data in recruitment

The traditional recruitment process heavily relies on intuition and gut feeling more than on data. This is how it is now and how it has been for decades, but it raises a question. Why is it that a hiring method that served us well for so long only resolves in steadily increasing employee turnover rate?

The truth is that there can be many reasons for employees not being loyal, and no recruitment process is perfect. On the other hand, a high cost comes with a bad hire, which is even more crucial to understand if you’re a starting business.

Startups are known for hustling, and a lot of decisions need to be made quickly, which often resolves in hiring a person based on intuition, and that person ends up leaving the company within the first month. Poor hires affect the productivity and costs related to recruitment and training.

The cost of a bad hire

Like any other company in the world, you’ve likely made a wrong hiring decision, and that is alright. No hiring process is perfect, but a mistake like this is a costly one.

According to the US Department of Labor, a bad hire’s cost is around 30% of the employee’s wages for the first year. Moreover, it’s not only about finances. A study showed that 34% of CFOs said they spent 17% of their time supervising poorly-performing employees. The time allocated to oversee an employee that ends up leaving translates into missed opportunities in other areas of your business.

Let’s put some real numbers in this scenario. As a starting business, the cost of bad hire might be a bit lower than 33%, and you might be more agile than a big corporation to make up for the losses. Some companies allocate 15% of employees’ annual salary as a turnover cost when they voluntarily leave the company. 

Let’s imagine that you hired a sales rep for a senior-level position. Copenhagen’s average salary level for a senior sales rep is around 596,142 DKK per year. If the sales rep leaves, this company would lose 89,421 DKK. 

There are some hidden costs for you to be aware of beyond the sales reps salary. 

Onboarding costs: When onboarding new employees, you would typically have your senior staff from either middle- or top management taking care of the process. If your company is an early-stage startup, the team that onboards will still be part of driving revenue – when you remove them from the phone, you ought to expect a lower conversion rate, given that the leads will now have to be attributed to the other sales reps that would be less experienced. 

Leads costs: New sales reps have a ramp-up time, with an expected timeline of when the sales rep is expected to hit the quota. The first 7-14 days, you should expect to be burning of leads, in some cases, up to a month before the new sales rep gets a hold of it. Therefore you want to allocate leads/prospects with the lowest lead value to ensure you don’t burn off too much potential revenue. How much do you pay per lead/prospect? How many leads are you prepared to write off? 

You can ask yourself if you could have used almost 90 000 DKK in a different way to scale your business. 

“When was the last time that you took an increasingly important decision, on a strategic level for your business, solely based on a gut feeling?”


Why the data-driven recruitment process isn’t so common

The difference between a top performer and a bad hire is the difference between decisions based solely on a gut feeling and decisions based on data. The challenging part about data-driven recruitment is the tedious work and inadequate solutions available on the market. 

For instance, ATS is an excellent solution for sorting through applications, tracking candidates through the hiring process, and getting data like time-to-fill and cost-of-hire. However, the current solutions are very limited in the correct type of data that can make the hiring successful. In that case, you most likely need to use various sources, models, and spreadsheets to cover all your needs. It’s no wonder that most of the hiring processes are based on gut feeling if you can’t get the data in one source that is easy to analyze.

On the other hand, it’s still more predictable than relying on guesswork.

Start with implementing a data-driven strategy.

Like everything in business, it all starts with setting up goals and the KPIs to evaluate whether the strategy was successful.

The initial step consists of selecting the correct data and metrics to measure your hiring process’s effectiveness. This can split into two folders: overall effectiveness and ICP. We’ve covered the importance of setting up the ICP in our previous article, but you need to define who you want to hire to summarize it.

From a more holistic point of view, there are common KPIs that recruiters are looking at:

Cost per hire

Time to hire

Ramp-up time

Source of hire

Application conversion rates

Job offer acceptance rates

There might be some other KPIs that are relevant to your business and your specific market needs. If you’re unsure what should be included, have a meeting with senior leaders in a department where you want to fill in the position and ask them which data they care most about.

The next step is to collect the data efficiently. As we mentioned earlier, the current recruitment tools are not perfect, but we can still use them to save us time. Your current ATS may already have some reporting capabilities that can make your life easier. If you’re using multiple spreadsheets, you can use some automation solutions to make the connections and save your time on repeating tasks. 

The last step is to act on the data.

It’s essential to know how to iterate your hiring process based on the data you’ve collected. For example, your data might show that your hiring process takes longer than your industry average benchmark. In that scenario, you can look at your:

Sourcing: You might be well acquainted with recruiting through LinkedIn, but you can consider other channels, depending on your ideal candidate’s demographics and behavior.

Screening: You can include qualifying questions on your job application form that should be easy for you to measure.

Interviews: Interviews typically take around 30 – 45 minutes. Make this time count by creating a plan that will make it easier to evaluate the right fit.

Job offers: You should consider putting some effort into writing a winning job offer letter that would push the candidate to accept it.

A common challenge for startups is a low job offer acceptance rate. Finding the best candidate only to turn it down results in higher costs and remaining vacant positions. If more candidates are rejecting your job offer, you might consider a few corrections:

Write a competitive job offer: Based on your data, highlight the benefits and perks that differentiate you from other companies.

Capture a candidate’s interest in the position early on: Make sure you communicate effectively with candidates. Find out what motivates them, what their concerns are, are there any barriers preventing them from accepting your offer, and can you deal with them?

Ensure their experience is pleasant: Make sure your team politely treats the candidates, get back to them on time, make them feel comfortable during interviews etc.

You need to realize that knowing the data has its limitations. You can use different data collection methods, but it’s a person interpreting them in the end. The data on its self can’t make the decision and act upon it, and therefore, all decisions are made and executed by people. Depending on how you set up the data collection process, it might not always be objective. For instance, if you made a hiring assignment, and it’s a person evaluating it, there is a risk of potential bias or misinterpretation based on human error. 

Key takeaway

Basing your hiring decisions on intuition and gut feeling more often results in bad hiring decisions that can significantly increase your costs. While it’s understandable that you need to make quick decisions as a starting business, it’s not sustainable to keep hiring people only for them to leave within the first few months.

Data-driven recruitment is a concept that your recruiters or HR teams can benefit from to make the right hiring decision. Find the correct type of data and metrics that are relevant for your business and start tracking them. Once you already have the data, it’s essential to know how to interpret it and act upon it.

Set your recruitment team for success.

As a starting business that considers using data to some extent, you’re probably using spreadsheets and generating reports from various sources. It can be a long process, but it will enable you to make better-informed decisions. However, to make your life easier, consider investing in new technology with sophisticated analytical functions.

Are you not sure that such a tool exists? Signup for our newsletter and see what we’ve been up to regarding recruitment systems. You don’t want to miss out on this!

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