Making HR Analytics Matter to the Business
Just as analytics are transforming other organizational segments such as marketing and finance, they also hold great potential for human resources (HR). HR analytics (also known as talent analytics or people analytics) are defined broadly as the application of sophisticated data mining and business intelligence (BI) techniques to the HR discipline. There are varied ways where analytics can provide business value—from recruiting and hiring better workers, to analyzing employee retention and training programs, to getting higher worker performance.
The good news for many organizations is the plethora of data that is available. The bad news? The amount of data, and many are drowning in it. The result is that the majority of businesses admit they are overwhelmed with HR data and don’t know where to start when it comes to using it.
This definitive guide to HR Analytics spotlights an 8-step checklist to realizing full value from HR metrics/analytics, detailed descriptions of over 64 HR Metrics in 7 categories, and the comparison of old school HR metrics vs new school HR/predictive analytics.
Evaluating the Importance of HR Analytics
According to a joint study by MIT and IBM1, HR analytics are a key indicator of whether a company is a leader in their space, delivering higher revenue growth and larger profit margins. Specifically, for companies using HR analytics, they see…
- 8 percent higher sales growth
- 24 percent higher net operating income
- 58 percent higher sales per employee
Executive leaders recognize the important of HR analytics to their bottom lines. According to a report by PwC, over three-quarters of companies rate HR analytics as an important priority2. But 40 percent say they are limited to basic HR reporting, and less than 20 percent are able to apply predictive analytics3. PwC explains that part of the problem is that nearly half don’t have the HR technology in place to produce HR analytics; 69 percent of those note that the major obstacle is that data is stored in different computer and paper files4.
So, what are some of the factors holding organizations back from realizing the benefits of HR analytics?The number one problem is that HR organizations don’t have a return on investment of what they want to get from an HR analytics standpoint,says Scott Pollak, a People Analytics Partner at PwC
One is the fact that HR teams often aren’t very analytical in their thinking. As they say in Missouri, ‘show me!’ Because HR leaders fail to put together a true ROI, their business case for HR analytics unravels very quickly. I also think organizations are limiting ROI in terms of the potential of where people analytics should be going. They should be focused on things such as driving better business outcomes through talent and through a better application of talent and how to increase revenue using talent.”
Another issue is related to the sheer amount of data that can be used within an HR analytics model. This makes a lot of sense. Voucher Cloud shows that over 2.5 quintillion bytes of data are created every day5, which EMC says equates to a doubling of the world’s data every two years6. In addition to this rapid growth, 90 percent of this data is unstructured, which makes it more difficult for organizations to organize and use it for HR analytics.
Gerry Crispin, the principal and co-founder of CareerXroads, explains that this has been one of the key factors holding back HR analytics: “We are only beginning to see data being used, even though it’s been there for a long time, simply because the quality of the collected data is so poor. Over the past few years, we’ve seen significant advances in getting the data right, making sure we’re collecting what we need to gather, where it is stored, and how to pull and access it.”
But it is more than finding the right data. It is also tracking the right data. “My gut instinct tells me that we have about 20 percent of the data that we really need,” says PwC’s Pollak. “For example, we don’t really know how everyone spends their 8 to 10 hours a day at work and what changes they can make to that allocation to be more impactful. We don’t know how many decisions leaders or managers make every day, and how to help them to be better at making those decisions. We don’t know the impact of locations on results, and how to harness all of the potential data we have about where people are at physically. Organizations need to determine what information is important and put the systems in place to capture, track, and store it.”
Listing Out HR Metrics
Before an organization can align its HR analytics with business metrics, it must first map out the breadth of the HR metrics landscape. There are countless ways in which organizations can track HR analytics. Over 46 metrics are broken into seven separate categories in the below overview.
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Cost & Revenue Revenue Per FTE. Average revenue per employee is broken out across departments, regions function, and skill set. Per the Society for Human Resource Management, revenue per full-time equivalent (FTE) this past year was $335,594 in the United States8. Profit Per FTE. Average profit per employee is broken out across departments, regions, and skill sets. According to Forbes, the average profit per FTE is around $57,815 (before taxes)9. Cost of FTE Per Revenue. Aggregate cost of compensation, benefits, and other worker-related expenses. Average Salary versus Market Rates. Knowing what competitors and other companies are paying for specific job functions and levels enables organizations to pay market rates—for both FTE and contingent workers. Cost of Benefits as Percentage of Salary. How much a company is paying for benefits relative to salary. Cost of Benefits as a Percentage of Revenue. The cost of benefits relative to a percentage of revenue. Recruitment & Hiring Time to Source. Average time required to find and source candidates for job openings. Time to Hire. Average time to hire a candidate for job openings. Glassdoor reports that the average time to hire is now 52 days – an all-time high10. Cost to Hire. Total cost required to fill a job opening with a candidate. Bersin by Deloitte indicates the average amount spent by companies is $4,00011. Recruiting Efficiencies. Amount of time HR recruiting spends on specified work function. Hiring Fill Rate How many positions are filled after a specified time frame (e.g., six months). Candidates Submitted to Hiring Managers. Number of qualified candidates submitted to hiring managers for interview and consideration. Candidate Satisfaction. Satisfaction rate of candidates—those hired and not hired—with the recruiting process. Hiring Manager Satisfaction. Satisfaction rate of hiring managers with the recruitment process—at the level of individual job openings and hires as well as in general. New Hire Satisfaction. Satisfaction rate of new hires with the recruitment to offer and onboarding processes. Offer Acceptance/Close Rate. Percent of offers that are accepted and the close rate for new hires. First-Year Turnover Rate. Turnover rate for new hires within first year of employment. Manager Satisfaction Rates with New Hires. Management satisfaction with new hires (normally expressed via surveys). Performance of New Hires. Performance of new hires measured in terms of quantifiable and qualitative metrics and evaluation surveys. Retention & Turnover Turnover Rates. Turnover rates in aggregate and per department, region, and FTE demographics. Resignation Rates. Resignation rates in aggregate and per department, region, and FTE demographics. Employees Eligible for Retirement. How many FTEs are eligible for retirement in the next year, two years, five years, etc. Voluntary Turnover Rates. Number and/or percent of FTEs that voluntarily leave. These also can be broken into categories of reason, geography, function, skill set, and demographic. Involuntary Turnover Rates. Number and/or percent of FTEs that are involuntarily dismissed. These also can be broken into categories of reason, geography, function, skill set, and demographic. Average Retention Period. Average amount of time an FTE stays with a company. Further insights can be achieved via looking at geography, function, skill set, and demographic. Settlement Costs and Penalties. Cost of fines and legal settlements related to HR issues broken across job functions, skill sets, geography, division, etc. Compliance & Policies Risk Mitigation. Potential HR and compliancy risks that are mitigated as a result of HR analytics (e.g., ability to track diversity and other demographics data). Diversity. Percent of workforce by various dimensions of diversity (e.g., gender, race/ethnicity, international). Diversity is top of mind for many organizations that seek to ensure compliance with regulations when it comes to demographic mandates. They also believe diversity promotes better performance. Workforce Demographics: Age. Organizations must comply with age-discrimination laws when it comes to their existing workforce, layoffs, and other age-related issues. Workforce Demographics: Gender. Organizations must ensure they are compliant with gender-related regulations as well as should aspire to foster workplaces that promote women into executive-level positions. Today, only four in 10 businesses have no women in senior management positions12. Workforce Demographics: Race. Organizations must ensure they comply with racial-discrimination laws when it comes to their existing workforce, layoffs, and other racial issues. Workforce Demographics: Disabilities. Organizations must also comply with disability laws and ensure they are compliant when it comes to their existing workforce, layoffs, and other workforce-related issues. Only 17.5 percent of people with a disability are employed today13. Workforce Demographics: Sexual Orientation. Many organizations are developing LGBT diversity policies that augment existing laws. HR analytics can help ensure compliance with these policies and laws. FTE Salary Per Level. Average salary broken down per function, skill set, experience, and level. FTE Productivity. Productivity of FTEs per region, department, function, level, length of tenure, and other factors. Equal Opportunities. Analysis and tracking of equal opportunities for FTEs. FTE Complaints. Number and/or percentage of FTE HR-related complaints per region, department, and function. Learning & Development Effectiveness of Training Programs. Percent of employees who say they are satisfied with learning and development programs. Percent of FTEs with Development Plans. Number and/or percent of FTEs with development plans. Readiness for Job. Readiness of FTEs to step into new roles (percentage of workforce). Training Cost Per FTE. Average cost spent on learning and development programs per FTE. Training Programs Per FTE. Learning and development opportunities per FTE at regional, departmental, function, and skill set. Financial Impact Tied to FTE Training and Development. Ability to show business outcomes associated with learning and development programs such as new revenue, improved margins, and increased efficiencies. Performance & Engagement Employee Performance. Employee performance is measured in different ways (e.g., scale of 1 – 5) and with varying levels of granularity across regions, departments, functions, and skill sets. Employee Engagement. Studies by Gallup indicate that fewer than one-third of workers are engaged14. Being engaged is defined in terms of surveys on satisfaction, willingness to advocate, work engagement, etc. Glassdoor research shows organizations with engaged employees achieve a 26 percent greater increase in annual company revenue15. Average Days Absent. Number of days employees are absent broken out across departments, regions, and functions. Problem FTE Rate. Percent and/or number of employees who failed performance reviews. Rehabilitation Rate for Problem FTEs. Percent of employees placed on “performance plans” who are “rehabilitated” and retained. FTE Satisfaction Rate. For companies using NPS, then FTE satisfaction is likely based on NPS survey results. But other survey models are used as well. Satisfaction needs to be measured at the levels of region, department, function, etc. Compensation Satisfaction. Compensation satisfaction can be overlaid with other data such as FTE Satisfaction, Job Empowerment, Retention, etc. Opportunities for Advancement. This can be viewed from the perspective of employees and that of the company. This data can be overlaid with various other data sets to produce even further insights. Work-Life Balance. An in-depth study by George Sheppard at Walden University found that improvements in work-life balance translates into improved employee performance16. FTE Commitment Index. This index is based on a series of questions posed to employees that result in an aggregate score. FTE Advocacy. Employee advocacy is becoming a critical initiative for a growing number of companies. For example, Gartner reports that 36 percent of marketing departments have employee advocacy programs in place17. The willingness of employees to serve as brand advocates—via distributing content and information on social networks, candidate referrals, etc.—can be measured via NPS and other survey programs. Management Effectiveness. This is typically measured in terms of employee satisfaction with direct managers as well as management hierarchy. Clarify of Company Vision Per FTEs. Often recognized as critical to employee engagement and an indicator of financial performance, the ability of employees to articulate a company’s vision and objections is seek as an important HR measurement. HR as a Service Average Response Time to Tickets. HR teams frequently establish service level agreements (SLAs) for their online support systems. Part of this process includes establishing response times SLAs and measuring the average time taken to respond to an employee ticket. Average Resolution Time (for Tickets). Similar to average response time to submitted employee tickets, average resolution time of employee tickets is another measurement from which HR organizations employ. HR Complaints by Category. Due to legal implications and compliancy, HR organizations must track employee complaints per category, region, department, and even function. HR analytics provide valuable insights that can be used to proactively mitigate risks. Average Complaint Resolution Time. HR organizations often measure the time required to resolve each HR complaint. HR Department Satisfaction Rate. Employee satisfaction with the HR department—measured in general as well as at the granularity of specific interactions. Growth in Internal Hires. In addition to reducing recruiting costs and delivering better performance, internal hires provides deeper insights around various recruiting, employment performance and engagement, etc. analytics.
Listing Out Business Outcome Metrics
Business outcomes boil down to three things – revenue, costs, and risk. Examples include:
- Customer acquisition rates
- Customer retention rates
- Up-sell and cross-sell revenue
- Revenue growth
- Cost reduction/efficiencies
- Risk mitigation
- Culture change
Activating the Value of HR Data with Data Analytics and BI
Use cases on how to employ big data and BI to turn HR analytics into actionable insights are varied. Yet, only a small percentage of companies are successfully analyzing and turning their data into actionable insights. In a recent survey published as part of its “2017 Global Human Capital Trends Report,” Deloitte finds that only eight percent of HR organizations have usable data and that only nine percent have a good understanding of the talent factors that drive performance18.
Those companies successfully using HR analytics are doing so in various areas. Recruiting is at the top of the list, though employee performance and engagement, retention and turnover, and compensation follow close behind. When the data is synthesized and then analyzed, HR organizations can turn latent data into actionable insights. The potential business impact is substantial. Let’s take a look at three different examples:
Turnover and Patient Service
Alliance HealthCare Services, which provides outsourced medical services through more than 2,400 healthcare professionals via partnerships with over 1,000 hospitals and healthcare providers across the U.S., takes patient care seriously. However, patient satisfaction and bottom-line results were being impacted by subpar retention rates for new hires, and Alliance HealthCare Services sought a way to pinpoint the root cause of the problem19.
Initially, Alliance HealthCare Services gathered and managed staff turnover data from multiple HR systems on spreadsheets. Not only did this incur a huge expenditure in time and resources, but it also proved difficult for decision making. For example, while Alliance HealthCare Services could see that turnover was higher for new hires, it couldn’t drill down to the level of job titles and locations and to pinpoint root cause.
Using multidimensional data analysis, Alliance HealthCare Services is able to drill down and focus on specific groups and the root causes of issues. For instance, isolating high turnover for clinical staff led to an overhaul of the onboarding program for that group. The changes Alliance HealthCare Services implemented as a result of the business insights enabled the company to reduce new hire turnover for targeted groups by 49 percent.
Security Incidents and Targeted Awareness Training
Global energy company Shell wanted to reduce its risk exposure by pinpointing which employees, based on different characteristics, are more susceptible to a cyber incident20. The intent was to create targeted cybersecurity awareness training for those employees. Using HR analytics and a deep-learning algorithm, Shell uncovered three main findings. First, phishing incidents for new hires drop each year over the first five years of tenure before increasing. Second, the tendency to download malware increases over the first five years of tenure before dropping off. Third, Shell also found a correlation with skills and assignment and the potential of a cybersecurity incident.
Shell subsequently implemented a customized cybersecurity awareness training program for those employees deemed higher cybersecurity risk behavior—comprising 47 percent of all employees. But with targeted security awareness training, which saved time and resources, Shell reduced the number of employees exhibiting high-risk cyber behavior to 16 percent of its employee population.
Diversity and the Language in Job Postings
Diversity is an important priority for many companies today. Two-thirds of executives agree21. Various issues are driving this focus such as the current political and social environment, brand awareness and how it ties back to financial measurements, and a millennial workforce comprised of diverse demographics and expectations for equal treatment. Teams that are diverse and inclusive deliver up to 30 percent higher revenue per employee and greater profitability22.
Online travel company, Expedia, places a high premium on diversity and relies on data analytics to ensure that its recruitment is gender inclusive. For example, analyzing the language used in its job postings, Expedia discovered use of gendered phrases is an important predictor of the gender of a hire. Specifically, when it uses it more masculine phrases and wording such as “manage” and “forces,” it gets more male applicants and thus there is a higher rate of male hires. The same is true when feminine words and phrases like “sympathetic” and “care” are used; more females apply and there is a higher rate of women hires23.
HR Analytics Transformed
Analysis confined to structured HR-only data Taps structured and unstructured data, internal and external data sets, cross-silo business data Tracked and reported for HR department Tied to business metrics and reported to business and executive leaders HR analytics team lives in HR department HR analytics team reports to CHRO and operates across organizational silos; multidisciplinary team HR analytics team has a strong understanding of HR data HR analytics team possesses a broad understanding of financial, customer, partner, marketing, HR, and other business-related data HR analytics focus on employee retention and turnover, compensation, and recruiting metrics HR analytics focus on business metrics such as revenue, margins, efficiencies, and risk management Focused on FTEs Focused on FTEs and contingent workers End objective: analysis and trends End objective: consultative recommendations that target business outcomes
TABLE 1: HR Analytics Transformed
Glossary of Terms
HR Big Data: Growing volume of employee, customer, and transactional data, which after synthesized, generate actionable business insights.
Business Metrics: Quantified measurement used to track and assess specific business processes or programs.
Descriptive Analytics: Mines past data and analyzes it for insights on how to address future initiatives.
HR Analytics: Also known as talent or people analytics, HR analytics is the application of sophisticated data mining and BI techniques to the HR discipline.
Prescriptive Analytics: Employs analytical techniques such as graph analysis, simulation, machine learning, etc. to anticipate what and when something will happen but also why it will happen.
Predictive Analytics: Examines data to determine what is most likely to happen.
1Steve LaValle, et al., “Analytics: The New Path to Value,” MIT Sloan Management Review, October 24, 2010.
2“10 Minutes on People Analytics,” PwC, March 2016.
3“Unlock the People Equation: Using Workforce Analytics to Drive Business Results,” IBM Report, 2013.
5“Every Day Big Data Statistics—2.5 Quintillion Bytes of Data Created Daily,” VCloudNews.com, April 5, 2015.
6“The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things,” EMC Digital Universe with Research & Analysis by IDC, April 2014.
7Dave Weisbeck, “Why Connecting Workforce Outcomes to Business Outcomes Matters,” Visier, March 17, 2016.
8“2016 Human Capital Benchmarking Report,” Society for Human Resource Management, November 2016.
11“Talent Acquisition Factbook 2015: Benchmarks and Trends in Spending, Staffing, and Key Recruiting Metrics,” Bersin by Deloitte, April 2015.
12Dina Medland, “Today’s Gender Reality in Statistics, Or Making Leadership Attractive to Women,” Forbes, March 7, 2016.
13“17.5 Percent of People with a Disability Employed in 2015,” United States Department of Labor, Bureau of Labor Statistics, June 24, 2016.
14“State of the American Workplace,” Gallup, January 2017.
15“50 HR and Recruiting Statistics for 2016.”
16George Sheppard, “Work-Life Balance Programs to Improve Employee Performance,” Walden Dissertations and Doctoral Studies, January 2016.
17Jay Wilson and Anna Maria Virzi, “Digital Channel Survey 2016: Social Marketers Expand Tactics for Results,” Gartner, September 7, 2016.
18“2017 Deloitte Global Human Capital Trends: Rewriting the Rules for the Digital Age,” Deloitte University Press, January 2017.
19“Alliance HealthCare Services: Making Employees a Competitive Advantage,” Visier, 2016.
20Vasilis Giagkoulas and Ben Hawkes, “People Characteristics: A Predictor of Cyber Security Incidents?” SlideShare, October 26, 2016.
23Allie Hall, “How Hiring Language Reinforces ‘Pink-Collar’ Jobs,” Textio, January 12, 2017.
24Rishi Agarwal, “Building Quick and Effective HR Dashboards That Matter,” PwC People Analytics, 2015.