Translating HR metrics into business results: how to talk to management in the language of numbers

Metrics alone are insufficient for decision-making. It's only when we gather different metrics together and logically connect them to the processes we're trying to analyze that they become tools for analytics.

Why you need HR metrics

Even well-chosen metrics may not be enough to talk to the business. It often happens like this: an HR specialist comes to a business, shows the metrics, and says, "We have a problem here." The business responds: "Yes, we have a problem. But there's no budget to solve it."

Typically, "no budget" doesn't mean that the business doesn't actually have the money. If the company really doesn't have money, it means it's on the verge of bankruptcy, and then HR issues aren't a priority. But if the problem is not so global, and the business still says "no budget" - it means that the financial benefits of implementing your HR project are not obvious to it.

Industry experts often point out that this happens because projects within a company compete for investment. To convince the business that your project is a more attractive investment than another, it's important to show them where their problem lies and what economic losses are hidden behind the indicator you're presenting.

The higher the cost of a problem to the business, the greater the motivation to solve it. For example, stating that employee turnover is 30% will sound alarming, but perhaps not alarming enough for the business to address the issue and invest money in a solution.

However, you can paint a clearer picture:

• Losses from turnover amount to 3 million;
• By increasing salaries, these losses can be reduced threefold — down to one million;
• To achieve this, salaries need to be increased by one and a half million.

Now, this becomes a potentially attractive project with a profit of half a million. It's crucial to show the business data they can understand and incorporate into their processes.

Classifying HR Metrics

Strategic Metrics

Strategic metrics are directly linked to business outcomes. These are metrics that show an impact on revenue or profit.

From a revenue perspective, this could be labor productivity or staffing levels. The logic is simple — revenue is the number of people multiplied by the valuable product each of them produces. Therefore, it's important to track whether you have these people (staffing levels) and how well they are working (labor productivity).

From a profit perspective, there are two options — either increase revenue or reduce expenses. The ratio of these two figures gives you the profit the company can expect. Here, it makes sense to look at the share of payroll costs in revenue, the cost per employee, and other similar indicators.

Operational Metrics

The challenge with strategic metrics is that they don't appear immediately — the effect of our actions on these figures can't be seen instantly. By the time the effect becomes noticeable, it might be too late — although we can correct the strategy for the future, the specific project might have already failed.

Therefore, we need operational metrics that help us understand if we are moving in the right direction and whether the set strategic goal is achievable at all. For example, if a business is actively growing and needs to quickly staff its team, the strategic metrics here are staffing levels and new hire productivity.

In turn, operational metrics for monitoring the process include:

• Time-to-fill vacancies;
• Number of candidates at the top of the recruitment funnel;
• Conversion rate of the recruitment funnel;
• Onboarding program performance indicators;
• Interim results of new employees.

How to Implement HR Metrics in Your Company

To formulate the necessary metrics, you should ask yourself six key questions:

1. What is the business objective?
2. What must employees do to achieve this objective?
3. What is the current situation, and what might hinder achieving the objective? To answer this, analyze: the labor market conditions, HR processes, the existence of onboarding programs, whether there are individuals responsible for new hire onboarding, and how recruitment is organized.
4. What is HR's role, and which HR processes can support the business?
5. Which indicators allow for tracking the results? At this stage, formulate strategic and operational metrics.
6. What raw data do we need? This question is crucial — you can come up with excellent metrics and then realize the company simply doesn't have the data to calculate them. Therefore, it's essential to:

• Understand what raw data is necessary;
• Align the idea of an analytics system with current capabilities;
• Identify any critical data gaps and create a plan for future collection.

In such conditions it is difficult to talk about labor productivity growth. The HR service, having analyzed the turnover rate, determines that it is functional - it is not rare and valuable specialists who leave, but employees who can be found on the market. However, due to high turnover rate, constant training of newcomers creates heavy loads on the adaptation system.

In this case HR should focus on the following aspects: fast recruitment and adaptation program organized as efficiently as possible, with minimal load on experienced employees and quick introduction of newcomers to normal performance.

How to work effectively with HR-metrics

Companies face three main groups of difficulties when working with HR metrics.

The first group is data problems:

• data is missing;
• data is stored in different systems;
• when combining data from different sources, they are not consistent with each other;

• human error when manually entering data into Excel (information is lost, overwritten or forgotten).

  

The second group is methodological problems. 
They arise when the company has not initially agreed on how to calculate certain indicators. For example, when calculating the turnover rate (the number of dismissed employees by the average number of employees), questions arise: whether to take the average or the average number of employees, whether to take into account only voluntary dismissals or all dismissals.

When the methodology is not harmonized, difficulties arise when comparing data between departments within a company, with data for previous periods if the calculation methodology has changed, and with the indicators of other companies if they think differently.

The third group - lack of competencies.

The competencies required for HR-analytics include two groups of skills:

If a company is focused on data-driven decision making - this is already a good start for an HR analytics system. To ensure high quality data, it is recommended to:

1. think about the data architecture for specific goals and objectives;
2. create a single data source;
3. automate data collection;
4. implement regular quality control and data audits;
5. develop a company-wide culture of working with data.

Questions and Answers (FAQ)

What are the different types of HR metrics?

There are two main types of HR metrics. Strategic metrics are directly related to business results - they show the impact on revenue (labor productivity, staffing) or profit (share of FTE in revenue, cost per employee). Operational metrics help track whether we are on track to achieve strategic goals - for example, for a staffing goal, this could be job closing rate, recruitment funnel conversion, onboarding rates.

How often should HR metrics be tracked?

The frequency of tracking depends on the type of metrics. Operational metrics require constant monitoring, as they allow you to identify problems and adjust processes in a timely manner. For example, if the turnover rate is high, it is important to monitor the recruitment funnel, the speed of closing vacancies and the results of adaptation on a daily basis. Strategic metrics are usually analyzed less frequently (annually, quarterly), as they show long-term results and trends.

What are the most common mistakes made when using HR metrics?

The main mistakes are related to three aspects. First, data problems - when data is stored in different systems, is not harmonized with each other or contains errors due to human error. Secondly, methodological problems - when a single methodology for calculating indicators is not agreed upon, which makes it impossible to make a correct comparison. Third, incorrect interpretation of metrics - when indicators are analyzed in isolation from business objectives or are not translated into financial terms when dialoguing with the business.