Questions:

1. What is the main problem here for technology companies?

a. Lack of ethics

b. Hostile work environments

c. Skewed employee demographics

d. Ambiguous performance evaluations

e. Poor growth

2. Which of the following is NOT a cause of workforce composition issues at technology companies?

a. Gender-based communication

b. The "information gap" for high school students

c. Patterns and norms when it comes to studying STEM subjects prior to college

d. Unconscious biases

e. Difference in abilities between males and females

3. What can be a strong reason that top universities graduate black and hispanic computer science and computer engineering students at twice the rate that leading technology companies hire them?

a. Inadequate credentials

b. Lack of skills

c. Not enough applicants

d. Lack of ability

e. Hiring manager bias

4. If technology companies attempt to implement an affirmative-action type of diversity program, in order to solve the problem, which of the following would probably NOT result?

a. New opportunities would open for applicants that otherwise would not have been considered

b. Applicants who benefits from the program may feel negatively stigmatized as unqualified or incompetent

c. Management may feel as if reverse-discrimination is occurring

d. Management would be able to effectively manage diversity

e. The program would not be supported bu people who hold racist or sexist attitudes

Problem-Solving Application CaseWhite, Male, and Asian: The Diversity Profile of Technology Companies Is setting diversity goals in hiring fair? This is an important question to explore, especially in industries dominated by a particular race, gender, or ethnic group. This activity is important because it shows how challenging managing diversity can be, especially in technology. This activity aims to examine what it means to "manage diversity" and explore which programs might actually decrease rather than increase (or at the very least balance) workplace diversity. Read the case about the typical diversity profile of technology companies. Then, using the three-step problem-solving approach, answer the questions that follow. Managing diversity is a hot topic among technology companies, some of which have started to display transparency by publishing their diversity profiles. Google's diversity report reveals its workforce is 69.1 percent male and 30.9 percent female. Ethnicity data for Google's U.S. workforce indicates 53.1 percent white, 36.3 percent Asian, 4.2 percent of two or more races, 3.6 percent Latinx, and 2.5 percent black. 1 This pattern is similar to Apple ( 32 percent female and 54 percent white, and U.S. ethnicity data showing 21 percent Asian, 13 percent Hispanic, 9 percent black, 3 percent of two or more races, and 1 percent other) 2 and Facebook ( 36 percent female, and U.S. ethnicity data of 46.6 percent white, 41.4 percent Asian, 4.9 percent Hispanic, and 3.5 percent black). 3 Executives within the technology industry have started to implement various programs and policies to change their companies' demographic profiles. For example, Pinterest established a 2018 goal to have 25 percent of new hires in engineering roles: female and 8 percent from underrepresented ethnic groups. 4 Intel established a hiring goal of full representation of underrepresented minorities and women in its U.S. workforce by 2020.5 Is setting diversity hiring goals fair? While companies that set them to note the hiring goals are not meant to be quotas, some managers may perceive them that way. This would likely create feelings of reverse discrimination, fueling resistance to hiring diverse employees. What has led to the skewed demographics at technology companies? Some experts believe the root cause goes back to elementary and high school patterns and norms, where girls are not encouraged to focus on STEM subjects (science, technology, engineering, and math). If this is true, female high-school students are not developing the proficiency that would help them major in STEM subjects in college. Further, a writer for Forbes concluded that an unconscious bias exists "that science and math are typically 'male' fields while humanities are primarily 'female' fields, and these stereotypes further inhibit girls' likelihood of cultivating an interest in math and science." 6 A related issue is the "information gap." High-school students do not know which jobs are in high demand. For example, research shows that 24 percent of high-school seniors "have no idea of what career they want to pursue. Of high school seniors who have pinpointed the desired profession, 23 percent said they made their career choice based on something they saw on TV or in a movie." 7 This is a problem because TV shows often depict technology-oriented people as geeky males. Who wants to be a geek? Others claim the tech industry has a pipeline problem. In other words, not enough females and minorities are majoring in STEM subjects in college. Statistics conflict on this subject. Some data indicate that females earn fewer than 20 percent of college degrees in computer science and engineering, even though they achieve most Bachelor's degrees in the United States. 8 In contrast, other studies suggest there is not a pipeline issue. According to EdSource writer Carolyn Jones, about half of the high-school science and math courses are female. 9 Data from the National Science Foundation indicate that women earn approximately 50 percent of science and engineering bachelor's degrees. 10AUSA Today study further showed that "top universities graduate black and Hispanic computer science and computer engineering students at twice the rate that leading technology companies hire them."11 There must be some reason these students are not being hired. If the above data are accurate, companies may have a systemic problem based on hiring managers' beliefs, stereotypes, or unconscious biases. This occurred at Pinterest, for example, when it tried to increase the number of women and minorities being hired. Although recruiters found qualified applicants "from nontraditional backgrounds, managers often continued to prioritize people from places like Stanford and MIT, which have less broad student bodies. And while Adam Ward, Pinterest's head of recruiting, and Abby Maldonado, its diversity-programs specialist, had encouraged colleagues to pass along rsums from a range of candidates, most of the referrals were still white or Asian," according to Fast Company. 12 Pinterest founder Evan Sharp believes technology companies may not be giving diversity the same type of attention they give to product development initiatives. There may also be more overt causes of the underrepresentation of female and minority tech employees. Consider results from a survey of 1,000 women who had held technology positions. These women explained why they believe females leave the tech field at a rate 45 percent higher than males. A perceived lack of career growth/trajectory was the most common factor in females' decisions to leave tech. Further, almost 50 percent of the women interviewed believed they had been paid less than their male counterparts. Other top reasons, particularly among women in tech aged 2534, were difficulties breaking into management and leadership roles, perceived bias and discrimination, and a lack of female leadership representation. 13 Could something as subtle as gender-based communication contribute to the problem? The answer is yes, according to a recent report presented in Fortune. A study of 1,100 technology resumes from 512 men, and 588 women uncovered gender-related differences that may affect a recruiter's perceptions. For example, "women's rsums are longer, but shorter on details. .... Yet when it comes to providing details about previous jobs, the men present far more specific content than the women do," according to the Fortune report. Women were also found to "lead with their credentials and include more personal background. On average, the women's rsums cite seven personal distinctions apiece, while the men's cite four." Overall, women tend to use more narrative while men are more precise about their experiences. 14 Assume you are a senior leader at a technology company. What does the information, in this case, tell you about managing diversity? Apply the 3-Step Problem-Solving Approach to OB STEP 1: Define the problem. - Look first at the Outcome box of the Organizing Framework in Figure 4.6 to help identify the important problem(s) in this case. Remember that a problem is a gap between a desired and current state. State your problem as a gap, and be sure to consider problems at all three levels. If more than one desired outcome is not being accomplished, decide which one is most important and focus on steps 2 and 3. - Cases have protagonists (key players), and problems are generally viewed from a particular protagonist's perspective. You need to identify the prospective-employee, manager, team, or the organization-from which you're defining the problem. - Use details in the case to identify the key problem. Don't assume, infer, or create problems that are not included in the case. - To refine your choice, ask yourself, Why is this a problem? Explaining why helps refine and focus your thinking. Focus on topics in the current chapter because we generally select cases that illustrate concepts in the current chapter. STEP 2: Identify causes of the problem using material from this chapter, which has been summarized in the Organizing Framework shown in Figure 4.6. Causes will appear in either the Inputs box or the Processes box. - Start by looking at Figure 4.6 to identify which person factors, if any, are most likely causes of the defined problem. For each cause, explain why this is a cause of the problem. Asking why multiple times is more likely to lead you to the root causes of the problem. For example, if you think demographics-input in the Organizing Framework-is a cause, ask yourself why. This might lead to the conclusion that there are not enough females and minorities taking STEM majors in college. In turn, this might lead to the conclusion that a poor pipeline is a root cause of demographics at technology companies. Then ask yourself why this is happening. The cause might go all the way back to elementary and high school. By following this process of asking why multiple times, you will be more likely to arrive at a complete list of causes. - Now consider the Processes box shown in Figure 4.6. Consider whether perception, attributions, psychological safety, group/team dynamics, or options to manage diversity are causes of the problem. For any concept that might be a cause, ask yourself, Why is this a cause? Again, do this for several iterations to arrive at root causes. - Follow the same process for the situation factors. - To check the causes' accuracy or appropriateness, be sure to map them onto the defined problem. STEP 3: Make recommendations for solving the problem. Consider whether you want to resolve it, solve it, or dissolve it. Which recommendation is desirable and feasible? - Given the causes identified in Step 2, what are your best recommendations? Use the content in Chapter 4 or one of the earlier chapters to propose a solution. - Potential solutions may be found in the OB in Action and Applying OB boxes within the chapter. These features provide insights into how other individuals or companies are handling the topic at hand. - Create an action plan for implementing your recommendation