What Is Average Days Open?
Average days open is a recruiting metric. It answers one question: as of today, how long has the typical open role been open?
You take every requisition still unfilled at the end of the period. For each one, you count the days from its opened date to the period end date. Then you average those numbers. The result is the mean age of your open pipeline.
The metric goes by a few names: open requisition age, requisition aging, average age of open reqs. The label changes. The math holds. It is elapsed time on the roles you have not filled yet.
This is not the same as time to fill, and the gap between the two is where the value lives. Time to fill measures reqs that closed. It starts the clock when a req opens and stops it when a candidate accepts. A role has to get filled to enter the calculation. So the roles that never close, the ones dragging past 90 or 120 days, are invisible to it. Average days open is built for exactly those roles. It counts what is still on the board.
That is why the two metrics can tell opposite stories at the same time. Your time to fill can read a healthy 40 days while a stack of hard-to-fill roles ages quietly in the background. One number says the process is fast. The other says part of the pipeline is stuck. You need both.
Average days open has grown more useful as hiring has gotten lumpier. Skilled-trades, clinical, and technical roles can sit open for months while high-volume roles close in weeks. An average that only reflects closed reqs hides that spread. Finance and operations leaders have also started asking harder questions about the cost of an empty seat, and average days open is the input that makes those questions answerable.
The Average Days Open Formula
Average Days Open = AVG(Days Between Opened Date and Period End Date)
Here is how to run it, one open req at a time.
- Pull every requisition still open as of the period end date. Exclude anything filled, canceled, or closed before that date.
- For each open req, subtract the opened date from the period end date. That gives you the days open for that role.
- Add up the days open across all of those requisitions.
- Divide by the number of open requisitions. The result is your average days open for the period.
The variables, defined plainly:
- Opened date: the day the requisition was created or approved to hire. Pick one definition and hold to it.
- Period end date: the last day of the window you are reporting on, usually month-end or quarter-end. It is the "as of" date, not a fill date.
- Open requisition: a role that is approved and unfilled as of the period end date.
Formula Variations
A few teams adjust the calculation. Each choice changes what the number means, so the version you pick should match the question you are trying to answer.
Approved date vs. posted date. Some teams start the clock when the req is approved. Others start when the job goes live. Approved-date timing captures internal delays, like a role that sat two weeks waiting on sign-off. Posted-date timing measures only the sourcing-to-hire window. Neither is wrong. Be consistent.
Median instead of mean. A handful of roles open for 200-plus days can drag the average up and make a healthy pipeline look broken. The median tells you what the middle req looks like. Report both when your open roles vary a lot in difficulty.
Business days vs. calendar days. Calendar days is the common default and the easier one to explain to a board. Business days can make internal service-level targets feel more precise. For reporting, calendar days is usually the right call.
Segment-level averages. The single company-wide number is the least useful cut. Average days open by department, location, job family, or recruiter is where the metric earns its keep.
Worked Example
Take Ironline Components, a fictional but familiar case. A 1,600-employee, PE-backed industrial manufacturer with 11 plants across the Midwest and Southeast. Frontline and skilled-trades heavy. Their director of talent acquisition, Dana, runs a monthly recruiting review.
At the end of Q2, Dana has 18 open requisitions. Her time-to-fill dashboard reads 38 days, and it has read something close to that all year. On paper, recruiting looks fine.
Then she runs average days open on the 18 roles still on the board, and segments them.
Ten are high-volume roles: assemblers, warehouse, entry-level operators. Average age, 21 days. Healthy.
Five are experienced roles: quality engineers, plant supervisors, buyers. Average age, 76 days.
Three are skilled-trades roles: two maintenance technicians and a controls engineer, all at the Toledo plant. They opened in late January and February. As of June 30, they have been open 138, 145, and 153 days.
The math is straightforward:
(10 × 21) + (5 × 76) + (138 + 145 + 153) = 1,026 total days open
1,026 ÷ 18 = 57 days average
Blended average days open comes to 57 days. That is 19 days higher than her time to fill, and the reason is sitting in those three Toledo reqs. They will not show up in time to fill until they close, and they are not closing.
Now the number does something. The 57-day figure is the symptom. The segmentation is the diagnosis. Dana can see her problem is not recruiting speed in general. It is three skilled-trades roles at one plant that have aged past 130 days while a maintenance line ran short through Q2. That is specific, and it is fixable. She can escalate the Toledo reqs, bring in a specialty sourcing partner, or revisit the pay band, and she can defend the ask with the number. The blended average alone would have buried all of that. Time to fill hid it completely.
What Data Do You Need to Calculate Average Days Open?
Three fields, pulled from your applicant tracking system.
- Opened date for each requisition. The day the req was approved or posted. This is your start point, so its definition has to be clean and applied the same way every time. Requisitions with a missing or wrong opened date will skew the average.
- Requisition status as of the period end date. You need to know which reqs were still open on that date, not which are open right now. Point-in-time status is the part teams most often get wrong. If your ATS only stores current status, you cannot rebuild last quarter's number accurately.
- Period end date. The "as of" date you are measuring against. Fixed, not floating.
A handful of data-quality issues show up again and again. Reqs left open in the ATS after the role was filled or abandoned inflate the average with phantom age. Bulk-loaded reqs from an acquisition can all carry the same artificial opened date. Evergreen requisitions, the always-on postings for high-turnover roles, will read as ancient if you include them, so most teams exclude or flag them. Reopened reqs raise a definitional question: does the clock restart, or keep running? Decide, write it down, and apply it the same way every period.
Why HR Leaders Need to Track Average Days Open
A counterweight to time to fill's blind spot. This is the core reason. A filled-only metric rewards you for the reqs you close and stays silent on the ones you cannot. Average days open is the counterweight. It keeps the stuck roles visible until they get filled, so nothing quietly ages off your radar.
A number for vacancy cost. Every day a role stays open carries a price: lost output, overtime to cover the gap, delayed projects, revenue the seat would have produced. Industry estimates commonly put the cost of a vacant professional role between $4,000 and $10,000 per month. Multiply a realistic daily cost by your average days open and your open req count, and you have a defensible vacancy-cost figure for finance. Longer average days open means a bigger bill.
An honest read on recruiting capacity. When average days open climbs across the board, it is often a capacity signal, not a sourcing one. Reqs age when recruiters are stretched too thin to work them. Rising average days open next to a rising req load per recruiter is a case for adding talent-acquisition capacity, and now you can show it with data instead of arguing from feel.
Sharper board and sponsor reporting. Operating partners and boards want to know whether hiring is keeping pace with the plan. "Our time to fill is 40 days" answers a narrower question than they are asking. "Our average days open is 57 days and climbing in skilled trades" tells them where the plan is at risk. For PE-backed companies, that link between open roles and the value-creation plan is the conversation worth having.
An early warning on backfill pressure. When turnover spikes, open reqs pile up and age before recruiting catches up. Average days open rises before the staffing gap fully shows in headcount. Watched monthly, it is a leading indicator that backfill demand is outrunning recruiting throughput.
Benchmarks and Interpretation
There is no single national benchmark for average days open, partly because so few teams measure open reqs instead of filled ones. The closest reference point is time to fill, which runs about 40 to 44 days on average across US roles, with healthcare closer to 30 and engineering closer to 55 to 60. Use that as a floor, not a target. Average days open almost always runs higher than time to fill, because it carries the aging roles that time to fill leaves out.
A more useful frame is age buckets. Sort your open reqs into ranges and watch the distribution, not just the single average:
- 0 to 30 days: healthy. Normal working age for most roles.
- 31 to 60 days: watch. Fine for hard roles, worth a second look for easy ones.
- 61 to 90 days: at risk. A common industry rule flags anything past 60 days for review.
- 90-plus days: stuck. These roles need intervention, not patience. Something in the pay, the process, or the market is broken.
The interpretation rule that matters most: your own trend beats any external number. Average days open climbing quarter over quarter in a specific job family tells you more than a benchmark ever will. Segment it by department, location, and role type, then compare each segment to its own history. A 70-day average for controls engineers may be normal for your market. A 70-day average for warehouse staff is a fire.
Common Mistakes
- Confusing average days open with time to fill. They measure different populations. Time to fill looks at reqs that closed. Average days open looks at reqs still open. Reporting one as if it were the other hides your aging roles.
- Leaving dead reqs in the count. Filled, canceled, or abandoned requisitions that were never closed in the ATS inflate the average with age that is not real. Clean the pipeline before you run the number.
- Reporting only the company-wide average. The blended figure smooths over the exact roles that need attention. Without segmentation by role type and location, the metric is a thermometer with no diagnosis.
- Including evergreen reqs without flagging them. Always-on postings for high-turnover roles will read as hundreds of days old and distort everything else. Exclude them or report them on a separate line.
- Using current status instead of point-in-time status. Measuring who is open today to describe last quarter gives you the wrong number. You need status as of the period end date.
- Chasing the average down at all costs. A low average days open can mean fast hiring. It can also mean you are closing the easy roles and canceling the hard ones. Read it next to quality of hire and offer acceptance, not on its own.
Related Metrics
- Time to fill. The filled-req counterpart. Average days open covers what time to fill leaves out, so the two belong on the same dashboard.
- Time to hire. Measures the candidate-side window from application to acceptance. Useful for candidate experience, narrower than average days open.
- Current openings. The count of roles open right now. Average days open tells you how old that count is.
- Opened positions. New reqs created in a period. Rising opened positions alongside rising average days open means demand is outpacing recruiting.
- Filled positions. Roles closed with a hire. The relief valve on your open pipeline.
- Offer acceptance rate. A low acceptance rate is a common reason reqs age. Declined offers reset the clock.
- Cost of turnover. Turnover drives backfill reqs, which drive average days open. The two connect vacancy time back to retention.