As experts in people analytics and management, we work closely with recruitment teams to refine their search and identify the key skills and experience needed for specific HR data expertise roles. In this case study, we share how we helped our client overcome their hiring challenges and successfully attract and hire the right data expert for their team.
As an HR professional, you know that finding the right talent is key to achieving mission success. But when it comes to people analytics, this task can be especially challenging. These are the top five chief complaints we hear from clients and colleagues regarding unsuccessful HR data job searches:
"It is hard to identify what type of data expert to search for, and what specific skills they should have."
"The recruiting process was long and expensive. In some cases, our search failed entirely, leaving us with no talent to help implement our people analytics plan."
"We had to pay far more for the talent we hired than we had planned or we feel we can afford."
"The data expert we hired is great, but it turns out they are overqualified for what we need them to do at this stage, and I think we would have been better off with someone less advanced."
"The data expert we hired was great, but they quickly left because another organization offered them a more exciting position, and a lot more money than we could offer."
Recently, a client (shared here with permission) approached us with a hiring challenge. They shared their draft of a job announcement they were planning to use to attract the right data expert for one of their organization’s recruitment teams.
The list of skills looked a lot like this:
Role: Senior Data Scientist
Required:
Advanced proficiency in Python or R
Advanced proficiency in SQL and minimum 5 years of experience applying SQL
Minimum 2 years of experience in applied analytics in HR
Bachelor’s degree in computer or data science, or similar field
Proficiency in Kubernetes
Proficiency in Apache Spark
Proficiency in JavaScript
Experience with machine learning
Experience with big data
Good to have:
Master’s degree or doctorate in computer or data science, or a similar field
At first glance, these are common skills among advanced data scientists and sound completely reasonable.
In fact, in the job description, it was also clear that this data expert’s day-to-day work would be to put together and communicate operational metrics (like time-to-hire and retention rates), and to create a survey to understand the applicant experience, which the client knew was a sticking point for their organization’s recruiting.
Although a very advanced data science skill set certainly could be useful to achieve these, it was much too high of a bar for their needs. Without changes to the required skill set, the client would be trying to recruit the equivalent of a Rocket Scientist to be a car mechanic. Yes, they’re an engineer - but an excessively advanced one for the task at hand.
If you peek back at the top five challenges above and consider how a Rocket Scientist would fare in a car mechanic’s role, you will quickly realize why this misidentification of what the organization needs will lead to all of the other issues:
If the organization doesn’t already have HR data experts, it is difficult to identify the specific type of engineering skills their project needs; it’s tempting to go after a Rocket Scientist to be sure they’ll exceed the minimum requirements
Because their skills are so specialized, Rocket Scientists are pretty rare, so finding and hiring them is a long process that is likely to fail several times.
Rocket Scientists are expensive to hire, often commanding a salary that exceeds even senior executives. If the organization is unwilling to pay that market price, the search will keep failing.
Rocket Scientists are overqualified, to say the least, for repairing a car engine and are actually likely to struggle to service the team on the level they need it. They operate and excel at a totally different level.
Rocket Scientists are likely to leave soon because they feel unfulfilled or because other organizations (NASA, SpaceX, Blue Origin) can offer them more relevant and interesting project work.
As we talked about it, the client quickly realized that the skill set they were asking for was not realistic, nor was it going to result in a successful hire in the long run.
But then what should they look for instead? Here is what we settled on:
Role: Junior Data Analyst
Required:
Proficiency in Microsoft Excel
Demonstrated ability to use data and analytics to identify and understand complex problems
Demonstrated ability to effectively communicate complex information to a variety of audiences with varying degrees of technical expertise
Strong written and verbal communication skills
Ability to work in a fluid environment with many different stakeholders and rapidly changing priorities
Good to have:
Some proficiency in SQL
Some proficiency in Python or R
Some proficiency in Tableau
Experience with applied analytics in HR
Here are the reasons why this specific job announcement was changed:
First of all, notice that most of the technical skills are no longer anywhere to be found. This data expert does not need Kubernetes, Apache/Spark or any other obscure data science tool. The technical skills that remain - SQL, Python or R, and Tableau have been moved to “Good to have”. Why? Because they would be valuable tools for the data expert to have, but are actually not necessary to execute on the goals for the position.
Notice also that specific education requirements are nowhere to be found on the list. If an applicant can demonstrate that they have strong data intuition, a record of using analytics to identify and understand complex problems, and the ability to effectively communicate the resulting complex information, should it matter if they have a “relevant” degree? In any case, applied skills are usually developed in real-world settings like jobs, internships and volunteer service. They are rarely developed while studying for a degree.
On top of that, one of the most common misconceptions about data expertise - especially in HR - is that it requires a degree in computer science, data science, or statistics. Or, worse still, a degree in mathematics! Talent with these degrees will always be more expensive to hire, and for HR, they rarely provide most of the soft skills a data expert will need to be effective.
Human resources is inherently more linked to the humanities and social science. A social scientist with analytics skills will almost always be a better fit for People Analytics than a graduate from computer science, or even data science - at least until People Analytics at an organization becomes highly advanced.
When humans are not only a part of the equation, but the central part of the equation, the appropriate technical methods of analysis are different than those used in most computer and data science settings. An understanding of human behavior is central to effective People Analytics. If you must list an education requirement, make sure political science, economics, sociology, psychology, and other social science degrees are included.
Notice that in the “required” section, only a single technical skill remains - Excel - and the rest are much softer skills. The technical skills necessary to achieve the team’s goals are actually fairly limited, and can be achieved with basic tools, but the need to operate quickly, problem solve, collaborate, and communicate are essential.
Finally, notice that the position title changed from “Senior Data Scientist” to “Junior Data Analyst”.
This title change allowed the organization to attract a wider pool of candidates with a range of experience levels. By modifying the title, the organization signaled that they were open to hiring less experienced candidates, which resulted in a larger and more diverse pool of applicants. This change also aligned the position title with the actual responsibilities and level of experience required for the job, resulting in a more accurate and efficient hiring process.
Through adjustments to the position title, technical and soft skill requirements, and educational qualifications in the job announcement, the role has been expanded to a more diverse and high-quality applicant pool. This talent will be available much faster, substantially increasing the chance of mission success. The talent attracted to this position is also more likely to be engaged in the long term, and far more affordable for the organization to hire. The modifications made to the job announcement have created a win-win scenario that is crucial for success in the client’s recruitment process.
If you are an HR executive struggling to identify, attract, and retain the right talent for your organization, we understand your pain. At Opterion, we have helped numerous clients overcome these challenges by leveraging our expertise in people analytics and HR consulting.
Are you looking to refine your job announcements and tailor your recruiting process to attract a more diverse pool of candidates with the right skills and experience? Our team at Opterion Consulting can help. Contact us today to see how we can partner with you to drive mission success. Email us at info@opterionconsulting.com or call us at +1 979-985-9714 (Americas) or +45 6168 9714 (international).
Comments