🗓 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 80 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 | 77% |
| Feb | Submit by end of Nov | 85.6% |
| Mar | Submit by end of Dec | 55.1% |
| Apr | Submit by end of Jan | 74.6% |
| May | Submit by end of Feb | 81.1% |
| Jun | Submit by end of Mar | 75% |
| Jul | Submit by end of Apr | 100% |
| Aug | Submit by end of May | 100% |
| Sep | Submit by end of Jun | 10.8% |
| Oct | Submit by end of Jul | 3.4% |
| Nov | Submit by end of Aug | 11.1% |
| Dec | Submit by end of Sep | 75.7% |
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 | 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 | ✕ clear |
| 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 Advertisement 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 | 236 |
74.6%
|
51d (~7wk) | → March | 8–81d |
| February | 111 |
81.1%
|
50d (~7wk) | → April | 10–332d |
| March | 28 |
75%
|
66d (~9wk) | → May | 5–349d |
| April | 3 |
100%
|
221d (~32wk) (outlier) | → November | 53–341d |
| May | 7 |
100%
|
262d (~37wk) (outlier) | → February | 239–314d |
| June | 37 |
10.8%
|
231d (~33wk) (outlier) | → February | 219–285d |
| July | 58 |
3.4%
|
222d (~32wk) (outlier) | → February | 201–225d |
| August | 9 |
11.1%
|
178d (~25wk) | → February | 133–184d |
| September | 37 |
75.7%
|
137d (~20wk) | → February | 120–177d |
| October | 74 |
77%
|
116d (~17wk) | → February | 69–175d |
| November | 209 |
85.6%
|
76d (~11wk) | → February | 38–132d |
| December | 372 |
55.1%
|
62d (~9wk) | → February | 8–118d |
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 |
|---|---|---|---|
| Monday | 378 | 55% | 81 |
| Tuesday | 187 | 83.4% | 79 |
| Wednesday | 244 | 55.3% | 104 |
| Thursday | 203 | 71.9% | 95 |
| Friday | 157 | 76.4% | 75 |
| Saturday | 22 | 72.7% | 22 |
🌍 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.