What's the best way to track and report your recruiting metrics?

Traditional "transactional" metrics such as time to hire/fill, cost per hire, cost to advertise & applicant volume; while important, are process and efficiency focussed. Sure, we can get an applicant through an interview and onto a desk - but how well will they perform in role, and will they stay? With predictive metrics, the organisation's focus is on the effectiveness of their hiring process, and the quality of hires; for example how well they will perform in role, or attrition rate in the first year, the effectiveness of the sourcing method, or the inclusivity or diversity of sourcing method used. A move towards predictive metrics, is a move towards unlocking greater value from your hiring function, through the use of data and insights.

It all starts with choosing the right metrics to track. If you're not following the right metrics, you'll send yourself on a wild goose chase chasing and tracking numbers that doesn't matter. At the end of the day, what matters most the people you hire & retain, and how efficiently you're doing it. Submittal to interview, interview to hire, submittal to hire are all metrics that I track to help me get there.

To track and report recruiting metrics effectively, start by selecting relevant metrics such as time to hire, cost per hire, quality of hire, source of hire, and candidate experience. These metrics offer insights into both the efficiency and effectiveness of your hiring process. Time to hire and cost per hire help measure process efficiency, while quality of hire and source of hire focus on the value and origins of your candidates. Candidate experience assesses satisfaction throughout the process. By incorporating predictive metrics, you gain deeper insights into performance and retention, enhancing your hiring strategy.

I feel like recruitment reporting metrics should be aligned to the markets. If they change, metrics sholud adapt as well. While in the past these traditional metrics were good enough to reflect on key numbers and give good insights, for the current market situation we need to focus on predictive metrics as well. Further analyzing what great talents that got hired revently have in common will help to find good talent in the market and save time. E.g. When I was hiring graduates for a Sales entry level positions, we had found out that the best performing new hires were all engaged in competitive sports. This way we adapted our search and focused on this competitive aspect bringing in better quality candidates, reducted time & cost per hire.

Another matric I tend to track is the panel evaluation feedback ratings of the candidates. For some crucial critical roles this may help to look back to the history and see whether any of the rejected candidate may be reconsidered. At times we may have to compromise on the mandatory requirements because of the scarcity of resources on those particular job role or Technology, This metric data will provide you and insight such decision making

If you’re manually collecting data, ensure you do it on a regular basis to not make it a daunting annual task. Also, ensure your entire team is looped in so they can effectively act as owners and adjust their hiring practices accordingly when things aren’t working.

To effectively track and report recruiting metrics, start by collecting accurate and reliable data. Use a consistent system for gathering and storing this data, like your ATS or HRIS. Define metrics clearly—what counts as a job opening or hire—and ensure consistency across sources. Regularly check for errors, duplicates, and missing values. By maintaining a standardized approach and correcting data issues promptly, you'll have a solid foundation for insightful and actionable recruiting reports. This way, you can make informed decisions and drive better hiring outcomes.

In my experience, data collection in the recruitment setting can be very challenging as most companies have not yet fully focused on recruitment metrics but more on their sales departement. Meaning, there is no possibility to collect the right data at all, or there is gaps in data collection or some part of your data is missing. In such settings, it is crucial to decide on how to handle such data and how to deal with missing data.

Accurate data is the cornerstone of effective recruitment metrics. Establishing a robust system for data collection, ensuring consistency, and standardizing definitions is paramount. This meticulous approach guarantees the reliability and integrity of your metrics, enabling sound decision-making in the hiring process.

Accurate data collection is the backbone of effective recruiting metrics. It's like building a sturdy foundation for your house – without it, everything crumbles. Consistency and standardization are your bricks and mortar, ensuring that your metrics are reliable and comparable.

Be aware that outliers can have a disproportionate impact on your dataset. For example, one complex executive role that takes 9 months to fill will inflate your time-to-fill metric for the year if your normal time-to-fill is about 2 months.

To tackle recruiting challenges effectively, start by analyzing your data for key trends and insights. Compare your metrics to benchmarks and industry standards. Break down the data by role, department, location, and level to understand how different factors influence your results. For instance, assess how time to hire varies by role or how quality of hire differs by source. Look for patterns, such as the impact of hiring volume on cost per hire or how candidate experience affects retention. This approach helps you identify areas for improvement and refine your recruiting strategy.

Analyzing meaningful trends in recruitment metrics goes beyond numbers; it's about extracting actionable insights. By comparing data against benchmarks and segmenting it by relevant factors, we uncover valuable patterns. This deeper understanding enables us to refine strategies and make informed decisions in the hiring process.

I would like to see a cutural shift in recruiting metrics to look back at candidates that did not convert, but who did very well in prescreens and interviews. Many companies say, "we'll keep your information on file for future roles"...but they often never reach back into that database to mine for great candidates that have already passed muster! It's cheaper to cycle in past candidates already on file, rather always hunting for new ones, but I don't see this happening on a wide scale. Kudos for Google, though, their recruiters absolutely do source from previous candidate pools.

Presenting clear reports on recruitment metrics is an art of communication. Tailoring information to suit the audience, utilizing visuals, and emphasizing key insights ensures that stakeholders grasp the essence. By encouraging feedback, we foster collaboration and ensure our reports remain dynamic, serving as valuable tools for decision-making and progress tracking.

Although this article pinpointed no universal set of metrics when recruiting, I like to speak on the underutilization of the number of quality candidates that are not being hired versus the time to hire. These are two top metrics that identify inefficiencies in the recruiting process. Time is money and so is talent.

No matter which metrics you're tracking, I think it's most important to be consistent and to act upon the data. Measurement without action will not lead to improvement. If you're tracking the same metrics month over month, you can choose one or two items to focus on improving each quarter (or half-year or year). And because recruiting and the job market overall is highly volatile and susceptible to many different influences, it's key to look at trends over time, versus an outlier one month, to determine what's working or not.

In my opinion, I think it should start with making sure you have a robust infrastructure & set of tools in place to allow you to do so. i.e.: Do you have all the right tools in place for effective data collection needed for these metrics? Are you going to be able to promptly act upon your metrics, if these require a huge manual push due to the lack of automated & appropriate processes & tools in place? Secondly, and I think this is somewhat overlooked in some workplaces, ensure that all Database/ATS/other tools users have the appropriate training on how to use these tools effectively. The outcome will only be as good as the input, so if the users are inputting data inaccurately, that will negatively impact the results.