Am I really an expert?
Maybe not. I know some stuff; I probably know a lot of stuff but I for sure do not know everything. Collectively, I know that we can come up with better solutions as a team. So, let’s work to expand our own personal “area of expertise” by asking others AND being willing to listen and take advantage of our differing perspectives. You have to start somewhere, and I am advocating you start from a position of shared knowledge to avoid sitting in that zone of utter ignorance.
The Scenario
I am a newly hired Chief Human Resources Officer (CHRO) and my primary goal is to ensure that the organization not only attracts but also retains top talent. In today’s competitive job market, data-driven decision-making is essential to thrive, and that’s where HR analytics plays a crucial role. But where do I start? I can see that the team has been capturing data, running metrics, and presenting results. But are we measuring what matters? It’s not a question of effort, it’s more a challenge on the direction and purpose of measurement activity; that’s what I was hired to do. I want to be sure that our company measures what matters and acts on what we learn. So, where do I start?
Getting Started
From my perspective, you first must clearly understand the problem you are trying to solve. Start by understanding the business problem or the goal of the analysis. Work closely with stakeholders to establish clear and specific objectives. This will provide a foundation for selecting metrics that align with the overall goals. I did this by stating that my focus is on hiring and retention. Broad concepts to be sure but my intention was to create some consideration around what that means.
Luckily, my new company has three talented data scientists that have experience, insight, and a willingness to share their perspective. So, I posed a question to the group, “what metrics should we measure and monitor (at least initially) that will . . . “
- Make people want to work at this organization if they don’t yet
- Motivate employees to stay if they already work here
OR - At least think fondly of us if they have left the organization
In this blog post, I will discuss the significance of HR analytics and share some perspectives on the most relevant metrics from three seasoned professionals in the HR analytics space.
The Power of HR Analytics
HR analytics involves the use of data to gain insights into various aspects of the workforce. By leveraging this data, we can make informed decisions and create strategies that align with the organization’s goals and enhance overall performance. From talent acquisition and development to performance management and employee engagement, HR analytics have the power to transform our workforce.
My objective is to define the most relevant metrics to build a robust talent attraction and retention practice that focuses on the health of the organization and is NOT an exercise in proving the value of an HR team.
The key recommendations from the data scientists show the desire to push organizations to go deeper and not just measure what’s in the measure pack, what you’ve always been measuring, or what other companies are measuring EVEN IF they are considered a “best practice” company. The summary below is focused on top three recommendations and the related themes within those recommendations. There are other metrics that could be considered but this is an experiment in starting from a clean slate. Take a moment to consider the commonalities and differences and the patterns in their supporting “why”.
Data Scientist 1
Suggestions:
- Forecasting new hires
- Employee engagement
- Identify your high turnover risks (where losing a person could cause problematic gaps)
And here’s why:
Organizations tend to focus on reactionary data; on what already happened. The way I see things the past has already happened and simply reporting on it is useful, but I don’t think it brings as much value as trying to forecast. My suggestion is to have a KPI or benchmark of what roles and skills we need to hire. Anticipate the business and understand what type of resources the organization needs to successfully achieve the desired results. Forecasting attrition may be challenging but it is future focused and can be aligned to future skill needs and help the organization before the employee leaves.
Data Scientist 2
Suggestions:
- Cost of loss per resource – quantify the cost of losing a resource
- What are the signals that affect employee engagement and retention
- Skill gaps across the org with shifting business environments and skill gap closure plans
And here’s why:
Calculating the cost of loss per resource down to the position / role can make an impact by putting the turnover in a financial lens. Cost will be different across different positions within the organization and where you have key talent or highly valuable skills, knowing the cost can be useful right from the point of hire to ensure the employee experience supports retaining this talent.
Suggestion 2 is related to cost of loss and is not just pay and benefits. Look at who leaves and whether they took advantage of benefits offered alongside other signals, which would lead to possibly being able to forecast who may leave and having a defined lever to increase employee retention. In a retail environment, for example, even increasing average employee retention by a few weeks would be a huge cost saving to the organization.
Knowing your skill needs and gaps can help an organization define:
- How will my skill needs shift in the coming years?
- Who do I retrain for what and how do I do it most effectively
- Do I need to hire for new skills or can I develop them internally?
- How do I train/hire for net new skills (carbon capture, etc.)
Data Scientist 3
Suggestions:
- Voluntary Termination Rate (VTR)
- Termination Rate Less Than One Year
- Application Started but Not Finished
And here’s why:
Voluntary Termination Rate refers to the percentage of employees who leave an organization on their own accord, typically through resignation or quitting. This metric has likely gained importance in the field of Human Resources (HR) due to several reasons such as remote work and changing dynamics in the job market and an increased focus on employee experience and engagement. HR departments and organizations are becoming more and more data driven and employee expectations are increasing; measuring voluntary termination rate can help provide insight into why people you wanted to keep decided to leave.
Along with VTR, employees who leave your organization in less than a year should raise a red flag and can indicate issues related to recruitment, onboarding, or initial job fit. This is an indication that their actual experience fell short of expectations. Possibly the talent acquisition process is deficient and gathering feedback from employees early in their career with your company can provide insight into problems with job previews and descriptions, interview processes, or initial job orientation and training may be inadequate in preparing the person to fulfill the role responsibilities.
The third suggestion is novel and ask the organization to consider if their processes are complicated or inefficient and what impression that leaves on a candidate. If a significant number of candidates start the application but do not complete it, it could signal issues with the application process itself including overly complex forms, technical glitches, or a lack of mobile optimization. Imagine if it’s this difficult to apply for a job, how hard might it be to get things done as an employee.
Key Learnings
The parameters for this scenario were to focus on “what metrics should we measure and monitor (at least initially) that will . . . “
- Make people want to work at this organization if they don’t yet
- Motivate employees to stay if they already work here
OR - At least think fondly of us if they have left the organization
The common themes from all three data scientists are about skills and being clear about what the organization needs and cannot afford to lose. A second resounding focus across all three data scientists and their suggested metrics is about the employee experience as well as the candidate experience. Work has changed and so have expectations. Employees are no longer willing to stick around and just hope something changes. It is important for organizations to anticipate and forecast needs and wants early and find ways to gather that data and report KPIs in a more target basis (e.g., turnover in less than a year vs. overall turnover rates). This gives the organization a better chance at changing programs and processes that new employees are exposed to and provide input into longer-term practices designed to develop and retain the skills the organization needs now and in the future.
I love this exercise because it shows that if you ask, your team will contribute. They have ideas on what to measure and they know what KPIs tend to be expected but really are not that helpful. They are curious about new ideas and patterns they see in the data as well as what they learn from being part of the workforce. Starting from a blank slate might seem crazy and reckless but take a chance. In the old days (college in the 80s) there were degrees in business management, finance, or marketing BUT today there are specialized degrees in data science and HR analytics and so many unique specialties so put your team to the test and let them use what they learned. We are well past the days where measuring cost of hire, days to fill, and turnover are enough.
Consider what is relevant in your organization and why it matters. As always, it’s critical to think longer-term about what actions the organization is able and willing to take. Capturing a metric that shows poor results is not helpful unless you have the approach that you are willing to do what it takes to implement changes to programs, practices, and policies designed to improve.
It’s time to be creative and collaborative. It’s time to start with the most pressing problem, solve that problem and then define the next problem to tackle. Dig deep, don’t surface measure. Take a chance and not only consider what to measure but be very clear on the WHY!
Conclusion
The industry is full of recommendations, best practices, “everyone measures this”, and so on. But does that mean everyone really does have to measure and monitor these best practices? NO. What is best for everyone does not always mean it is best for you, especially not right now.
Building an HR analytics practice focused on talent attraction and retention is vital for the success of this fictitious organization in today’s competitive business landscape. By harnessing the power of data and using relevant metrics, we can make smarter decisions, implement effective strategies, and create a workplace where top talent thrives. As a CHRO, my commitment is to leverage HR analytics to drive our organization towards a brighter and more prosperous future, where our employees feel valued and inspired to reach their fullest potential.
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