Author: Steven Chopade

Posted On Feb 29, 2024   |   7 Mins Read

HR analytics is a game-changing tool that enables HR to make intelligent decisions for better talent and business management. According to HRTech experts, HR analytics best works for businesses when they are data focused.

It is good to be data-driven; however, when you are data-driven, you ignore almost everything else that’s happening around you. Being data focused is when you have people within HR and executive leadership who understand data, who are comfortable with it, and who can leverage it in addition to leveraging their own experience.

What is HR Analytics?

HR analytics can be defined as the collection and application of talent insights and data for the improvement of crucial talent outcomes and business results.

HR analytics helps develop critical insights on how investing in human capital assets adds to the success of strategic planning and execution, risk mitigation, cost reduction, and revenue generation for a business. It allows HR to create data-driven insights to enable positive employee experience, enhance workforce processes, and inform talent decisions.

Recently, Harbinger conducted a Power Hour on the topic Unlocking Strategic Insights: A Deep Dive into HR Analytics. Industry experts Prashant Khambekar, Senior Vice President, Harbinger Group; Chris Radvansky, Principal Consultant, Rad Consultants; and Dirk Jonker, Founder and CEO, Crunchr shared their insights on the key aspects of HR analytics.

Let’s look at what the experts had to share on HR analytics and how to prepare to benefit from it in the best way possible.

Example of HR Analytics: Labor Outsourcing Optimization

Organizations dealing with contingent workforces, employers of record, staff augmentation, statement of work (SOW) activity, and staff supply need to optimize four key factors: cost, quality, efficiency, and compliance. HR analytics plays an important role in measuring and capturing critical data on these factors.

You may be looking for a cost optimal way of engaging with a skilled worker and wondering whether you should source them through SOW, contingent labor organization, or fixed-term employment. There are a lot of different considerations that you need to put into the mix, and therefore there is a lot of data that you need to collect.

For instance, you need to understand compensation, statutory in your given location that you’re looking to source those workers, benefits, and supplier markups if you’re going to go with a staff augmentation population. Now, if you’re going to go with SOW, then you may consider diverting that liability or that responsibility to complete a certain project to that supplier. But what could come at a cost?

All these things are related to HR analytics. HR data, compensation, and finance are all interrelated, and none of these can really exist in a silo. Once you do get all that data together, then you need to come up with a business-driven recommendation, and that’s what HR analytics can really enable for you.

How to Prepare to Benefit from HR Analytics

1. Making Available Clean Data

To benefit from HR analytics, it is important to ensure the required data is available and in the right condition or format. The data availability depends on the kind of governance structure you have set up and the kind of systems and technologies you are using.

Chris used an interesting phrase in Harbinger’s recent HRTech Power Hour: “Quality input yields quality output.” You need to ensure that the data you’re receiving for downstream HR analytics operations comes in clean.

80% of the time of data analysts or data consultants is spent scrubbing the data, bringing it together, and making sure it makes sense.

You can work with advanced software available on the market and its configurations to have much cleaner data to benefit from your HR analytics strategies.

Within contingent labor programs, there are tools like vendor management system which is responsible for bringing all the data together – requests, invoices, onboarding, and offboarding – in one cohesive unit. They are helpful from a transactional standpoint and operationally to make sure you are compliant and have some level of visibility.

Generative AI is another tool that can help extract, clean, and compare data within different systems. Within the data analytics space, it can also be used to extract insights from complex and large datasets and to visualize and process data.

Learn how to revolutionize HR strategies with Generative AI and LLM. Explore Generative Ai tools and LLMs for HR. Follow the best practices to implement Generative AI in HR.

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2. Creating a Data Strategy

Once you have the data to leverage HR analytics, it is essential to have a data strategy in place. You can start building a data strategy by using payroll data – this data is checked by HR, accountants, and employees every month. There are many relevant payroll datapoints that you can use for HR analytics, like salary, hierarchy, work location, gender, and job title.

With this data, you can create headcount reports and compare payslips, which helps you know who joined and who left your organization and determine your hire and attrition rates. With salary and gender data, you can identify salary pay gap and gender pay gap in your organization. With information on the number of finance people working in your organization, you can know you have the resources to perform selling, general, and administrative (SG&A) analysis not only on headcount but also on cost.

3. Thinking Startup

It is recommended to ‘think startup’ when planning to have a buy-in for HR analytics. What does it mean to think startup? It means having limited budgets, one shot, and one opportunity to get HR analytics right and basically earning a seat at the table. You may not have the time to build a big data lake or clean up all your data. You need to balance short-term wins with long-term investments.

Pick a problem you could be successful with. It could be a business development problem, maybe you are losing too many good people, or have too many layers in your organization and you need to delayer. Then see if you have reasonably enough data to solve this problem.

Try to be as startup as possible to (within two weeks or so) basically show your HR analytics solution is the art of the possible and can be implemented to solve the problem. With this, you get karma points which allow you to get a bit more investment, time, or attention from executives. This is how you build up your story to get a buy-in for HR analytics. It’s like functioning like a startup.

4. Investing in People

It’s good to have a pilot type of a program and value-based proposition for HR analytics. Having said that, you also need to have people who have a real reason and motivation for creating these essentials. You need to have somebody who is going to drive value, take interest in learning more, upskill themselves, take up a class, or watch a YouTube video to best leverage HR analytics for your organization.

Start Implementing HR Analytics

HR analytics is playing a powerful role in improving HR processes while enhancing the employee experience, reducing attrition, and minimizing costs. This ultimately translates into better business outcomes and increased bottom line. HR analytics can eliminate the need to spend time tracking large volumes of data from numerous sources and allow HR teams to explore and innovate the “human” aspect of HR.

With the various tools like AI and machine learning available in HR analytics, HR teams can have a good understanding of human-business, human-human, and human-technology relationships. HR analytics can empower your HR to become strategic business partners who make significant contributions to your business success.

If you would like to learn more about HR analytics, its applications, and use cases or build HR analytics capabilities to realize improved HR and business results, connect with our HRTech experts at