From Concept to Reality: How to Implement People Analytics

Most People Ops leaders say adopting people analytics is a high priority, but they struggle to integrate it into everyday business operations. In a LinkedIn survey of over 7,000 HR professionals, 55% said they need “basic analytics” help.

People analytics is the collection and analysis of data about talent. Companies that implement people analytics see improved recruitment, increased productivity, and reduced turnover.

Every business has information about its employees and industry. And most organizations have human resource data, including employee pay, attrition, and performance ratings. But not all organizations use this data to guide business decisions.

Fortunately, putting people analytics into practice doesn’t have to be a massive undertaking. With the right technology, the implementation should be lightweight and the resulting system should be easy to use and accessible for everyone.

A Note on Getting Started with People Analytics

A lack of resources—financial or talent—shouldn't delay your people analytics program. Your organization doesn’t need to build proprietary tech to get started with people analytics, and your HR team doesn’t need to develop new skills or algorithms either. Even Google launched its people analytics program without any metrics or complex data models. Instead, they focused on figuring out the questions they wanted people analytics to answer.

Sarah O’Brien, LinkedIn’s global insights director, said half of the companies using analytics don’t have a dedicated analytics team. These smaller people analytics teams focus on two areas. First, HR asks relevant business questions. Second, they find easy-to-use tools to analyze the data.

Here’s a look at what it takes to bring this concept to reality for your organization -- and how to do so easily.

Step 1: Identify the business questions you want analytics to answer

Determining the questions you want to answer with people analytics will help you choose the best people metrics to track and analyze. Here are examples of metrics that can have a direct impact on business performance:

• Diversity, equity, and inclusion metrics: According to Boston Consulting Group, companies that prioritize DEI outperform their peers. Crunchbase’s anti-racism plan offers examples of metrics companies can use to monitor DEI. One example is a minimum number of phone screens with candidates from underrepresented groups.
• Pay equity metrics: Pay equity is linked to improved retention. Rajiv Ranjan, the CEO of HR tech firm Complygate, said people analytics can also ensure fair candidate offers. Pay equity metrics include average salary by gender, ethnicity, department, and title.
• Employee satisfaction metrics: Satisfied employees are more likely to be your ambassadors. And turning employees into brand advocates will boost your recruitment efforts. Examples of employee satisfaction metrics are employee Net Promoter Scores, Glassdoor ratings, and employee engagement levels.

It’s also important to validate the metrics you plan to track and analyze with frontline managers. In its special issue on people analytics, the Human Resource Management journal found analytics projects were effective when HR and managers articulated how employees contributed to the company’s growth.

This type of partnership is so valuable because frontline managers supervise most of the workforce, so they know how an employee's daily tasks connect to the business’ larger vision. As a result, it pays to have check-ins with these managers to define the roles employees play in company success.

Step 2: Develop ethics for people analytics use

Once you identify the people analytics you’ll track, it’s essential to ensure the business will use that employee data responsibly. You can do so by creating transparency about the types of data you’ll collect and the reasons you’re using the information.

The Society for Human Resource Management suggests this framework for handling people data:

• Prioritize privacy: Protect employees’ personal information by controlling access to people data.
• Ensure security: Select a platform that encrypts data and employs two-factor authentication.
• Mitigate bias: Seek to reduce bias by highlighting discrimination across the employee experience.
• Consider people impact: Make sure employees know how their data will be used and that you’re using analytics to help people. Take time-tracking, for example. Employee surveillance might end up stressing your workforce, harming their well-being and productivity.

Step 3: Create and share a master dataset

A master dataset is when you merge all the data your organization uses to make decisions about the workforce into a single place. Building this foundation of high-quality data is critical to effectively implementing people analytics, according to McKinsey’s people analytics analysis.

One of the easiest ways to bring all of your data into a single place is to streamline your HR tech. For example, you can pare down the tools you use to centralize people analytics and data into a single platform or ensure all of those tools are properly integrated so that data can automatically pass between each solution.

Step 4: Identify a champion to own people analytics

A people analytics champion is an employee who will manage data sharing, liaise with peers across the company, and present data-backed recommendations. The people analytics champion is a problem solver. They turn the business challenge into a hypothesis people analytics can test. They should also help the business act on its data.

Depending on your business size, the head of People Ops or a member of your HR team might be the best pick for your people analytics champion.

To motivate the company to drive action with the data, the champion must:

• Share copies of reports with relevant leaders and teams in easy to understand formats (visualizing the information can often help with this).
• Explain which data is available and how often it updates—some platforms will automatically update data daily.
• Add relevant context to the data, such as industry averages.
• Walk leaders and managers through how they can turn the reports into action.

The people analytics champion should also work closely with stakeholders to regularly identify new analytics questions and priorities. For example, Ciara Trinidad, then head of diversity and inclusion at Lever, set up monthly check-ins with management. Trinidad and the managers viewed data updates and discussed ongoing DEI progress during the sessions.

“By showing people managers their diversity dashboards they feel like they are a part of something,” Trinidad said. “And then they’re able to ask really specific questions to start solving problems.”

Step 5: Make your people analytics champion a data storyteller

In an episode of Digital HR Leaders, David Green, an executive consultant on people analytics, said HR professionals should become translators of people data. As a data translator, the people analytics champion can tell their colleagues the story behind the data and why it matters to the business.

Meanwhile, the Human Capital Analytics Group said HR must share the story beyond the “values.” Scientific evidence shows a compelling story triggers chemical reactions in the brain. In this way, stories help you build trust and promote understanding.

To achieve this goal, LifeLabs Learning recommends using the ABT framework. The ABT framework is a simple formula to improve storytelling skills using And, But, and Therefore.

“In the framework, the word ‘And’ helps set the context for the story; ‘But’ bridges words that are in contradiction — the pattern interrupt that grabs the audience's attention; finally, 'therefore' connects words of consequence — a problem that has been addressed.” An example might be:

Our engineering team is 20% female, AND our research shows that’s in line with industry benchmarks. BUT, female team members are more junior and less satisfied than male employees. THEREFORE, we need to put a program in place to support and engage women in engineering.

Step 6: Determine your people analytics maturity

Finally, assess your people analytics maturity to establish a baseline against which you can measure future progress.

Start by determining how you currently use the people data your business collects to make decisions. For example, perhaps your data informs hiring plans, compensation reviews, or training initiatives.

HR industry leaders have developed several frameworks to help rate people analytics maturity. Sambit Das, data scientist and HR consultant, proposes a list of questions to measure people analytics maturity:

• Does HR create and share people data with managers and executives? Examples of data include headcount, terminations, and paid time off.
• Can HR analyze metrics like attrition and pay for different groups of employees based on performance?
• Does HR perform benchmarking for job levels and salaries?
• Does HR collect employee information in a database?

The Josh Bersin Academy also published a maturity analytics guide for HR professionals. You can use this model to establish a baseline of your current people analytics capability:

• Level 1: HR does reactive reporting for operational and compliance requirements. Businesses focus on ensuring access to data and analytics tools.
• Level 2: HR engages in proactive reporting to inform decision-making. Companies at this stage use data to identify trends and detect issues with culture or performance management.
• Level 3: HR uses data to improve productivity. At this level, HR can apply analytics to make recommendations for changes in the org structure. If a manager has too many reports, for example, the data may show a bottleneck because the manager struggles to approve employee projects.
• Level 4: Organizations use data to develop scenarios about workforce planning.

Solve business problems with people analytics

Implementing people analytics to solve business challenges should not be daunting. In fact, with the right approach, it’s very achievable for any organization. It starts with breaking the process down into simple steps. Along the way, it’s important to view people analytics as an ongoing process; you may need to revisit the analyses you run or metrics you track over time as your business and your people evolve.

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