Talent analytics: a beginner’s guide

Talent analytics uses data analysis to get insights about an organizational workforce. It involves collecting, processing, and interpreting various types of data to make effective data-driven choices. 

As Deloitte reported in 2021, data analysis is even more important than engineering software from scratch. Businesses now have a wide range of software to collect and monitor company data – but without a highly skilled analytics team, that data is almost useless. 

To help support talent analytics in your organization, this article will briefly introduce this complex topic. In this article, we will: 

• Define talent analytics fully; 
• Explain data collection in talent analytics; 
• Summarize three important reasons to invest in talent analytics.  

Across every business unit, leaders recognize how digital transformation data can inform every decision they must make. So, let’s see how technology’s helping out in talent management. 

What is talent analytics? 

Talent analytics is a small part of general data analytics. Data analytics systematically applies data analysis, statistical techniques, and quantitative methods to gather, interpret, and derive meaningful insights from various aspects of an organization’s workforce. Talent analysis refers specifically to applying data analytics to elements of the workforce. 

Talent analytics helps organizations to make informed decisions about talent acquisition strategies, optimal deployment of human resources, identification of high-potential employees, design of effective training programs, and the enhancement of overall workforce effectiveness. In essence, talent analytics empowers HR professionals to align their human capital strategies with broader organizational goals, fostering an environment of data-driven decision-making and promoting sustainable growth.

Perhaps you have previously heard similar terms to “talent analytics.” There are several different words that all mean the same thing. There is no real difference between HR, people, and workforce analytics. 

Maybe “talent analytics” is a strange phrase. After all, in an HR context, “talent” is a flattering word for talking about “people.” Sometimes (in particular, recruitment), “talent” means “people with exceptional skills.” But in many cases, people are “talented” if they offer something useful to the company – regardless of whether or not they are talented.

Data collection for talent analytics 

Talent analytics rests on data from many aspects of the HR function. But you need to know what to look for – and how to look for it. In this section, we will go over the methods of data collection, the types of talent data you might look for, and three key types of data to know more about. 

Unsurprisingly, HR technology is your best friend here. 

Data is easier to gather when you have a strong digital transformation program. Software like employee experience platforms, HRM software, and staff training portals make getting the data you need easier. Such platforms are also excellent for reporting the results, and, as a result, achieving Gartner’s three goals of “actionability, credibility, and accessibility” in talent analytics. 

You can look for metrics in every company area involving people. For example: 

• Recruitment and Hiring
• Employee Performance 
• Employee Engagement and employee satisfaction 
• Retention
• Learning and Development
• Succession Planning
• Diversity and Inclusion
• Compensation and Benefits
• Workforce Planning
• Employee Feedback and Performance
• Absenteeism and Time-Off
• Employee Relations

Some of the data you generate will be related to key KPIs and metrics. However, other information may simply be about the way people work. 

We’ll dive deeper into three areas: employee performance, retention data, and recruitment data. 

Employee performance 

Tracking employee performance is vital in talent analytics as it offers invaluable insights into individual contributions and overall organizational effectiveness. Organizations can identify top performers, address skill gaps, and tailor development strategies by analyzing performance metrics. 

This data-driven approach aids in making fair compensation decisions, fostering a culture of improvement, and aligning individual goals with broader company objectives. Ultimately, monitoring employee performance empowers organizations to optimize talent management efforts, enhance productivity, and drive sustainable success.

Retention data 

Retention data holds significant importance in talent analytics as it unveils essential patterns about employee engagement, satisfaction, and the overall health of an organization. Analyzing turnover rates and reasons for employee departures provides insights into potential pain points within the work environment, allowing proactive measures to improve retention and reduce talent loss. 

By understanding the factors influencing employee retention, organizations can refine their recruitment, development, and workplace satisfaction strategies, leading to enhanced employee loyalty, increased stability, and a competitive advantage in the market.

Recruitment data 

Recruitment data is a cornerstone in talent analytics because it can optimize the hiring process and enhance workforce quality. Organizations can fine-tune their recruitment strategies by analyzing sources of hire, time-to-fill positions, and candidate demographics, focusing on the most effective channels and refining their approach. 

This data-driven approach accelerates the hiring process and ensures a more diverse and skilled workforce. Moreover, insights from recruitment data enable organizations to adapt to changing market trends, attract top talent efficiently, and align their recruitment efforts with broader talent management goals, fostering long-term growth and success.

The benefits of talent analytics: Three examples from the experts  

Talent analytics helps to achieve the core goals of HR by assisting companies to understand how to keep their workforce happy and stable. As such, there is potentially a very long list of why talent analytics are important! But here, we will focus on three key examples that experts and thought leaders have examined: the role of talent analytics in crisis management, retention, and decision-making.

Crisis management 

Business leaders have learned much about crisis management in the past few years. But it’s easier to handle the unexpected when you have excellent employee data. 

The MIT professor of management, Emilio J. Castilla, gives an example of one major company that adapted very easily to the Covid lockdowns. 

With great talent analytics measures, they could easily reorganize their staff most effectively: “They did not even experience the disruptions that many other companies experienced” because they were so well prepared. We don’t know what the next crisis will be – but a talent analytics program can be one part of your preparation. 

Recruitment and retention 

It’s no surprise that talent-focused analytics helps to drive better recruitment and retention. After all, if you get these processes right, your company can save a lot of money – and line managers are keen to know what they can do to improve. 

Kon Leong, CEO of ZL Technologies, explained in a 2021 HBR article how analytics give great ways to solve many recruitment problems.

He shows that analyzing data can help fill a precise company knowledge, improve hiring decisions, and identify patterns around the highest-value employees. Data provides a sound basis from which to make the best decisions. 

Driving decisions with evidence (not anecdotes) 

And in fact, data-driven decision-making is especially useful within talent analytics. Although it is a feature of all data analytics, the human aspects of talent seem to make the regular problems harder. 

Notably, David Green, a thought leader in talent analytics, has suggested that talent analytics’ core function is to “separate the signal from the noise.” Looking particularly at the “great resignation” period in the wake of Covid lockdowns, Green argued that the panic was, in fact, less severe in reality than many people believed. 

In any situation, talent analytics can give you the hard facts about human behavior in a specific problem – without thinking about the inaccurate discussion around it. 

Use the tech, don’t give up on empathy 

On this blog, we’re unashamedly pro-tech. But at the end of this article, let us remember that HR data processes should be implemented with “human” characteristics – empathy, compassion, and critical thinking. 

We’ve always known this much. At an earlier stage of talent analytics as a business discipline, Colin Strong of Ipsos Mori already reminded us that  – “We all need to manage a bit and say that data should not be the final word…. It’s there to guide you. It’s a way of supporting decisions”. 

To make an impact in HR with tech, you must balance humanity with data. Like so many technological innovations, talent analytics is simply a useful tool.