Metrics and analytics continue to be challenging areas for HR. In the McLean & Company 2021 Trends Report, we found that HR departments averaged just six out of ten in effectiveness at facilitating data-driven decision making and barely 10% of HR departments are highly effective (n=456). In today’s world that’s not good enough. Digital transformation is accelerating faster than ever, and organizational leaders increasingly demand data to inform all decisions, including those about the workforce.
In our conversations with HR leaders across industries and across the world, as well as our extensive research on the topic, a few common challenges in getting started with metrics and analytics have emerged. These challenges can be grouped into four categories, which we used to develop our foundational model for HR metrics and analytics:
- Data Plan: A strategic understanding of the intended use of data and how it will add value.
- Data Governance: Processes related to data, like ensuring accuracy, availability, and integration.
- Analytic Capability: The ability of the HR team to conduct and understand data and analysis.
- Data Adoption: The extent to which data is being used to drive decisions in the organization.
Image source: McLean & Company
For HR to master metrics and analytics, we need to first ensure these four foundational elements are in place.
A data plan is a strategic understanding of the intended use of data, which means defining the intended audience and their needs, how the data will be used, and the methodology for data collection. It underpins the other three pillars of HR metrics and analytics, so should be defined on a high level before tackling anything else.
- Who is our intended audience for HR metrics and analytics?
- What types of decisions will the data drive or inform?
- How, and by who, will data be collected and analyzed?
Identifying and documenting the answers to these questions will help inform the decisions you need to make as you improve your HR department’s effectiveness with metrics and analytics by limiting the scope of work to what will have the biggest impact.
Data governance may not be the most exciting topic, but it is critical to ensuring that the data you have available is accessible, up to date, and most importantly, trustworthy. McLean & Company defines data governance as:
“A collection of processes and definitions that work together to ensure acceptable data quality. It should include, at a minimum, standard definitions and clear accountability for data quality.”
If you don’t have processes, definitions, or accountability for data yet, you’re not alone. But establishing these things is a critical first step to building an effective and trustworthy HR metrics and analytics function.
So where to start? It’s important to note that while poor data can lead to incorrect conclusions and undermine confidence in HR’s analytic capability, achieving perfect data is extremely time consuming and may not add much value. Get started with an easy first step to ensure you’re not overwhelmed by trying to make your data perfect all at once – a data inventory.
How do you get started with a data inventory? Document all the different data elements available about the workforce (e.g. PA ratings, start/end dates, demographic data). For each data element, capture the location (where the data is housed), the owner, any security or compliance requirements, and how frequently the data is updated.
With this as a starting point, you will understand what data you have and where it lives. From there you can start doing some basic analytics, targeting a more in-depth data audit down the line to continue to improve your data governance.
Analytic capability refers to the ability of your HR department to transform data into insight and outcomes. This includes both the competencies required to conduct analytics and the capacity to do so.
McLean & Company has identified four key competencies for metrics and analytics:
- Data Analysis
- Business and Financial Acumen
- Organizational Awareness
- Problem Solving and Decision Making
How does the team who will be conducting analysis stack up in these four areas? Consider training to help upskill your HR team, like training on data literacy or business acumen.
But don’t forget about the capacity piece of capabilities. Is there sufficient FTE to support your goals with HR metrics and analytics? A good way to manage capacity is to create a process for managing and prioritizing ad hoc requests for HR data, which can quickly bog down a team if not carefully managed.
Metrics and analytics will provide no value if they’re not adopted and used by decision makers. With your target audience in mind, ask yourself about their:
- Awareness: Do clients know what data and support is available?
- Comfort in using HR data: Do clients use HR data in their decisions?
- Leadership support: Do leaders buy into HR metrics and analytics?
- Culture: Does the organization value data?
Identify potential pain points in these four areas and plan to address them to ensure the work you’re doing is used and valued by your audience for the data. A great way to get started here is with training in data literacy.
The Big Picture
Improving HR metrics and analytics is not something that can be done overnight. Moving from individual data points, to combining those data points into metrics, to using statistical tools to conduct analysis, to taking advantage of advanced analytics like AI or machine learning is a long path.
The first step on that path is to master the basics by building a data plan and getting started with data governance. Check out McLean & Company’s Become a Data-Driven HR Function research for step-by-step advice, tools, and templates.
By: William Howard