What is People Analytics, And Why is it Important?
Cloud computing and the adoption of data analytics as a core element to an increasing number of projects and departments within organizations and businesses have seen an unstoppable rise in recent years.
It was only a matter of time before data analysis methodologies and tools began to provide insights that also shaped HR processes.
As approaches to work evolve, with new technologies and values, correctly interpreting trends, effectively addressing issues, and rapidly taking advantage of opportunities are becoming increasingly important.
People analytics tools and techniques offer ways to achieve these results while coupling the success of businesses to that of their employees.
This post explores how organizations can use people analytics to improve success. We look at metrics and examples to ground the methodology in reality.
People analytics: A definition
At its core, people analytics describes the use of talent data focusing on people and business-oriented results.
In essence, people analytics means collecting and using data about employees. For example, employee feedback, key motivators, relationship insights, and more. These insights are then used to drive growth and make evidence-based decisions for your company.
It can also be referred to as people, HR, or workforce analytics.
This broad definition can have many different approaches and priorities. Still, they all share the understanding that data on processes, roles, engagement, issues, and interactions within an organization hide important insights. These can help drive improvement, grow business success, and can be leveraged through analytics solutions.
Benefits of people analytics
Just as with all data, people analytics has countless benefits that will vary depending on your business strategy as well as your analytics strategy and company culture. Some benefits are well-recognized across the board. We like to group these as:
1. Performance benefits
- Improve Retention
- People analytics can also be useful in monitoring retention rates or spotting departments, teams, or roles deviating from the trend, enabling you to quickly address issues or apply winning approaches throughout your organization.
- Constant improvement
- Through access to big data sets and machine learning processes, you can ensure your structure is constantly being monitored, investigated, and tested, making constant improvement in real-time easier than it ever was.
- Boost Performance
- Regular feedback yields people analytics that empowers management to tailor employee experiences. It typically results in strategic planning that allows employers and employees to grow. People analytics enables organizations to predict business’s future needs
2. Process benefits
- Improve Talent Acquisition
- While many tools, such as Referrals by Roots, can help boost the quality and speed of your acquisition, you shouldn’t overlook the value data can have in improving the process.
- Identify Gaps
- Whether looking at skill gaps, opportunities not being fully leveraged, or any other detail you might be overlooking, data analytics can make gaps stand out clearly, for your organization to address.
- Improve Process Efficiency
- People analytics help you constantly improve your processes, giving the insights you need to rapidly tweak and adapt the way you work to current needs.
3. Culture benefits
- Reduce bias
- Data analysis holds insights that go way beyond process optimization and performance boosting, and can help you monitor and address aspects of your organization that relate to culture, bias, and inclusivity.
- Enhance Employee Experience
- While sales and revenue data can be straightforward to monitor even through conventional approaches, the same cannot be said for HR metrics such as belonging, inclusion, and workplace satisfaction. People analytics offer insights that can enhance employee experience and increase employee retention.
Core metrics of people analytics
Now that you are sold on the benefits of leveraging your people data let’s look at the core metrics your HR team should focus on to inform effective and evidence-based decision-making.
Perhaps not surprisingly, what metrics you might want to focus on will depend heavily on what you are trying to achieve through people analytics. Still, some things you should always keep an eye on are:
- Revenue per employee
- Absenteeism rate
- Voluntary turnover rate
- Involuntary turnover
- Onboarding time
- Training cost per employee
- Offer acceptance rate
- Time to hire
- Retention rate
- Employee engagement
- Compensation levels
- Employee life-cycle
- Employee satisfaction
Examples of people analytics
Ok, this is all very cool, but how does it apply to the real world, and what are its effects on real-life business decisions and, more importantly, business outcomes?
Here’s a list of companies that have implemented some form of data science initiatives in connection with human resources management and how things turned out for the business leaders that adopted them.
Uber approached people analytics by creating data dashboards for their people managers to address employee engagement and business outcomes.
Not only did they provide access, they asked managers for input on what HR data they would need, and then built their dashboards and visualization solutions on this input.
By doing this, they improved their employee engagement and talent decision-making considerably.
It should be no surprise that NASA strongly values data collection and data-driven decisions in its processes. They do, using data to inform their decision-making in talent management and workforce planning.
NASA is using Neo4j technology to analyze people, skills, and projects. This then forms connections and relations between data points, mapping them on graphs that help employees visualize growth, development opportunities, and career change options. These graphs also help business and HR leaders visualize and address organizational needs.
The software giant uses people analytics to provide managers with insights and information, and combines this with explanations and appropriate actions in their Manager Hub. This mix of real-time data and predictive analytics helps managers organize 1-on-1 sessions with their reports, and employee connections.
Johnson & Johnson
Sometimes our assumptions might not be correct, and building talent management strategies based on incorrect assumptions is risky.
At Johnson&Johnson the assumption was that retention rates were higher in more experienced staff. But the people analytics data highlighted the opposite, as graduate employees had the highest retention rate. Insights like these can be critical when rolling out policies or ensuring company culture and values match reality.
People analytics isn’t restricted to space agencies and tech companies, though. One good example of this is shoe manufacturer Clark’s.
They set out to see whether there was a connection between their already high employee engagement rate and business performance.
After much data analysis, not only did they confirm that there is, indeed, a relation, they were able to quantify it as a business performance increase of 0.4% for each 1% increase in employee engagement.
This German energy company needed to address absenteeism, which had risen to worrying levels. By formulating hypotheses, and validating them against their data, E.On’s people analytics team was able to figure out that a lack of time off being taken by employees was at the core of their issue. They solved their issue by educating managers and implementing a better holiday approval policy.
IBM’s case shows us how people analytics can be used to gain insights about overlooked issues and to provide solutions to well-known challenges.
In their case, IBM was looking to reduce the churn rate for some specific roles that saw an unusually short employee life-cycle.
By approaching the issue with a data-informed people analytics approach, they developed an algorithm that helped process data about employee satisfaction, salaries, promotions, recruitment, and much more.
The data-driven solutions IBM applied have had exceptional results, providing benefits for hundreds of millions of dollars, reducing churn by 25%, and increasing productivity.
Another creative approach was that of Cisco. They chose to focus their people analytics efforts outwards, using available data about office space usage and availability of graduate candidates, among other variables, to determine the best locations to open new offices.
Experian chose to apply talent analytics to a specific issue: an attrition rate that was too high for their liking.
They built a model that took into account hundreds of variables that might affect employee churn, from commute time to team organization. Processed through predictive analytics, the data highlighted some attrition causes that the organization was able to address, seeing a drop in churn rate, and savings estimated at around $10,000,000.
As we saw in all the above examples (and linked case studies), the variety and depth of insights that can come from applying data analysis to employee performance management are only limited by our imagination (and the skill of our HR professionals and data scientists).
Start improving your workplace with Roots
While many of the approaches we talked about involve ad hoc projects, dedicated teams, and analytics tools, there are steps you can take towards improving your organization through data that are easy and fast to implement.
At Roots, we build tools that help you manage your workforce and simplify your HR processes without ever having to leave the comfort of your Slack workspace.
Make sure your employees are taking enough time off and that your PTO policy is fit for purpose with PTO by Roots.
Make sure engagement levels are high with Connections, monitor progress through our Pulse Survey plugin, and make sure your employees have a place they can ask questions and express ideas or concerns with our 1-on-1 management tool!
Discover our range of Slack-based plugins at Roots!