Jen DuBois By: Jen DuBois

How to Build Data-Driven Recruitment and Retention Strategies

We recently hosted a webinar with our partner, Pavestep, a performance management company, to discuss why data-driven recruitment and retention strategies are important in today’s world. We also discussed methods and metrics for being more data-driven in recruitment and retention efforts.

Watch our 40-minute webinar on data-driven recruitment and retention strategies, which includes a May the 4th message from a galaxy far far away.

If you are curious and have 40 minutes, watch the entire webinar here at your convenience. Or, click on the image to the right to access the video.

Short on time? Following is a summary of the highlights and key takeaways from our webinar on data-driven recruitment and retention strategies (5-minute read).

 

 

 

 

 

 


Data-Driven Recruitment Strategies

Quanthub’s CEO, Matt Cowell covered several points regarding what it means to be “data-driven” in recruitment efforts.

What does it mean to be “data-driven”?

The term “data-driven” sometimes engenders angst in HR leaders and recruiters because it encompasses a broad spectrum of operations and approaches.  Being “data-driven” simply means moving from a more intuition-based decision-making approach to leveraging data in the decision-making process.

Being data-driven does not, however, mean throwing out all intuition or gut feel.  Experience is important in a variety of situations and has value.  So data-driven recruitment is not about constantly using the data to tell you what to do and who to hire. It’s more about coupling data with intuition, which leads to better recruitment decisions.

4 Types of Analytics

           Recruitment teams should try to move towards diagnostic analytics.

There are 4 types of analytics, which in order of complexity and value are: descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.

Many organizations are stuck in the descriptive category of recruitment data and analytics.

The downside to this type of analytics is that recruiters only get a very high-level view of what’s happening with recruitment and hiring that doesn’t inform the organization of why certain things are or are not happening.

Descriptive analytics also doesn’t help predict future outcomes of certain recruitment decisions or make recommendations for what to do to improve recruitment processes.

So organizations should start by trying to move more into diagnostic analytics as a first step to becoming more data-driven in their recruitment efforts.

Shifting to Value-Creating Metrics

Companies should look at what they currently “think” is going on, based on descriptive outputs.  For example, they may think that the quality of hires is poor and that too much time and effort is spent on the process.

They should then look to leverage analytics to move from thinking to knowing how to leverage data and analytics to create more value in the recruitment process.

For example,  recruiters and HR staff should use measurements and analytics to help address challenges such as time spent sourcing (to reduce this), optimizing the recruitment effort (i.e. by leveraging screening technology), and addressing high candidate attrition by implementing responsiveness targets and tracking those and tacking clear actions.

Know What Matters the Most and How to Measure It

One of the most important aspects of being data-driven is knowing what matters the most in recruitment. If you don’t focus measurement and data on what matters the most,  you’ll take actions that don’t improve the recruitment process.

Beyond that, it’s best to pick 3 or 4 aspects to measure and track, not 10 metrics all at once.  Choose to track the top 3-5 metrics that are aligned with what matters the most. Then take action. That’s what creates impact.

Recruitment metrics should also meet 4 criteria to enable truly data-driven decisions:

  1. Relevance to the hire – Align them to what matters the most, such as quality of hires.
  2. Comparative – They should be comparable to time periods, sites, segment, peers, etc.  An example would be comparing % of referrals vs. previous time period.
  3. Rate or ratio – Examples include applicants per day during a specific length of time.
  4. Actionable –  Choose metrics that will directly influence future behavior.

Once you’ve decided on appropriate metrics, the four-step process to leverage them is to:

  1. Measure the results
  2. Benchmark results
  3. Assess what is happening and why (diagnostics)
  4. Take action

Do this iteratively.

Addressing the #1 Problem in Recruitment – a Good/Bad Metrics Example

Finding great talent and unearthing candidates with the highest potential is the number one recruiting challenge right now.  Assuming this is the #1 problem, the image below shows a list of 9 typical metrics used to address this key problem.

These metrics are not very high-quality, however, because they’re very high level and not very actionable. They really look more like a dashboard, plain and simple, with little insight provided that will help a company find and hire great talent.

Most of these metrics do not meet the quality of metrics standards and are not very relevant.

The list of “better metrics” below demonstrates how more detailed, deep-diving metrics that meet the 4 metric quality standards can better help companies to solve the talent shortage problem.

For example,  the “sourcing effort by role” metric encourages multiple managers to collaborate on sourcing candidates, thereby improving the candidate pool and the chances of finding the right hire. It’s relevant to the talent shortage problem, it allows for comparison among roles, it can be measured as a percent of a total, and it is actionable.

These metrics are much more targeted and actionable.

The Value of Recruiting Internally (Upskilling)

Recruitment aims to fill a role that has been exited by someone. The natural inclination when this happens is for the recruitment team is to go out and hire externally.

However, mounting evidence, including several reports from the World Economic Forum, show that the key to filling roles that are hard to fill, such as data and AI-related roles, is upskilling internal employees. Essentially recruitment teams should set their sights and metrics internally to fill those roles.

In practical terms, upskilling might involve new metrics “such as percent of roles filled internally”, especially, “advanced roles filled internally”, which benefits retention as well.   The decision to upskill will also impact and compare to metrics for external hiring, such as time to fill the role and quality of hire metrics.


Data-Driven Retention Strategy

Harrison Kim from Pavestep covered the value of focusing on retention and how to create a three-pronged plan to increase retention.

Why Do We Care About Retention and Turnover?

In a word – costs.  High costs in fact.  The cost of turnover includes lost productivity (before, during, and after), time/money spent on exiting and recruiting, other employees’ time backfilling resources, and reduce morale and follow-on employee turnover.

These costs total anywhere from 60% – 150% of the salary of the role to be filled. For more senior roles, the costs can go as high as 400%.

According to Pavestep, annual turnover can cost as much as 15% of profit.

 

Studies show that roughly 77% of turnover is preventable.  So focusing on retention can have a real impact on business and its bottom line!

Three-Part Plan of Attack for Increasing Retention

Harrison suggested a three-part approach for analyzing and correcting retention issues using data.

1. Identify and prioritize core areas

Break down your organization’s retention rate into critical areas to analyze. The related data will help you identify which areas to focus on to increase retention.

You can’t just look at your retention rate and know what’s happening. You have to break it down and look at retention by function, demographics, performance, tenure, location, and other factors.  Prioritize your retention efforts according to what you find.

2. Analyze the root causes of turnover

Once you identify areas that have retention problems, you want to identify the biggest drivers of turnover.

There are 5 key drivers of turnover:

  1. Alignment Only 14% of workers who understand the company strategy and goals.
  2. Development >70% of high-risk employees say they’ll be forced to leave to advance their careers due to lack of skill development opportunities.
  3. Feedback and RecognitionEmployees whose managers consistently acknowledge them for good work are 5x more likely to stay.
  4. Relationship Close friendships at work can increase employee engagement by 2x.
  5. Compensation 49% of employed adults feel they must switch companies to obtain any meaningful change in compensation.

Gather metric insights around alignment, development, feedback, relationships, compensation, and so forth.   Identify drivers with the biggest gaps.

3. Develop retention initiatives

Once you’ve found key gaps that are driving turnover, focus retention initiatives on those.  Some examples include:

  • Alignment – Host a company “values day”, allow for internal mobility to places where the employee is better aligned. Use data-driven placement.
  • Development – arrange mentorships with non-managers, have regular career path conversations.
  • Feedback and Recognition – Engage employees in real-time feedback processes and systems.
  • Relationship – Organize “lunch and learns”, company retreats, happy hours, etc.
  • Compensation – Create transparent salary bands, offer non-cash benefits

 

 

 

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