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TDWI Upside - Where Data Means Business

Breaking Through Barriers in Traditional Hiring and Recruiting: 3 Stories

Three examples show how you can find candidates to fill your analyst positions by changing where and how you look.

We are currently in a tight labor market, which traditionally makes hiring and recruiting seem more difficult. The general assumption is that when unemployment is low, job postings tend to attract fewer applicants and the qualified applicants are more difficult to land in the open seat.

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The good news is that business intelligence and analytics jobs are perceived as move-up jobs by many candidates in analyst and technician roles due to the higher pay and skill level. Those candidates may not have all the technical skills and experience needed, but they can easily be trained and mentored into data engineering roles if they have the right interest and aptitude.

How can you recognize the best candidates among those less-qualified applicants? What hiring methods can lower the risk of hiring a less-qualified candidate who will require significant training and mentoring investments?

Here are three examples from my personal experience that show how we found non-traditional candidates with high potential.

Story #1: Finding the Hidden Data Geek

Victoria was working for a small family business doing purchasing and inventory control. She had a business degree and significant business experience, but no formal training in data engineering or SQL-based tools. When opportunities arose, though, Victoria began to use Microsoft Access to improve her manual Excel processes. She experimented with table designs and queries, then built forms and reports to automate steps.

Small projects led to larger projects and Victoria began to demonstrate to herself and to her co-workers that she had an emerging talent for database projects. One of her friends recommended her to us a potential candidate for a BI Analyst position.

Victoria didn't meet the basic requirements for the job in terms of a technical degree or specific BI tool and project experience, but we saw her aptitude and interest level. She was offered a salary corresponding to her experience level, then we worked hard to give her the biggest raises possible as her skills and value began to shine in her new role.

Story #2: Tech Experimenter + Amateur Graphic Designer = Great Viz Builder

Andrew had worked for almost seven years in tech support roles. He wanted to advance in his career but faced a major obstacle -- he had only a high school degree. While working in tech support he began to show aptitude building reports and presenting data, then worked his way into a reporting role within the same company.

We ran into Andrew as customers of his company and were impressed with his work. His flair for report design was obvious and he was able to show us an impressive portfolio of designs he had completed for reporting.

When we had a job opening, we reached out to Andrew and later hired him. With some additional SQL training and resources, Andrew became our top dashboard and report builder, and he consistently impressed our staff and clients.

Story #3: Test Run that Didn't Work Out (But Ended Happily)

Carlos was an internal referral in the company. He had been working for three years in tech support and was looking for a way to advance his career. Realizing the pay increase he could get in an IT role, he had enrolled in a computer science degree program and began looking inside the company for open positions. When we met him, he had a lot of enthusiasm but no relevant work experience to show his aptitude with data engineering skills. With little to go on other than interest, we decided to do once-a-week trial/training sessions for a couple of months.

I began by giving him access to a development database, providing some basic SQL instruction, and giving him some challenges to write queries. The first week went great. Enthusiasm was high, results were great, and we continued the one-hour sessions. By the third week things were starting to slow down. His energy level was dropping as the SQL concepts became more difficult and the challenges began to feel like math story problems that he used to dread as a kid.

After two more weeks, Carlos had made up his mind to try a different avenue. The good news is that we all parted ways on good terms and on a positive note. Carlos had gained some insight into his interests and aptitudes and we had avoided making a hiring mistake. He eventually found a system administrator role in the company that better fit his interests.

Best Practices

Based on my experience in these three situations -- and others -- here are some of the best practices I can offer for finding good candidates for your team:

  • Be open to resumes; filtering using keywords will eliminate some great candidates
  • Non-traditional candidates should be able to demonstrate a portfolio of related work
  • Internal candidates can be involved in real work experiences to allow both sides to evaluate the fit
  • Referrals are the best way to identify non-traditional candidates with high potential.
  • Managers should be constantly building a pipeline for diverse candidates to move beyond basic job postings and resume sorting.

If you are frustrated that you are not finding candidates for your job openings, it's time to think out of the box and look in new locations and channels. You can lower the risk of hiring non-traditional candidates by looking at their portfolio of work products and self-initiated data projects. These candidates may require more investment in terms of training and mentoring, but they can bring a collection of new perspectives and energy to your team.

About the Author

Stan Pugsley is an independent data warehouse and analytics consultant based in Salt Lake City, UT. He is also an Assistant Professor of Information Systems at the University of Utah Eccles School of Business. You can reach the author via email.

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