Title: People Analytics and Human Capital Trends
Course: Question Banks

Q: People analytics can be described as:
- the observations on the business performed by its employees. (Incorrect. Employees always have opinions, but that wouldn’t be good actionable information!)
- integrating various types of data to improve HR decisions. (Incorrect. Though, hopefully, that’s what an HR professional does with people analytics.)
- the statistics derived from general demographics as they are applicable to your business (Incorrect. People analytics aren’t just about general demographics, though they can be included.)
- insights derived from an organization’s employee data. (Correct. It’s the application of analytics to statistical data around an organization’s employees.)
A: insights derived from an organization’s employee data.

Q: Approximately how long have people analytics been in use by businesses?
- Since 1969 (Incorrect. People data wasn’t as readily available as everything was done manually.)
- Only two or so years ago—it’s still far from maturity. (Incorrect. People analytics are a little older than that!)
- We’re still trying to determine the best applications for people analytics usage. (Incorrect. People analytics are already informing business decisions.)
- Since about 2001 (Correct. Merck was noted to be the first company to use people analytics.)
A: Since about 2001

Q: Why do companies want to use people analytics in their business?
- To provide insight to HR professionals on employee turnover and hiring. (Incorrect. This is just a small example of what people analytics can do for a business.)
- To provide insight into the availability of human capital in the industry market. (Incorrect. That’s just a portion of what people analytics covers.)
- To provide actionable business data to non-HR professionals that is easily understood. (Incorrect. People analytics are for use by all business professionals.)
- To provide HR and business leaders with actionable people insights that improve business outcomes. (Correct. People affect every aspect of the business, so people analytics has many applications business wide.)
A: To provide HR and business leaders with actionable people insights that improve business outcomes.

Q: Previously, only 10–15% of large organizations were engaged in building people analytics teams and databases, but that number has:
- risen to about 84% of all large organizations. (Incorrect. About 84% of respondents to Deloitte’s human capital trends survey said that people analytics are important, but they haven’t all put it into action.)
- risen to about 20% of all large organizations. (Incorrect. That number is a little low!)
- unfortunately declined to only 8% as a result of the last recession. (Incorrect. Businesses are making more efforts to improve their people analytics.)
- risen to about 69% of all large organizations. (Correct. This is a dramatic increase and shows that people analytics are a solid method for improving business outcomes.)
A: risen to about 69% of all large organizations.

Q: Companies are greatly expanding the type, nature, and level of data to analyze. What does this behavior indicate?
- It shows that interest in expanding data is concentrated in certain industries. (Incorrect. There are certain industries more interested in people analytics than others, but this is not an indication of that behavior.)
- It shows that more companies are interested in the reasons behind employee turnover. (Incorrect. That would be just one reason why people analytics is used.)
- It shows that organizations are looking at general demographics to make smarter hiring decisions. (Incorrect. People analytics can do that, but it’s just a portion of what they can assist with.)
- It illustrates the accelerating pace of people analytics adoption. (Correct. Companies are adding more complex data (like employee engagement, sentiment, behavior, etc.) to traditional people data.)
A: It illustrates the accelerating pace of people analytics adoption.

Q: Those organizations using AI-aided tools and technologies to collect, integrate and analyze data represent:
- those organizations who don’t consider people analytics a value driver. (Incorrect. AI-aided tools would not be used by companies who don’t feel people analytics are important.)
- those organizations who are planning to use people analytics but have not started. (Incorrect. Organizations who are using AI-tools are at a more advanced stage than this.)
- those organizations who are focused on building these capabilities and creating teams to analyze them. (Incorrect. These organizations would be striving for AI-aided tools to be involved, but they’re not quite there yet.)
- the organizations that are most mature in using people analytics. (Correct. AI-aided tools and technology are top-of-the-line methods for reviewing and collecting this kind of data.)
A: the organizations that are most mature in using people analytics.

Q: Human Resource leaders are concerned about which of the following, in regard to people analytics?
- The price of putting plans into action around people analytics is too high. (Incorrect. While there may be cost involved, people analytics often save money for businesses long term.)
- There is too much data to review. (Incorrect. That’s always a problem with Big Data, but today there are many ways to technologically address that issue.)
- If only a few companies adopt people analytics, it won’t work for everyone. (Incorrect. Data benchmarking with other companies in your industry is important, but overall people analytics supports decisions within your company, too.)
- HR professionals aren’t skilled enough in data interpretation to understand its implications. (Correct. As one CHRO stated, “I’m tired of hiring HR professionals that don’t know the difference between a median and a mean.”)
A: HR professionals aren’t skilled enough in data interpretation to understand its implications.

Q: What continues to be a significant barrier in the use of people analytics?
- the cost of software to process people analytics data (Incorrect. Costs on software are not a major issue for using people analytics.)
- the amount of data that needs to be reviewed (Incorrect. Software and AI-aided systems are available to churn through large amounts of data for a business.)
- getting buy-in from non-HR business leaders (Incorrect. It’s always important to get buy-in, but this isn’t cited as a significant barrier.)
- finding or developing the right talent (Correct. Talent continues to be an issue, as HR professionals have not been traditionally trained for this kind of data analysis.)
A: finding or developing the right talent

Q: The success of a people analytics program lies not just in data interpretation, but in what other area?
- data clean-up and data scrubbing (Incorrect. Clean data is always an issue, but not a huge part of the success of a people analytics program)
- available industry information. (Incorrect. It’s always good to benchmark, but internal data is important here, too.)
- direct orders from business leaders to process HR recommendations (Incorrect. Hopefully business leaders don’t need to get involved to help other departments understand the value of people analytics.)
- the skill set of the HR business partners, analysts and staff (Correct. It’s imperative to have people who understand how to analyze and act on data.)
A: the skill set of the HR business partners, analysts and staff

Q: Which of the questions below are CHROs attempting to strategically answer for their organizations with people analytic data?
- What kind of ideas can be brainstormed to improve our organization’s culture? (Incorrect. People analytics can give you indications about how strong your culture is, but brainstorming solutions is not a feature.)
- Do we need more diverse employees in our workforce? (Incorrect. People analytics can offer data regarding workforce diversity, but how much diversity an organization needs or wants is not a question people analytics can necessarily answer.)
- Which leaders will lead their staff to more sales this year? (Incorrect. People analytics can tell you who has done well leading a sales team in the past and if they look equipped to do so this year, but they can’t predict the future.)
- How do we identify and predict our next group of successful leaders? (Correct. People analytics can assist them with that answer.)
A: How do we identify and predict our next group of successful leaders?

Q: In the example of Nielsen and employee retention, people analytics showed employee turnover was high due to lack of internal mobility. Which of the following was a positive result of their people analytics efforts?
- Data offered the solution of creating an internal mobility program. (Incorrect. Data doesn’t offer a solution—it shows an HR professional where the problem lies.)
- People analytics helped HR professionals create more jobs so employees could move into them. (Incorrect. People analytics might show that more employees are needed, but it doesn’t help create new jobs, and that didn’t happen in this case.)
- Turnover decreased by nearly 50% due to people analytics helping employees renew interest in their work. (Incorrect. It would be great if people analytics could do that, but it cannot)
- HR professionals developed an internal mobility program, and turnover decreased by almost 50%. (Correct. The data pointed out the issue and they creatively solved it.)
A: HR professionals developed an internal mobility program, and turnover decreased by almost 50%.

Q: If a company was looking to set up a new distribution center, how could it leverage people analytics to help decide on the location?
- People analytics could provide data on who will consume the company’s product in that area. (Incorrect. People analytics is more workforce oriented.)
- People analytics could provide data on companies to build and furnish the distribution center. (Incorrect. People analytics doesn’t provide that kind of information.)
- People analytics could help leaders determine the average rent and operating costs for that area. (Incorrect. People analytics is workforce oriented.)
- People analytics could provide data on the employees available to work at the distribution center in that geographic area. (Correct. People analytics can look at the age, gender, education levels, and other demographics in the area to help determine if there would be available employees in the area.)
A: People analytics could provide data on the employees available to work at the distribution center in that geographic area.

Q: What is the key distinction of people analytics when it’s compared to HR metrics?
- People analytics measures the difference between numbers. (Incorrect. Metrics measures the difference between numbers.)
- People analytics offers a solution to any business problem. (Incorrect. People analytics can probably solve many, but not all problems.)
- People analytics allows managers to have an opinion on a problem. (Incorrect. People analytics allows them to move from opinion to insight.)
- People analytics makes the connection between people drivers and business outcomes. (Correct. Data analysis inspires conclusions and creative solutions.)
A: People analytics makes the connection between people drivers and business outcomes.

Q: The twenty pieces of data that Nielsen used to determine a solution to its employee turnover issue are classified as:
- people analytics. (Incorrect. People analytics are defined as when the data/HR metrics are reviewed and interpreted.)
- people data. (Incorrect. That’s not a term we used here.)
- the difference between numbers. (Incorrect. That’s the definition of metrics.)
- HR metrics. (Correct. They are just data points.)
A: HR metrics.

Q: If we’re examining data and we know that 16% of all employees have been put on some sort of corrective action plan, what is the first problem we have with this information?
- It doesn’t tell us what the cause of the issue is. (Incorrect. This is a true statement, but what do you have to do first to solve it?)
- This doesn’t take into account industry averages. (Incorrect. The answer is even more simple than that.)
- This is too many people on a corrective action plan. (Incorrect. This might be lower than average. How would you know for sure it’s too high?)
- It’s just one data point, so we don’t know if that’s low or high. (Correct. You need comparisons to understand if a number is average or unusual.)
A: It’s just one data point, so we don’t know if that’s low or high.

Q: Business leaders want to rely on “gut feelings” when making HR decisions. Which of the following is a true statement?
- Gut feelings are an effective way to make business decisions. (Incorrect. Gut feelings are often wrong.)
- Gut feelings are only useful in specific situations. (Incorrect. Gut feelings are often wrong, no matter what the situation.)
- This reliance is a reason why leaders are open to adding people analytics into their decision-making process. (Incorrect. This is usually a deterrent.)
- This reliance is reason why implementing people analytics can be challenging (Correct. Data helps businesses make sound decisions around people, and “gut feelings” can often be wrong.)
A: This reliance is reason why implementing people analytics can be challenging

Q: In her role as an HR leader, Ayesha has delivered some spectacular business outcomes using people analytics. What challenge might she face now that this has occurred?
- Business leaders may want to rely on gut feelings. (Incorrect. That might be the case, but it’s not a related problem.)
- They think she’s just a person with some data and an opinion. (Incorrect. If she’s delivered great results, she probably has some credibility.)
- The business leaders won’t have confidence in her data. (Incorrect. If she’s delivered great results, she probably has some credibility.)
- Her business leaders may have unrealistic expectations around people analytics capabilities. (Correct. If impressive results are delivered, leaders are apt to expect more.)
A: Her business leaders may have unrealistic expectations around people analytics capabilities.

Q: Which of the following options might help an HR professional make a case for big data and people analytics?
- Showing them how little work it takes to do people analytics well. (Incorrect. That’s often not the case—people analytics, done right, can be a lot of work.)
- Showing them why people leave their jobs and why it costs money to replace them. (Incorrect. The HR professional would be better off showing them how to change that.)
- Showing them that people analytics will be interesting and insightful. (Incorrect. That might be true, but “interesting” isn’t enough to spend money and time on it.)
- Showing business leaders how data relates to revenue and profits. (Correct. Business leaders want you to show them the money!)
A: Showing business leaders how data relates to revenue and profits.

Q: Among the best practices of people analytics is understanding that it’s a process. What can take up to 75% of your project time?
- requesting leadership and legal approval for projects. (Incorrect. Hopefully that doesn’t take you so long.)
- understanding how the analysis process works. (Incorrect. But definitely brush up on that to make the process easier!)
- getting buy-in to look at a particular problem (Incorrect. If a problem is costing the company money, you’ll probably get encouragement pretty quickly.)
- honing in on the research question, developing the model, selecting the data, and so on. (Correct. That not-so-glamorous work takes a lot of your time, but needs to be done carefully)
A: honing in on the research question, developing the model, selecting the data, and so on.

Q: It’s one thing to identify a problem, but as an HR professional, Roxanne knows that a best practice in people analytics is not only to identify a problem but also:
- get legal approval regarding the issue. (Incorrect. You don’t need legal approval for the issue, just the solution.)
- receive buy-in from leaders who want to use their “gut feelings.” (Incorrect. That’s a problem, but she seems to have already gotten permission to review data.)
- learn how to interpret the data (Incorrect. She’s probably interpreting data to identify the problem.)
- generate actionable insights. (Correct. Knowing the problem is only half of it—you have to solve it to save money!)
A: generate actionable insights.

Q: In order to lead an organization into the future, HR must respond to human capital trends and execute shifts across four dimensions. They are:
- enterprise, workforce, lens, and how work gets done. (Incorrect. This is a combination of dimensions and the three “futures.”)
- mindset, focus, lens, enterprise (Incorrect. This is a combination of dimensions and “futures.”)
- traits, behaviors, personalization and measurable value (Incorrect. These are components of those four dimensions.)
- mindset, focus, lens, and enablers (Correct. These four dimensions are shifting.)
A: mindset, focus, lens, and enablers

Q: A human capital trend includes what is referred to as “lens.” What does this dimension encompass?
- It’s a shift from being center-driven to providing human-centered solutions. (Incorrect. That’s the “focus” dimension.)
- It’s a shift from integrated systems to a unified engagement platform. (Incorrect. That’s the “enablers” dimension.)
- It’s a shift from doing digital to being digital (Incorrect. That’s the “mindset” dimension.)
- It’s a shift from compliance and control to trust and empowerment. (Correct. It’s done with flexible operating models and ecosystems that foster speed, talent and innovation.)
A: It’s a shift from compliance and control to trust and empowerment.

Q: Why is it that enterprises will need to adapt in regard to human capital trends?
- People will be less interested in working. (Incorrect. They won’t necessarily be less interested in working, but they’ll work differently.)
- There will be more people competing for jobs. (Incorrect. That may or may not be true, depending on the job and the geographic area.)
- Technology will make jobs easier, and people will be laid off. (Incorrect. It’s true that the dynamic of technology may change how people work, but that’s just part of the full answer.)
- How people live and work is changing dramatically. (Correct. Enterprises must change with the demands of their human workforce.)
A: How people live and work is changing dramatically.