People in other departments can’t get the data analytics they need

When departments can’t get the data analytics support they need, it can hinder progress for your company and risk your competitive edge. This lack of support can arise when people in other departments don’t know what types of data support they need. As a result, the recruiters who support them can’t recruit data scientists for the right roles or have to find qualified talent in a short time.

Situations like this occur frequently, creating challenges for their recruiting partners. Here are some challenges analytics recruiters frequently face.

HR Lacks Quality Input to Get Other Departments the Data Science Support They Need

As a recruiter, you find talent to meet particular skills and job requirements. As part of the HR department, you support the entire company. But, often recruiters lack the details needed to see where a data analyst belongs. As a result, supporting the company becomes difficult.

Acquiring talent to solve problems is one measure of recruiters’ success. But, often a recruiter can’t get the right talent to solve the analytics needs of a department. This happens because the recruiter doesn’t have enough details about the problem…or clarity on what the hiring manager really needs.

Why Recruiters Can’t Fulfill the Need for Data Analytics Support

The world of data science and analytics has many specialties, languages, and tools. Many times organizations struggle to understand the details about the skills needed to execute with these capabilities. This lack of understanding creates resistance, misalignment, confusion, and anxiety in the hiring process when looking for data talent.

A NewVantage Partners survey said that 85% of firms desire to create a data-driven culture. But 48% of those firms surveyed failed in their pursuit of a data-driven culture. The study showed three obstacles to building this kind of culture. Some of the barriers were:

• Lack of organizational alignment—4.6 percent
• Lack of middle management adoption and understanding—41 percent
• Business resistance or lack of understanding—41 percent

Furthermore, companies may lack the tools for working with a distributed data analytics team. These elements can confuse a recruiter looking to understand what skills the company really needs.

Lack of Organizational Alignment
Amidst a myriad of technologies, many companies lack the particular software or tools needed for the type of analysis a company needs. Or, the company’s employees might not know how to use the software or tools at the level required to pursue a particular strategy.

Lack of Understanding
Sometimes middle managers are resistant to the recommendations coming from an IT or Data department. Hiring managers may not include data analytical skills in non-IT job postings, slowing a company’s digital transformation. This lack of alignment with the organization’s vision can cause tension and confusion when trying to fill a vacant position.

The Challenge of Recruiting Data Analytics Talent
Budget limitations are the biggest challenge of recruiting data analytics talent and can impact both large and small organizations. These limitations make recruiting and hiring data scientists challenging. It becomes even more challenging if you need a data scientist solely for a particular project or short time period. Recruiters need to find data specialists to complement existing talent while staying within budget…and are expected to do so in a short time period.

Retaining Data Analytics Talent
The supply of data scientists and other analytics professionals is small but the demand is significant. That means data science professionals can demand high compensation for their skills. The Bureau of Labor Statistics states that the median salary of a data science professional is about $120,000. And they predicted job availability to grow 19% through 2020.

Although you recruit and hire a data science professional, retaining them is difficult. The Financial Times reported that data professionals spend 1 to 2 hours a week job hunting. So why are data professionals job hunting? Here are a couple of reasons.

Relying Too Much on One Data Science Professional

Too often, recruiters and executives don’t understand the differences among different data science and other analytics roles. People at the company assume a data scientist will be able and willing to do it all. There’s no appreciation when writing the job description to the real distinctions among data engineering, database management, programming/ query writing, analytics/ statistics and data reporting/ visualization.

Not Setting Expectations of Work

This lack of appreciation manifests itself into the day-to-day work. Let’s say you hire a data wrangler, but the manager has the employee creating data visualization reports for a weekly board meeting. When this happens, data professionals likely will start looking for another job. It’s important that hiring managers are clear about the expectations of the work and criteria for success in the role before someone is hired.

Data scientists aren’t the only ones expected to be miracle workers. Recruiters must find qualified talent for ill-defined data analytics work.

Chisel Analytics can help you find the right talent for project work or permanent roles. As a result, you meet the Data Analytics demands and make your life easier.