Anything brand new is appealing because it’s clean, untouched, and uncorrupted. Within the last year we’ve all purchased something new, and have felt the “newness” of the item fade with each use. A new system can be viewed the same way. You start out with a clean system, but once it is put in operation, you face the potential of having missing, invalid, or even corrupted data. Trying to keep the system “clean” or maintained becomes a challenge (and usually ends up as someone’s full-time job). Let’s see how this applies to the issue of data integrity in applicant tracking systems. Data integrity is defined in many different ways in a tech encyclopedia, but generally refers to preventing the corruption of data in a system (whether by erasure, manipulation, or alteration). However, I would extend this definition for the everyday recruiting system user to include preventing the input of invalid data or the lack of input – basically your “garbage in = garbage out” axiom. Below, I’ve outlined some specific steps you can take to encourage recruiters to enter data properly and help you preserve data integrity. Relevance for Recruiting Let’s say you manage a large recruiting operation and you’ve just purchased and implemented a new system. Soon you have countless pairs of hands tapping data into your system. With the passing of each day, your data, whether good or bad, begins to multiply exponentially. You hope that everyone is following the system usage guidelines and with high expectations, you print your first system report. Elation quickly diminishes when you stare at a page that looks like statistical Swiss cheese. “Where’s all the data?” you may ask, or “Why don’t these numbers look like what the recruiters used to show me on their Excel spreadsheets?” As a recruiter, you may have always viewed data input and upkeep as a necessary evil – a virtual ball and chain that eats up valuable time. But let’s look at some of the issues for recruiters: How about accurately tracking stats for that bonus that’s dependent upon the number of developers you hire each quarter? What about when legal comes knocking on your door asking you to recreate a year’s worth of applicant flow that you didn’t bother putting in the system? Now how much time are you wasting? Not to mention, being able to track your efficiencies with source usage, sharing candidates, and saving redundant phone calls! Strategic HR The importance of data integrity not only touches the recruiting organization but also corporate HR and hiring managers trying to balance head count issues. In some cases it flows all the way to the top, where CEOs wait to see reports that will help them leverage human capital management and business growth. Data integrity issues may be the drier side of recruiting, but if managed well, can greatly contribute to a recruiting organization’s success. The clearest and biggest benefit in focusing effort on data integrity is reporting and tracking metrics that lead to key decision making including:
- Critical reports such as EEO reporting for US companies
- Applicant flow validation and pipeline analysis
- Identifying time lags in the recruiting process
- Identifying utilization problems with users
- Identifying key trends through source tracking that will affect advertising expenditures
When I managed technology for large groups of recruiters, my team kept a “worst offenders” list of recruiters who were always failing to put data in the system or putting incorrect data in the system. Using various systems over the years, I’ve found some of the worst offense areas for input included:
- Applicant flow tracking. Have you ever seen those phantom records where applicants mysteriously jump from no status to “hired” – with no record of any screens, interviews, etc.? What exactly happened leading up to the hire? This is what the OFCCP would like to know.
- Sources of applicants. Not just general source, like Internet, but specific source like monster.com. And by the way, did you “mine” them on the database or did they come through a posting?
- EEO data for U.S. candidates. What percentage of your tracked applicants is of “unknown” race and sex?
- Interview or Screen results. Some people like reinventing the wheel over and over again. You need to share and recycle data so recruiters don’t repeat efforts.
- Reasons for rejecting an applicant. Internal HR loves this one.
Why Your Data Went Awry There are several main causes of data deterioration after an implementation and beyond:
Article Continues Below
- Training doesn’t “sink in” well enough and is not continual enough to have all users entering all information perfectly in every part of the application. I once had a user who went through two formal training sessions and several phone-training sessions. After about 30 days on the new system she started to complain that her system wasn’t working. I came to discover that she had never logged onto the “live” system, but was still in the “training” system…posting jobs to nowhere!
- Training did not address true “day in the life” simulations, so recruiters didn’t relate data input to their real life recruiting tasks. Thus, the benefits of the system weren’t clearly presented so recruiters were not motivated to put in their data.
- Users focus on areas they understand and give immediate effective gratification (like posting a job to the corporate career site), and forget about inputting data in other sections (like logging reasons for rejecting a candidate). Most data input responsibilities are looked upon as a necessary evil for the recruiter and if there is not a perceived timesaving for using the system, recruiters will cling to pre-implementation processes.
How to Tighten Up On Data To maximize not only the ROI for a new system, but give the recruiters easier usage guidelines, here are a few ideas to control data input for consistency as much as possible:
- Make as many input fields of data required as possible. This may not be appropriate for all data, but will give no options to the user.
- Use set menus of choices as often as possible over open text fields. Otherwise, you run into “10 ways to spell M.I.T.”
- When choosing a system, try to watch for areas where the system helps with input by preventing certain steps to continue until data is filled in – like creating a new requisition without an EEO category or hiring a candidate without a valid source.
- Establish an airtight input process and user guide for the way your organization uses the system and focus frequent and direct communication to the user community on “gap” data areas that cause problems.
- Give the gift of a data “audit” to your recruiters. Sometimes, recruiters in their busy daily tasks don’t realize that their accumulated data input habits can add up to small or large holes in reports. Supply recruiters with weekly or monthly “audit” reports customized to their activity that clearly display missing data on their reqs. and candidates. Most recruiters will be thankful for this information.
- Provide monetary and/or non-monetary incentives and praise for users who consistently input data correctly. In past experiences, I worked with recruiting managers to give these users special recognition, whether it was one-on-one positive feedback, verbal acknowledgement at a meeting, or a “perk” like attending a special conference.
- Look for a system that has fully integrated and automated on-line EEO tracking on the company Web site and prompts both users and recruiters when this information is missing.
- Make data input and system utilization part of the recruiter’s measurable job objectives and review the recruiter accordingly at performance appraisal time.
- Identify users that are “data-input challenged” and assign “superusers” or system administrators to give these users more attention, tutoring, checkpoint accountability and frequent data reviews.
- Build in wizards that don’t leave a lot of options except “Back” and “Next” commands to enable certain, more complex data entry areas in the application.
If you have no data integrity issues with your current system, congratulations, you are in great shape! If you do, run some reports in your current system and identify the top areas where data input is either missing, erroneous or inconsistent. Establish guidelines on these areas and provide key communications and training to users to help improve your data, and ultimately your recruiting decisions. <*SPONSORMESSAGE*>