Brainstorming data and metrics lead to analytics

Organizations are becoming more data focused and create strategic goals built with key performance indicators (KPIs). If HR expects to keep that proverbial seat at the conference table, it’s important to understand key data concepts, including the difference between data, metrics, and analytics and how all three work together.


Metrics set the parameters for the data your organization will use to measure performance. Let’s say you’re looking to measure the performance of your talent acquisition (TA) team. An important metric to look at would be time to fill. Time to fill is the average days it takes for your TA team to fill open positions. KPIs are then built from the metric. A KPI for the TA team could be keeping time to fill below 45 days. Make sure you clarify the parameters of the metric and apply them consistently. For example, do you stop counting days when the offer letter is signed or the new hire’s start date?


Data is the set of numbers or calculations gathered for a specific metric. For the TA team’s metric, time to fill, the data would be the actual number of days. Each team members average number of days to fill a job would also become a part of the data set for the metric. Data integrity is vital to ensuring your metrics are accurate.


Once metrics are produced, it’s time to analyze and find patterns in the data. Analytics require more critical thinking skills to look for the why behind your data and to use metrics to guide decision making. For instance, your TA team’s time to fill metric is produced and you find that it is trending high. Asking the TA team what challenges they are experiencing and doing a task analysis will help find why the metric is high. The investigation shows that there is a breakdown in communication between TA and hiring managers for scheduling interviews. It can be two weeks before an interview is confirmed with the candidate. This leads you to interview the hiring managers and finding that managers are not using the scheduling feature in the applicant tracking system (ATS). As a solution, ATS training is rolled out to managers. Once the solution is implemented, monitoring the time to fill metric and seeing if the trend changes is a part of analytics.

Analytics are key to organizational success

The entire process of finding trends in data with metrics and using the information to support business objectives speaks to analytics. If your organization is becoming more data focused, it might be time to consider building an HR dashboard. It uses data from your various HR systems to output metrics and leaves you open to focus on analytics. An HR dashboard supports data integrity as it takes human error out of the calculation process.

Data, metrics, and analytics all mean different things but work together to support strategic goals. You can’t develop metrics without data. Without metrics, there are no trends to analyze and it’ll be harder to find the relationships within the data. And metrics without analytics is just a waste of the time it took to make the calculations. Analytics are key to making HR the strategic business partner organizations need.  Don’t forget to listen to the story your data is telling you and take action.

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