Optimize and streamline: Structure workflows for data-driven outcomes

Hiring team planning meeting

3 mins, 40 secs read time

Create the foundation for workflows that surface data to measure success

Measuring your hiring efforts relies on the data you gather throughout your entire recruiting process. Having structured workflows will make it easier to report on performance metrics, keep stakeholders informed and maintain data integrity. Optimizing your data quality can be a huge lift. Here’s some guidance to help you get started.

Use recruiting KPIs

Before you optimize your data quality, you’ll want to define which recruiting metrics you plan to track. To streamline this process, choose metrics that will act as a signal of behind-the-scenes changes, successes or areas of weakness. These metrics should also be meaningful, regardless of how your recruiting team is set up. Here at Greenhouse, for example, we focus on these five KPIs:

  1. Qualified candidates per opening – Number of applicants who had an initial screen interview, per job opening
  2. Candidate survey results – Feedback from candidates indicating interview experience
  3. Source-to-close – How quickly candidates move through your recruiting and interview process
  4. Offer acceptance rate – The percentage of offers extended to candidates that are accepted
  5. Hires-to-goal – How well you are meeting your hiring objectives

All of these metrics are aimed at making sure you are building a process that leads to great hires. You’ll know your process is highly effective when you have a robust pipeline, a great candidate experience and a smooth-running process.

Want to learn more? Greenhouse’s Five recruiting KPIs eBook walks you through how to measure and interpret these KPIs for a more optimized process.

Assess your current data quality

Now that you’ve determined your recruiting KPIs, take a look at your existing data to determine whether you're collecting the data points you need for accurate measurement. Check how your data quality affects your ability to:

  • Determine which sources work best for your roles
  • Understand why candidates leave your process, whether you rejected them or they rejected you
  • Re-engage candidates using Greenhouse as a database
  • Keep stakeholders informed of hiring status and past hiring trends
  • Stay on top of late-stage candidate details
  • Plan timelines and resources for future hiring

This helpful Data Quality Audit checklist breaks this process down even further, allowing you to review your data collection workflows by category (candidate data, job data and reporting data) so you can zoom in on which parts of your workflows need improvement.

If you’re tackling your data quality on your own, watch this data integrity webinar for additional guidance on using the data quality audit tool and creating a data integrity action plan.

Enable features and practices to improve data quality

After auditing your data, enable the tools in Greenhouse that promote good data hygiene. Making certain behaviors required (assigning a source to every candidate, for example) will help condition your teams and get them used to inputting data correctly. Equally as important is training your teams on the correct behaviors and workflows for data quality. Here’s a list of essential Greenhouse actions for data integrity. Use this as a starting point for your process maintenance.

Essential Greenhouse actions for data integrity

  • Enter every candidate under the correct job
  • Assign Source and Who Gets Credit and make required for all users
  • Assign a Recruiter and Coordinator
  • Move candidates through each stage of the job as they move through your interview process
  • Schedule interviews in the system with the correct interviewer
  • Train interviewers to completely fill out their scorecards using the unique URLs they receive through their interview invites
  • Disposition candidates with the appropriate rejection reasons and make this required for all users
  • Fill out the offer information in Greenhouse and mark candidates as hired when they accept
  • Close jobs for which you’re no longer hiring

Lastly, create a routine for reviewing your data quality. Creating a data-driven process is a lot of work and you may not get it right the first time. Arm your recruiting teams and hiring resources with the data integrity checklist. Be sure to hold them accountable for upholding good data habits for all hiring activities. To make sure your data quality is improving, start off with monthly or quarterly data quality reviews. Once you are more confident in your data, you can move to a cadence that feels right and gives you all the data you need for your recruiting metrics and hiring success.

View the Optimize and Streamline webinar series for more tips and best practices on building a more efficient hiring process.

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