instances, you would likely be comparing the entire population set for this company with the external data. It is up to you to determine your course for your analysis. You have been provided with the scope and limitations and it is up to you to take the next step with it. Please keep in mind what you learned in project 2. In project 2 you were required to provide a minimum of three historical data points to prove that there was a trend. What is a trend other than a specific type of pattern? So, carry this logic forward to Project 4 where you are tasked with “describing patterns of interest”. When you find something in the data such as a significant deviation in salary between men and women in the subpopulation mentioned above…all you have is a single data point. A single point is not a pattern. Dig deeper. Was this just an anomaly or is there a concerning pattern…a pattern of interest? You must find a minimum of three such data points for it to be considered a pattern. For the first paragraph of the essay…describe the pattern of interest. You must have at least one pattern well described. The second paragraph has a task of explaining the potential relevance of the pattern or patterns. Remember your audience. Remember the framing or scoping information provided by leadership in the scenario and questions. You are briefing this to the C-level suite so they can make major decisions for the company. They have a goal of making the company more diverse. Does your pattern “seem” to imply that the company is moving in a direction to support this goal (a positive pattern) or will the pattern damage diversity relations and slow or reverse the direction of becoming more diverse (a negative pattern)? Maybe you will uncover evidence that proves something is being done to become more diverse. You might not know what, but the proof is in the data. The final paragraph touches on real-world limitations…you will NEVER have all the information. When performing research and analysis, you will identify the information you need but cannot find or you will identify where information is close but not quite perfect. For example, we know that some of the employees live in the Midwest. But does that mean Michigan or Kansas and could that be relevant in some way to salary deviation. You see, when you find a deviation, you need to try to understand what is driving the deviation. There could be perfectly logical explanations for some deviations that have nothing to do with diversity or discrimination. Maybe the Michigan office is in Chicago and the Kansas office is in Crawford County Kansas. There is a significant difference in the cost of living in these two locations. However, you cannot answer this because the data provided lacks that additional fidelity or granularity. Look at the data you have…are there any other lacking fidelity? If you had additional fidelity, might you be able to better analyze the data with further investigations? Concerning missing data, we don’t know the color of anyone’s hair or if they have tattoos. Sure, that’s kind of silly…but is there any information that is simply missing from this data set that could be used to explain any patterns you identified? This is the purpose of the final paragraph. You have identified a pattern AND you have convinced management that the pattern is significant and that they should be concerned. Now that you have your executive sponsor engaged…what is your shopping list? What do you want from them? Tell them what you need to be able to complete your analysis. What data is missing and what data needs to be refined to be able to answer their question. Now challenge yourself and find a different pattern than salary deviations between men and women. There are a lot of good patterns in here if you look for them. Dig deeper.

Latest Assignment