4 Powerful Examples of HR Data Analytics in Action

Shefali Vasave | April 25, 2022 | 600 views

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Data Analytics Applications That Are Positively Impacting HR

Data analytics has some critical and timely applications in people management. According to SageHR, global data and business analytics revenues have grown by about 36% in just four years. The importance of HR analytics can be felt today more than ever in everything from attracting and onboarding talent to boosting employee morale.

Diversity, Equity, and Inclusion

It is possible to leverage HR data management to improve the diversity quotient of an organization. For example, companies can expand their candidate search with big data and present a clear picture of pay structures to uncover bias and create more diversity.

Training and Development

Skill gaps are a significant aspect of core HR responsibilities. Human resources analytics aims to dive deep into the organizational skill structure and draw insights that can help HR shape better learning and development initiatives.

“Now AI, blockchain, robotic process automation, and machine learning provide opportunities to leverage technology to improve efficiencies for organizations and the HR experience for individuals.”

- Scot Marcotte, Chief Technology Officer at Buck
 
In addition to these crucial areas of HR management, data analytics in HR is driving growth and transformation across the human resources landscape. Let’s look at some of the ways industry leaders are using it to impact key HR metrics.


Tackling Employee Turnover at HP

With over 300,000 employees, Hewlett-Packard (HP) could not afford to dismiss HR data analytics as part of its efforts to retain employees. A turnover rate of 20% wasn’t unheard of in the organization’s sales division. HP naturally aimed to increase the average amount of time people stayed.

Employees who leave an organization are leaving with their knowledge base, network, and even customers at times. For a company like HP, this means a loss of millions of dollars. With data scientists at the helm, the HR data analytics team took up the task of identifying employees who might be at risk of leaving. The exercise revealed several intricacies that would allow managers to build better retention strategies. For instance, if a promotion didn’t come with a significant raise, promoted employees were at a high risk of leaving. Siege reported that HP saved an impressive $300 million with data analytics in HR.


People Analytics at Every Step at Google

Google is the youngest firm in a league of industry leaders who attribute its success to having decades of history and reputation. Google owes much of its success to people analytics and data analytics in HR. The firm’s people analytics team reports directly to the VP.

With predictive analytics, Google identifies hiring problems like salespeople leaving the company if they haven’t gotten a promotion within four years. In pursuit of better retention, Google has also developed an algorithm to predict which employees will be difficult to retain. In addition, the search giant uses analytics to analyze rejected resumes, so no top-notch candidates fall through the crack. The company has used data analytics to compare the value of top performers versus average ones to enable HR leaders to make a business case for better resources to hire, retain, and develop talent.


Boosting Hiring Decisions with Facebook

“The great thing about data is that it gives you a comprehensive view of the organization. It’s just not possible to get this 360-degree look on our own for most organizations.”

- Alex Fink, VP of People Analytics and Workforce Strategy at Facebook

Social media has long been used by companies to supplement screening and background checks. But can a platform like Facebook be used to predict personalities and work performance? A study by Kluemper, Rosen & Mossholder thinks so. The hiring rate provided by participants based on Facebook profiles in this study predicted a manager-rated job performance of 8%. Although a standard personality test delivers a higher predictive value than this, studies have shown that multiple predictors like IQ tests, interviews, and personality quizzes contribute to the most accurate predictive models for future work performance. Adding a Facebook personality test might just be the edge needed to predict job performance.


Increasing Employee Retention at Nielsen

Organizations using HR data management and analytics have seen a major breakthrough in employee retention. Data analytics firm Nielsen was among the first to do that. One of its financial impact studies found that a percentage point decrease in employee attrition leads to a whopping $5 million drop in business costs. Guided by these statistics, Nielsen’s data analytics team succeeded in identifying 120 key employees at risk of leaving. By running multiple programs to arrest the retention rate, Nielsen was able to reduce employee attrition by two percentage points and save $10 million.


Conclusion: How Can Human Resources Analytics Continue to Be a Game Changer

The importance of HR analytics is undisputed. These examples clearly demonstrate the business case for using data analytics applications in HR and using them to predict performance, identify patterns, and eventually develop HR management strategies. It helps to identify negative patterns and course-correct work strategies to maximize resources.

From optimizing day-to-day HR operations to attracting top-notch talent to delivering a positive employee experience, HR data analytics is helping build agile HR processes.

Frequently Asked Questions


What are the areas of data analytics in HR?

HR data analytics include descriptive, predictive, diagnostic, and prescriptive analytics.

Who is responsible for HR data management and analytics?

As data grows in importance, the role of HR expands to include data analytics skills as an integral part of them. HR analysts typically use data to draw actionable insights.


What metrics are used to analyze HR data?

Key metrics like absenteeism rates, overtime expenses, training expenses per employee, productivity, and employee happiness are the most significant data points in HR.

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