Our team has been filling contract and full-time analytics positions for the past 7+ years. We have worked on thousands of analytics searches and have found 5 things that cause jobs to stay open for far too long. They are:
1. Wish Lists Instead of Requirements Lists
The analytics director at XYZ corp. draws on the white board where they want to be in a year. Then they take stock of their tools, processes and talent and find many gaps. They have limited budget for talent and only 1 open headcount. So they take the list of talent gaps and copy/paste them as “requirements” for their new position. Their goal is to hire whoever checks off as many boxes as possible. This approach is destined to fail for several reasons:
- Analytics professionals look at this job description and immediately conclude two things
- Whoever wrote this job description has no idea about the market for analytics talent because this person does not exist
- Nobody could possibly be successful in a role that has this many requirements and responsibilities
- Each stakeholder that participates in the interview process considers his requirements the most important. As a result, the candidate has completely different interview experiences with each interviewer. This is a huge red flag for candidates.
- It is impossible for stakeholders to agree on a candidate because they are all looking at different qualifications / criteria.
The result is that they burn through well-qualified candidates while damaging their brand in the community. They eventually realize what they are doing wrong, but by then everyone in their geographic market has either been contacted for the role, interviewed, or heard a horror story about the interview process.
2. Suzie in HR
Suzie is working on 32 open positions for her business unit. She has openings for accounting clerks, secretaries, financial analysts, mailroom supervisors and web analysts. She has no idea what a web analyst does, but she has a call with the hiring manager, who explains what buzzwords to look for and how to evaluate candidates.
Suzie posts the job all over the Internet and waits for applicants. She gets three kinds of responses:
- The usual suspects: the same people that are ALWAYS on the market. Some are crazy, some are incompetent and some are both. They have all the right buzzwords on their resumes and they meet all of the qualifications on paper, so they are invited for interviews.
- Hidden gems: Suzie will probably receive 100+ responses to her many postings. In the deluge there will be 1 or 2 that are hidden gems. They may not have the right buzzwords on their resumes and they will not make it through Suzie’s checklist, but given the chance to speak with the hiring manager they would be considered strong candidates. These people are usually passed over.
- Everyone else: An avalanche of technical and quantitative people across the analytics spectrum. Some may be relevant for other opportunities on the team, but she doesn’t understand what they do and doesn’t care. She has a checklist and a job to fill.
Three months pass in this way. Suzie forwards the usual suspects and an occasional candidate to the hiring manager, but nobody gets hired. Desperation starts to build and the hiring manager says, “I can’t take it anymore. We have to get outside help. Call those guys from IQ Workforce. They claim to be experts in this space. I don’t care if we have to pay a fee – we NEED these positions filled.”
Now put yourself in Suzie’s shoes. Her job is to fill jobs. Her performance evaluation will be based on her statistics of jobs filled vs. those filled by agencies. Her bonus, her promotion and even her continued employment at the company depend on the perception that she is able to fill her jobs.
Is this the best person to manage the agency relationship? If the agency fills the job she will successfully prove that SHE was the problem – especially if they do so quickly and easily. She is “Freakonomically” motivated to make sure that the agency does not succeed.
Many people will say, “Not MY Suzie. She really cares about the business and would never put CYA over the good of the company.” Yes, YOUR Suzie.
3. Candidates Dying on the Vine
The clock starts the moment a candidate is scheduled for their first phone interview. If they are actively interviewing they could be involved in as many as 3-5 other processes. Any more than 3 rounds of interviews for analyst-level candidates is too much. Any more than 4 rounds is too much for managers & directors. This includes the phone screen, so don’t waste it by letting Suzie do the screening.
In addition to too many rounds of interviews, companies will often let too much time pass between rounds. A basic rule of thumb is to never let more than a week pass between rounds. This will keep the momentum moving forward and keep candidates engaged. Otherwise they will lose interest and move on to other opportunities. At that point the search has to be restarted with a depleted pool of candidates.
4. Sell the job.
Most people don’t realize how many job offers are turned down by analytics candidates. They get very caught up in the evaluation of the candidate (understandably) during the interview process and they forget to sell their jobs. We recommend that each interviewer take 3-minutes at the end of their meeting to sell the job back to the candidate. Explain why they think the role addresses whatever is motivating the candidate. It is a small investment that can make their close rate skyrocket.
When offers are rejected companies will usually have to start the process all over again with a depleted candidate pool.
If a company is located in a small or mid-sized city there may be only a handful of people locally that qualify for the job. If they can’t get one, they have 3 options:
- Wait for one to become available
- Try to relocate someone to their city
- Consider virtual office / remote candidates
Considering how important a lot of the open analytics roles are, it is amazing how reluctant many companies are to consider relo or virtual candidates.