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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: 652 decisions). Avoid submitting in July (72.9% approval).
🏆 Best SUBMIT Month
March
Apps submitted then → 91.9% approval (652 decisions)
⚠️ Avoid SUBMITTING In
July
Apps submitted then → 72.9% approval (317 decisions)
⚡ Submit For Fastest Decision
February
Apps submitted then → avg 40 days to decision
🎯 Inverse view — "I want a decision in [month], when do I submit?"

Based on this LPA's typical decision-lag of 76 days (~3 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 Oct 86.6%
Feb Submit by end of Nov 84.7%
Mar Submit by end of Dec 81.7%
Apr Submit by end of Jan 83%
May Submit by end of Feb 86.3%
Jun Submit by end of Mar 91.9%
Jul Submit by end of Apr 89.4%
Aug Submit by end of May 86.4%
Sep Submit by end of Jun 79.3%
Oct Submit by end of Jul 72.9%
Nov Submit by end of Aug 86.5%
Dec Submit by end of Sep 90%

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 4,584 72.6% 87 d (12 wk) 1–365 d Filter ▸
Lawful Development 2,815 84% 47 d (7 wk) 0–337 d Filter ▸
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 34 88.2% 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 ▸
🤔
Submit-now-or-wait recommendation
BORDERLINE
Current month (June): 79.3% approval. Best (March): 91.9%. Best is too far away — submit now.
Current month's decision speed: ~241 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 5,545
83%
46d (~7wk) → March
February 2,908
86.3%
40d (~6wk) → March
March 652
91.9%
51d (~7wk) → May
April 142
89.4%
217d (~31wk) (outlier) → November 1–365d
May 184
86.4%
228d (~33wk) (outlier) → January 1–330d
June 275
79.3%
241d (~34wk) (outlier) → February 184–294d
July 317
72.9%
212d (~30wk) (outlier) → February 152–268d
August 386
86.5%
181d (~26wk) → February 123–237d
September 667
90%
145d (~21wk) → February 90–213d
October 1,523
86.6%
111d (~16wk) → February 59–178d
November 4,022
84.7%
71d (~10wk) → January 24–210d
December 5,657
81.7%
58d (~8wk) → February 5–143d

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
Sunday 54 81.5% 82
Monday 5,407 82% 84
Tuesday 4,809 85.2% 82
Wednesday 4,376 82.7% 87
Thursday 3,936 86.1% 86
Friday 4,049 86.1% 89
Saturday 191 77% 47

🌍 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 651
91.9%
51
April 140
89.3%
215
May 184
86.4%
228
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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