Change Management WalkMe TeamJanuary 24, 2022

An introduction to HR analytics for change management

3/5 - (2 votes)
An introduction to HR analytics for change management

It is important to clearly define HR analytics – the journey towards investing in this powerful technology starts with a clear understanding of what HR analytics are and how they can help your organization achieve its goals. 

According to the Chartered Institute of Personnel and Development, HR analytics – also known as people analytics – describes the process and technologies relating to “gathering and analyzing data about people in a workforce”. Data about employees not only exists within HR systems, such as staff records, but can be gleaned from other departments within organizations, such as IT, sales, marketing, production, manufacturing and creative services. In addition, external sources, such as industry-wide surveys about salaries or working conditions, can be added to the HR analytics database.

The process of leveraging HR analytics effectively helps organizations develop strategies to positively manage change and identify how people at all levels can play their role in driving change. 

Are there different types of HR analytics?

There are three main types of HR analytics: descriptive, predictive, and prescriptive. It is important to understand the difference so they can be used to their full potential. In short, these three types of HR analytics vary in depth and detail and can be used together to ensure the best quality data is gathered, analyzed and used for organizational change and improvement.

  • Descriptive analytics: Perhaps the most basic level of analytics, descriptive analytics use, as the name suggests, descriptive data to provide a picture of organizational health. Simple data, such as annual leave records, records for leave in regard to factors such as illness or bereavement, staff retention and turnover rates, and recruitment rates. When HR leaders take this often superficial data to the next level, deeper analysis can result in important insights. For example, intensive analysis of reasons for sick leave, such as stress, when combined with analysis of staff turnover and reasons for resigning can help identify issues within an organization that require remedying. 
  • Predictive analytics: Descriptive analytics can help with determining predictive analytics, but this level of analysis demands additional data to help organizations predict future trends. External industry and labor market data, for example, could be used to determine factors that could affect an organization’s workforce planning and optimization processes. If external data pointed towards a shortage of workers in a certain demographic, this could affect an organization’s ability to recruit people for a period of growth. When such insights become apparent via predictive analytics, a business can take early actions to prevent staff shortages, such as additional staff training or casting the recruitment net to a wider geographical area.
  • Prescriptive analytics: This is where the results of descriptive and predictive analytics come together to automatically devise recommendations for change management and organizational improvements. This is perhaps the most powerful type of HR analytics, but it does require investment in analytic technology. Continuing on from the above example in regard to predicted staff shortages, prescriptive analytics could be engaged to automatically recommend training programs to upskill people who already work for the company or suggest recruitment solutions to find people outside the local area.   

Why are HR analytics important?

It is crucial that HR professionals can clearly communicate to senior management about the importance of HR analytics. This is especially important when making a strong business case for investing in technology to facilitate the process of analysis and, critically, taking action as a result of analysis. The business case for introducing HR analytics and the associated technologies needs to focus on real return on investment (ROI) that can be achieved. Workforce planning can then be taken to the next level.

HR analytics should provide organizations with the detailed insights needed to best manage employees and meet business goals – it is the ability to communicate these bottom line benefits that come with a well-managed workforce that will lead to investment.

The sheer quantity of available data can be overwhelming, but when HR teams can, with the help of the right technology, identify which information is the most relevant and use it effectively, the ROI benefits are easily demonstrated.

Bottom line benefits for introducing effective HR analytics systems include:

  • Improved staff retention: When HR analytics can effectively examine the reasons for workforce attrition, action can be taken before minor concerns turn into major problems. Data from exit interviews can be useful for this process.
  • Fast action when issues are identified: Improved staff retention is just one area where HR analytics can be used to ensure the bottom line is not affected. For example, if analysis of sick leave data reveals issues with large numbers of employees taking time off for stress-related reasons, this would be a good opportunity for an organization to take proactive steps to improve staff mental health
  • Prevention of staff shortages: HR analytics that take into account wider industry data and detect major trends will stand an organization in good stead if they can avoid labor shortages. There can be a number of reasons for labor shortage, including internal and external factors. While descriptive data gathered within an organization can help prevent staff shortages, predictive data based on external factors can have a more powerful impact. If factors, such as major demographic changes and immigration patterns, can be analyzed in conjunction with internal data, costly staff shortages can be flagged up early and more easily avoided. 
  • Staffing levels aligned with economic conditions: Whether your organization has been experiencing tough financial times or you are in a period of growth and expansion, using HR analytics insights will help ensure staffing levels are optimized. Staffing costs are generally one of the biggest expenses of any organization, so using data constructively means the right balance can be struck between payroll expenditure and having enough people on board to meet productivity targets. Especially as businesses are recovering post-Covid, this aspect of business is more important than ever.
  • People deployed in the right place at the right time: Smart staffing is not just a numbers game. While it is important to have the right number of people working in your organization, it is equally important to make sure they are properly deployed. Are you getting the best value from your team? HR analytics can provide the information you need to be aware of productivity levels and how every team member fills their working day. Data from a skills audit, for example, can be used to determine if everyone is in a role that best suits their skills. Properly deployed people are generally more productive and happier – this achieves the twin bottom line benefits of high productivity and improved staff retention. It’s a win-win.

Getting started with data gathering

Starting the process of introducing HR analytics can seem daunting, especially when new technology has been introduced. Obtaining senior management buy-in to implement HR analytics and invest in the right solutions to optimize the process is just the beginning. But data collection as part of a digital transformation process for the HR department can and should result in far-reaching, long-term, positive outcomes for the whole organization.

The three types of HR analytics data – descriptive, predictive, and prescriptive – are all important to the overall process. Ideally, all three types of data should be collected and analyzed in conjunction with each other to get the best possible insights.

Gathering descriptive data is the obvious place to start, especially as this is the most basic level of data and it should be readily available in the records of most HR departments. On the surface, descriptive data is raw and therefore might not seem particularly useful at first glance. What is important here is the process of aggregation and analysis.

When climbing the HR data mountain, it can be helpful to start with the absolute basics and build in more detail. A headcount of all employees is a good place to begin – once you have this raw figure, a simple number, you can then start breaking it down into further categories, such as age, gender balance, and education and qualification levels. Even this basic information will start to paint a picture of an organization and important insights will start to emerge. For example, if you discover that a significant proportion of your workforce is getting close to retirement age, you might want to consider developing a solid succession planning strategy.

From here, more sophisticated and detailed metrics can be added to bolster the data, deepen the insights, and be the catalyst for positive workplace change. Turnover rates, for example, can be instructive when analyzed alongside the reasons for leaving. This is another example of descriptive analytics so caution is needed because such data tends to focus on the things that have already happened. 

Solely focusing on descriptive analytics is not the most effective way to undertake a comprehensive HR analytics program because it tends to be reactive rather than proactive. This is why it is essential to move on to the more detailed, forward-looking metrics of predictive and prescriptive analytics, which is vital for detailed insights and better decision-making. 

Taking the next step towards being proactive

Predictive and prescriptive HR analytics will result in a more proactive approach that can evolve to align better with business needs.

When adding the next layer of analytics – the predictive and prescriptive layers – to the HR datasets, it can be as overwhelming as getting started with the basic descriptive data gathering and aggregation. But there are two key ways to overcome the big data fear, take a deep dive into more advanced HR analytics and reap the benefits. 

  1. Bring on the technology: If you have made a strong business case for technology investment, now is the time to be fearless. Digital transformation is having an incredible impact across all industries and across all departments within organizations – and HR should be no exception. If you are unsure of how to get started with the right technology for your organization’s needs, do not be afraid to ask for help. 


Different companies have different needs, depending on a wide range of factors, including size of workforce, type of industry, and quality of internet access. But when you have found the right technology and you are comfortable using it, the sky’s the limit in terms of what can be achieved.

  1. Keep your eyes on the prize: Whenever the digital transformation process seems like an onerous challenge, remind yourself of the myriad benefits. As well as the financial benefits that led to making the business case for technological development in the first place, do not forget the benefits of having a happier, more productive workforce with employees who look forward to coming into work.

    Predictive and prescriptive analytics require that extra commitment to digital transformation, but when you realize you can do things such as help determine if potential employees will be a good cultural fit before they are hired, or spotting opportunities to offer extra training to advance the careers of junior team members. There is even technology available now to help make predictions such as how long new hires might stay with the organization. 

The power of digital transformation

In this data-driven age, knowledge is power. Information has become an incredibly valuable commodity. Everything from market intelligence to insights about how an aging population might affect your workforce can be gathered and analyzed so your organization can be continually proactive and dynamic. 

Understanding not just the simple definition of HR analytics, but being empowered to use technology to take the HR analytics process to great heights will be transformative for your organization. 

Technology should be your friend during this process. What might seem like a daunting task, especially in larger organizations, can become genuinely meaningful with multiple benefits if the right solutions are leveraged to meet your needs to save time, money and create an organization that is driven by solutions rather than being in a constant cycle of reactive crisis management. 

At its best, adopting a forward-thinking, proactive approach to HR analytics will improve employee engagement across every level of the organization, as well as boosting business.

If you liked this article, you may also like: