🗓 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.
📊 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.
🎯 Inverse view — "I want a decision in [month], when do I submit?"
Based on this LPA's typical decision-lag of 81 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 | 80.1% |
| Feb | Submit by end of Nov | 76.7% |
| Mar | Submit by end of Dec | 70.8% |
| Apr | Submit by end of Jan | 68.3% |
| May | Submit by end of Feb | 80.4% |
| Jun | Submit by end of Mar | 94.4% |
| Jul | Submit by end of Apr | 91.1% |
| Aug | Submit by end of May | 75.9% |
| Sep | Submit by end of Jun | 61.2% |
| Oct | Submit by end of Jul | 37% |
| Nov | Submit by end of Aug | 53.8% |
| Dec | Submit by end of Sep | 76.9% |
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 | ✕ clear |
| 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 | 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 Full / Major only. The table above always shows all types so you can compare.
📅 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 | 987 |
68.3%
|
56d (~8wk) | → March | 22–356d |
| February | 322 |
80.4%
|
61d (~9wk) | → April | 11–361d |
| March | 36 |
94.4%
|
259d (~37wk) (outlier) | → December | 1–365d |
| April | 45 |
91.1%
|
271d (~39wk) (outlier) | → January | 41–365d |
| May | 58 |
75.9%
|
274d (~39wk) (outlier) | → February | 21–317d |
| June | 116 |
61.2%
|
241d (~34wk) (outlier) | → February | 196–294d |
| July | 100 |
37%
|
221d (~32wk) (outlier) | → February | 160–267d |
| August | 39 |
53.8%
|
176d (~25wk) | → February | 126–225d |
| September | 156 |
76.9%
|
144d (~21wk) | → February | 98–213d |
| October | 462 |
80.1%
|
115d (~16wk) | → February | 59–177d |
| November | 964 |
76.7%
|
76d (~11wk) | → February | 38–210d |
| December | 1,300 |
70.8%
|
64d (~9wk) | → February | 23–143d |
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 received | Decisions | Approval rate | Avg days |
|---|---|---|---|
| Sunday | 17 | 70.6% | 132 |
| Monday | 1,170 | 69.8% | 117 |
| Tuesday | 978 | 77.5% | 118 |
| Wednesday | 983 | 69.3% | 123 |
| Thursday | 816 | 75.7% | 107 |
| Friday | 819 | 76.4% | 114 |
| Saturday | 52 | 63.5% | 70 |
🌍 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 in | Decisions | Approval rate | Avg 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 |
📊 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.