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🗓 Submission Timing Intelligence

When is the best month — and weekday — to submit your planning application? Real approval-rate + decision-speed data from 25,848 dated decisions across UK LPAs.

📅 Monthly breakdown per LPA 🏆 Best / worst windows ⚡ Decision-speed by month 🌍 National baseline for context
🏛️ By LPA 🗓 Best LPAs by Month
Narrow by type All types Householder Full / Major Outline Reserved Matters Listed Building Conservation Area Prior Approval Lawful Development Change of Use

📊 National (all LPAs)

Months below refer to when you submit, not when the decision lands. Each application is bucketed by its received_date month — but the approval rate measures the final outcome, whenever it landed (60-90 days later typically). The lag is already baked into the signal: "submit in December = 100% approval" already accounts for the fact that those decisions arrive in Feb/March. The month-by-month table below shows the lag explicitly so you can see the full cycle.

Best month to submit: March — apps submitted then end up with 91.9% approval (sample: 111 decisions). Avoid submitting in May (60.0% approval).
🏆 Best SUBMIT Month
March
Apps submitted then → 91.9% approval (111 decisions)
⚠️ Avoid SUBMITTING In
May
Apps submitted then → 60.0% approval (10 decisions)
⚡ Submit For Fastest Decision
March
Apps submitted then → avg 14 days to decision
🎯 Inverse view — "I want a decision in [month], when do I submit?"

Based on this LPA's typical decision-lag of 66 days (~2 months), the table below shows when to submit if you want your decision to land in a specific month.

If you want a decision in...Submit by (approx.)That submit month's approval rate
Jan Submit by end of Nov 81.1%
Feb Submit by end of Dec 81.5%
Mar Submit by end of Jan 86.4%
Apr Submit by end of Feb 85.4%
May Submit by end of Mar 91.9%
Jun Submit by end of Apr 50%
Jul Submit by end of May 60%
Aug Submit by end of Jun 84.6%
Sep Submit by end of Jul 100%
Oct Submit by end of Aug
Nov Submit by end of Sep 77.8%
Dec Submit by end of Oct 78.3%

Inverse calculation is approximate — actual decision time varies (range typically ±30 days). Use the Decision Time Predictor for tighter forecasts.

⏱ Decision speed by application type

How long different application types actually take at National (all LPAs). Householder apps are statutorily 8 weeks; full/major are 13 weeks — but the real numbers usually drift. This is what the data says, not what the statute says.
→ Fastest: Discharge Conditions (43 days). Slowest: Outline (110 days).

Application type Decisions Approval rate Avg days Range
Householder 5,243 86.8% 67 d (10 wk) 2–365 d Filter ▸
Full / Major 4,585 72.6% 87 d (12 wk) 1–365 d Filter ▸
Lawful Development 2,815 84% 47 d (7 wk) 0–337 d ✕ clear
Conservation Area 1,482 86.8% 50 d (7 wk) 0–365 d Filter ▸
Advertisement 1,181 65.5% 83 d (12 wk) 5–349 d Filter ▸
Listed Building 1,111 90.6% 100 d (14 wk) 7–356 d Filter ▸
Prior Approval 884 66.2% 46 d (7 wk) 2–345 d Filter ▸
Change of Use 107 65.4% 93 d (13 wk) 23–319 d Filter ▸
Discharge Conditions 35 88.6% 43 d (6 wk) 3–194 d Filter ▸
Outline 13 23.1% 110 d (16 wk) 37–361 d Filter ▸
Reserved Matters (low sample) 6 83.3% 151 d (22 wk) 15–361 d Filter ▸

ⓘ Month-by-month stats above are filtered to Lawful Development only. The table above always shows all types so you can compare.

🤔
Submit-now-or-wait recommendation
BORDERLINE
Current month (June): 84.6% approval. Best (March): 91.9%. Best is too far away — submit now.
Current month's decision speed: ~249 days avg.

📅 Month-by-month breakdown — full submit→decide cycle

Each row shows the complete journey for applications received in that month: how long they took, when the decision actually landed, and what % were approved. The approval rate already accounts for everything that happens between submission and decision — the lag is part of the signal.

Submit month Decisions Approval rate Median lag Decision typically lands in Range
January 922
86.4%
40d (~6wk) → February
February 529
85.4%
32d (~5wk) → March
March 111
91.9%
14d (~2wk) → March
April 4
50%
178d (~25wk) → October 1–330d
May 10
60%
261d (~37wk) (outlier) → February 32–308d
June 13
84.6%
249d (~36wk) (outlier) → February 238–274d
July 7
100%
205d (~29wk) (outlier) → February 185–230d
September 18
77.8%
134d (~19wk) → January 104–172d
October 69
78.3%
94d (~13wk) → January 60–157d
November 386
81.1%
60d (~9wk) → January 34–132d
December 746
81.5%
51d (~7wk) → February 9–119d

Read across each row: submit in [month] → wait [median lag] → decision lands in [target month] → outcome [approval rate]. The approval rate is the final outcome of the whole cycle, not a snapshot.

🗓 Day-of-week patterns

Day receivedDecisionsApproval rateAvg days
Monday 735 82.3% 50
Tuesday 634 83% 45
Wednesday 491 81.1% 51
Thursday 443 86% 50
Friday 470 89.4% 47
Saturday 42 83.3% 32

🌍 National picture — all 25,848 dated decisions

The broader pattern: March has the highest approval rate in our corpus; July the lowest. Pick an LPA above to see council-specific timing.

Received inDecisionsApproval rateAvg days
January 5,547
83%
46
February 2,908
86.3%
39
March 652
91.9%
51
April 141
89.4%
213
May 185
86.5%
227
June 275
79.3%
241
July 317
72.9%
212
August 386
86.5%
181
September 667
90%
145
October 1,523
86.6%
111
November 4,024
84.7%
71
December 5,661
81.7%
57
⚖️ Why timing matters less than they pretend: A planning decision should be made on its substantive merits, not the season. But officers have queues, committees have schedules, and consultees go on holiday. The data is a guide to operational friction, not policy friction. If your scheme is sound, time it to land in their best window. If it's borderline, give yourself every advantage.
📊 Data sources & freshness

Timing is a tactical edge, not strategic justification. Use alongside the constraint check + pattern fingerprint to make the case strong on substance, then time it to land well.

  • planning_applications.received_date (updated Daily ingest)
    25,848 dated decisions where both received_date and decision_type are known. Approval = approved/granted/permit. Sample size gating: months with fewer than 8 decisions excluded from best/worst recommendation.
  • Day-of-week patterns
    Reflects when applicants choose to submit, which may correlate with applicant type (Monday = professional consultants; Friday = end-of-week DIY submissions). Causality is correlative not causal.
  • Decision-time outliers
    Months showing 200+ day averages are flagged — they reflect older PINS-appeal-derived rows where determinations stretched over many months. Read the Jan/Feb/Nov/Dec numbers (largest samples) as the reliable benchmark.
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