How can you use HR data to anticipate your attraction and retention actions?

The different ways of using HR data

Before delving into the heart of HR data, let’s take a look at the different ways it can be used.

There are 4 types of data exploitation:

• descriptive: provide a snapshot of a situation ;
• analytical: to understand the causes ;
• predictive: create predictions from hypotheses ;
• prescriptive: proposing concrete recommendations for a given situation.

Leveraging HR data can help you better meet your challenges in terms of talent attraction and retention, as well as employee engagement. Indeed, a better understanding of the origin of tensions within the company and their impact on the most stable employees is essential. This reduces the attrition rate and ensures that measures are taken in good time for “at-risk” employees.

The last 2 types of analysis are those that will interest us most in this article in terms of HR innovations.

Innovative ways to measure employee engagement using HR data

Six parameters can be used to quantify employee commitment within a company. The innovation lies in the way the data is collected and, above all, used.

1. Employee Net Promoter Score, which answers the question, “How likely are you to recommend this company as a great place to work? “
2. Voluntary employee turnover, which focuses on employee-initiated departures.
3. Customer satisfaction ratings (CSAT) gathered through formal customer satisfaction surveys, or more informally through conversations or feedback.
4. Employee productivity
5. Employee absenteeism rate
6. Employee satisfaction score

A variety of systems are used to measure employee commitment: commitment barometers, surveys, regular HR interviews and annual social surveys, such as the one conducted by Great Place To Work, …

Scott Judd, Head of People Analytics at Facebook, has co-authored an insightful article on employee surveys. “ Employee Surveys Are Still One of the Best Ways to Measure Engagement “, he asserts that employee surveys remain a “high-yield” practice for HR.

Today, instead of spacing out the frequency of surveys, many companies are turning to continuous surveys. This method involves gathering employee feedback by asking a single question on a regular basis, known as a “lightning survey”. Most flash surveys work by asking one question a day. It takes a minute to answer, so your employees don’t feel overwhelmed by the task.

The aim is to gather feedback and respect employees’ space and time at all times. No need to bother employees with long questionnaires.

Some companies prefer to launch questionnaires just after “HR highlights” such as salary reviews, annual interviews… which often have a direct impact on employee engagement. This increases the number of responses to questionnaires.

Boosting employee attractiveness and commitment through data science

The world of big data is profoundly transforming the job market and the various existing professions. In human resources,data analysis to confirm past trends has been around for many years. What is less so, but is beginning to emerge, is theuse of data to build HR strategies.

Data analysis of employee engagement measurement systems is a first key to entry. Results are consolidated in real time and accessible to managers and HR. Engagement questionnaires measure the feelings of teams and transform them into concrete actions that sustainably improve QWL.

Applicable in a wide variety of sectors, predictive data analysis in human resources can be used to :

Improving recruitment

A profile adapted to the needs of a position is more committed and loyal, and has a direct impact on the turnover rate. For example, it can also analyze CVs, recognize how often a person changes jobs and calculate the likelihood of them changing again. Data science can also understand the types of career paths candidates are likely to follow by analyzing career trajectories across millions of different data points to spot trends.

Optimizing performance

Optimize organizational performance and, at the same time, anticipate demotivation and failure factors.
Anticipate foreseeable departures (e.g. retirement, maternity, etc.) and also statistics (e.g. demographic data or trends by business sector, location, etc.).

Ensure the company’s development

Ensure the company’s development through better decision-making: help make the company more attractive and boost employee satisfaction.

Assessing skill levels

Evaluate employees’ skill levels and anticipate skills development: an employee who has greater confidence in his or her personal capital and who is developing skills is more likely to stay with the company.

Anticipating moments of demotivation

By referring to their productivity and objectives, anticipate moments of employee demotivation.

HR data analysis can also be used to assess the skills available within the company, in order to enhance internal mobility. HR data is based on job-skills matching, which compares the profiles of the company’s employees with vacant or future positions.

All these areas of analysis make it easier to identify the issues that motivate or demotivate employees. The real value of these studies lies above all in the discussion they provoke and the concrete actions they lead to.

Employees are more attached to a company that allows them to evolve and offers them change. It also contributes to employee satisfaction and well-being in the workplace, creating a positive dynamic.

What are the challenges faced by HR data in improving employee engagement?

Many HRIS systems already allow you to use HR data with the help of Machine Learning to produce a predictive analysis of HR trends.

The use of quantitative data such as age, performance rating or absenteeism rate is rather simple and objective. The difficulty may lie in interpreting qualitative data, such as annual interviews. However, it is essential to make the most of personal data in order to recruit the right talent, but also to keep them happy to guarantee their productivity…

HR data can be rich in information, but they are also subjective and can vary from one individual to another. Analyzing this data often requires skills to extract meaningful trends and actionable information. HR teams therefore need to be trained in the use of these tools to take full advantage of qualitative data.

However, with the right tools, the right skills and a personalized approach, companies can overcome these challenges and fully exploit the potential of HR data to create a more engaging and productive working environment for their employees.

Conclusion

In conclusion, HR data represents a considerable opportunity for companies wishing to remain competitive in a constantly changing world. By exploring the different types of HR data exploitation, we were able to glimpse how these HR innovations can improve talent management, employee engagement and job satisfaction.

The adoption of innovative methods opens up new perspectives for human resources. These approaches not only anticipate the company’s talent needs, but also create an environment where employees feel listened to, valued and encouraged to evolve.

However, it’s important to recognize that HR data is not without its challenges… Interpreting qualitative data requires appropriate, personalized support. At SQORUS, our multi-disciplinary HR & Data Council teams are at your service to help you make the most of your HR data. Don’t hesitate to contact us if you have a use case you’d like to test as part of the SQORUS LAB.

This article is one of a series dedicated to HR innovation, the fruit of research, analysis and reflection by the LAB SQORUS teams.

SOURCES

• Supermood, Ebook – measuring and developing employee commitment
• https://www.gartner.com/smarterwithgartner/9-work-trends-that-hr-leaders-cant-ignore-in-2021
• Esmoz blog
• Applauz, 8 best practices for measuring and improving engagement
• https://www.digora.com/fr/blog/bien-utiliser-la-data-rh-pour-booster-lengagement-des-collaborateurs
• https://www.groupe-partnaire.com/fr/engagement-salaries/
• SWILE, the dictionary of commitment
• https://www.forrester.com/blogs/previsions-tendances-2022-experience-collaborateur-fr/
• https://troops.fr/blog/mon-agence-et-mes-candidats/la-gestion-predictive-des-rh
• https://www.talend.com/fr/resources/analyse-prescriptive/