How to spot delivery risk from leave in the next 2-4 weeks (Capacity checklist)
Most delivery slips don't happen because the work was hard. They happen because someone critical took leave, nobody noticed until it was too late, and the team scrambled to recover. By then, the deadline is tomorrow and your options are "work the weekend" or "tell the client we're late."
This guide gives you a simple weekly ritual: look 2-4 weeks ahead at planned leave, apply a capacity buffer, and make decisions before problems become crises.
TL;DR Answer
If you want to spot delivery risk from leave early, do one thing weekly: look 2-4 weeks ahead at planned leave + critical-role coverage, then apply a simple capacity buffer for unplanned absence and dependencies. This turns "surprise gaps" into "planned trade-offs" - change scope, move dates, or shift people before a deadline slips.
Q: Why look specifically 2-4 weeks ahead?
A: Two weeks is the typical sprint or milestone window. Four weeks captures the "next milestone after that." This range is short enough to be actionable (you can still move things) and long enough to catch problems before they become crises.
Looking only 1 week ahead is too late - your options shrink to "work harder" or "miss the deadline." Looking 6+ weeks ahead introduces too much uncertainty (plans change, people cancel leave, priorities shift).
According to the PMI Pulse of the Profession 2025, only 58% of projects meet their original deadlines. Resource availability and poor capacity planning are consistently cited as top failure factors. The 2-4 week window is where you can still intervene.
Q: What does "delivery risk from leave" actually look like?
A: It shows up in four patterns:
- Critical-role gaps: The only person who can deploy to production is on leave next Thursday.
- Stacked leave: Three engineers (out of five) are off the same week. Your team capacity drops 60%.
- Dependency collisions: Designer is off when you need final assets. PM is off during client review week.
- Over-utilization + absence: Team is already at 90% capacity. One person goes on sick leave = instant overload.
These aren't problems because people took leave. They're problems because nobody looked ahead and adjusted plans.
Q: What baseline data should we assume for unplanned absence?
A: Use these data points to set realistic capacity buffers:
ONS Data (UK, 2024):
2.0% of working hours were lost to sickness absence in 2024, totaling 148.9 million days lost. The average worker took 4.4 days off sick per year.
CIPD Survey (2025):
UK employees took an average of 9.4 days off sick in 2024, equivalent to 4.1% of working time lost. This is the highest level recorded in over a decade.
Practical buffer recommendation:
- Normal periods: Assume 5-10% capacity loss for unplanned absence
- High-risk periods (winter, post-holidays): Assume 10-20% capacity loss
Example: If your team is 10 people and 2 are on planned leave next week, don't assume you have 80% capacity. Assume 70-75% after accounting for likely sick leave or emergencies.
Q: The 2-4 week capacity checklist (copy/paste)
A: Run this weekly. It takes 15 minutes once you have the right leave management visibility.
📋 Capacity Checklist (Weekly Ritual)
- Build "who's off" view
Pull approved leave for the next 2-4 weeks into a single view (calendar or tool). - Convert leave into capacity impact
Formula:(team size - people on leave) / team size
Example: 10 people, 2 on leave = 80% capacity. Apply 5-10% buffer = 70-75% effective capacity. - Identify critical roles
Mark which roles are single points of failure (only 1 person can do X). - Flag stacked leave
Highlight weeks where 30%+ of a team or 2+ critical people are off simultaneously. - Check dependency timing
Cross-reference leave against known deadlines, handoffs, and client commitments. - Score risk
Green (safe) / Amber (watch) / Red (high risk) for each week. - Decide response
For Amber/Red weeks: cut scope, move dates, shift people, or arrange cover. - Confirm cover plan
Document who covers what. Confirm with team members. - Communicate in one place
Share the risk assessment and mitigation plan (Slack/email). - Track outcomes next week
Review what actually happened vs prediction to improve future assessments.
Q: Comparison table - common risk signals (and what to do)
A: These are the patterns that show up repeatedly:
| Signal | What it means | Fast mitigation |
|---|---|---|
| 30%+ team capacity gone one week | High risk of missed deadlines | Move non-critical work to following week; cut scope on critical work |
| Critical-role person off during milestone | Blocker with no obvious workaround | Move milestone date or train backup person now |
| Dependency chain + leave overlap | Designer off when dev needs assets | Deliver assets early or delay dev start |
| Back-to-back leave (no buffer) | Person A off week 1, Person B off week 2 | Ensure handoff is documented before Person A leaves |
| Manager + team member off same week | Decision bottleneck if blockers arise | Delegate approval authority to another manager |
Q: A simple weekly ritual to run this (15 minutes)
A: Pick Monday morning (or Friday afternoon). Run this as part of your weekly planning:
- 0-3 min: Pull leave calendar for next 2-4 weeks
- 3-6 min: Apply capacity formula + buffer
- 6-9 min: Check critical roles + dependencies
- 9-12 min: Score Green/Amber/Red
- 12-15 min: Decide mitigation (scope/date/people)
The hardest part isn't the thinking - it's remembering to do it weekly. According to Wellingtone's State of Project Management research, resource management is one of the hardest disciplines to embed consistently. Teams know they should do it but often skip it until a crisis forces the issue.
Make it a standing calendar event: "Monday 9am: 2-4 week capacity check"
Q: Before vs after - what changes when you do this weekly?
A: The shift is subtle but powerful:
| Scenario | Before (reactive) | After (proactive) |
|---|---|---|
| Engineer takes leave | "Wait, who's deploying this week?" | "Deployment moved to next Monday, Alice confirmed cover" |
| 3 team members off | "We'll just work harder this week" | "Scope cut to 2 critical features, rest moved to sprint +1" |
| Designer off during review | "Client feedback sitting unanswered for 5 days" | "Review moved forward 1 week, designer available" |
| Sick leave hits | "Everything's on fire, we're late" | "We budgeted 10% buffer, absorbed the impact" |
| Manager escalation | "Why didn't you tell me sooner?" | "You approved the scope cut 2 weeks ago" |
The ONS and CIPD data support this: if 4-9 days of sick leave per employee is the norm, teams that don't budget for it are setting themselves up for constant surprises. The 2-4 week look-ahead turns unplanned absence from "crisis" to "expected variance."
Q: Spreadsheet vs calendar vs "proper visibility" (what breaks first)?
A: Different approaches work at different scales:
| Approach | Good for | Breaks when | Typical outcome |
|---|---|---|---|
| Spreadsheet | Teams under 5 people | Version conflicts, manual updates, no workflow | Manager spends 2hrs/week reconciling versions |
| Shared calendar | Seeing who's off | No approval workflow, no balance tracking, calendar bloat | You see leave but don't know if it's approved or how many days remain |
| Leave tool only | Request/approval + balances | No capacity or project view | You know who's off but still manually cross-reference with project plans |
| Leave + capacity view | 2-4 week risk spotting | Rarely (if designed well) | Manager spots conflicts in 5 min instead of 30 min |
The key insight from queuing theory: as utilization approaches 100%, wait times explode exponentially. A team at 95% capacity with no buffer becomes a bottleneck factory. The 2-4 week view + capacity buffer keeps you out of the danger zone.
Q: What should we quote if we want a "data-backed" PR angle?
A: Use these stats for blog posts, internal memos, or stakeholder updates:
- UK employees lost 2.0% of working hours to sickness in 2024 (ONS)
- Average sick leave: 9.4 days per employee, 4.1% of working time (CIPD 2025)
- Only 58% of projects meet original deadlines (PMI Pulse 2025)
- Resource management is one of the hardest PM disciplines to embed (Wellingtone)
One-line PR quote:
"Most delivery slips aren't caused by the work being hard - they're caused by predictable capacity gaps that nobody spotted 2-4 weeks early."
FAQ
How often should we run this checklist?
Weekly, typically on Monday morning. It takes 15 minutes once you have the right visibility tools.
What's a good buffer for unplanned absence?
Assume 5-10% capacity loss for unplanned absence (sick leave, emergencies). In high-risk periods (winter, post-holidays), use 10-20%.
What's the #1 thing that causes delivery slips from leave?
Stacked leave on critical roles with no cover plan. When 2+ people with unique skills are off the same week, and nobody flagged it 2+ weeks early.
We're a small team - do we really need this?
Yes, especially in small teams. Losing 1 person from a 5-person team = 20% capacity drop. Small teams feel absence more acutely.
What if we can't move deadlines?
Cut scope (reduce features/quality) or shift people (pull from other projects). If neither is possible, negotiate the deadline early - not the day before.
Get leave tracking with capacity visibility
If you want leave tracking with capacity visibility and no per-seat pricing, Zotrack combines leave management, resource allocation, and expense tracking in one tool. See who's off, spot capacity gaps 2-4 weeks ahead, and make decisions before deadlines slip.
References
- ONS: Sickness absence in the labour market, 2023 and 2024
- CIPD: Health and wellbeing at work 2025
- PMI: Pulse of the Profession 2025
- Wellingtone: State of Project Management Research
- Dan Slimmon: The most important thing to understand about queues