🗓 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.
📊 Kensington and Chelsea
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 68 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 | 96% |
| Feb | Submit by end of Dec | 95.7% |
| Mar | Submit by end of Jan | 72.7% |
| Apr | Submit by end of Feb | 50% |
| May | Submit by end of Mar | 80% |
| Jun | Submit by end of Apr | 100% |
| Jul | Submit by end of May | 33.3% |
| Aug | Submit by end of Jun | 42.9% |
| Sep | Submit by end of Jul | 33.3% |
| Oct | Submit by end of Aug | 86.7% |
| Nov | Submit by end of Sep | 100% |
| Dec | Submit by end of Oct | 100% |
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 Kensington and Chelsea. 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: Conservation Area (63 days). Slowest: Advertisement (170 days).
| Application type | Decisions | Approval rate | Avg days | Range | |
|---|---|---|---|---|---|
| Full / Major | 101 | 72.3% | 117 d (17 wk) | 35–289 d | Filter ▸ |
| Householder | 51 | 94.1% | 82 d (12 wk) | 32–317 d | Filter ▸ |
| Advertisement | 38 | 36.8% | 170 d (24 wk) | 53–239 d | Filter ▸ |
| Conservation Area | 16 | 93.8% | 63 d (9 wk) | 47–100 d | Filter ▸ |
| Lawful Development | 13 | 92.3% | 67 d (10 wk) | 49–128 d | Filter ▸ |
| Listed Building | 10 | 100% | 88 d (13 wk) | 56–130 d | Filter ▸ |
| Prior Approval (low sample) | 2 | 100% | 268 d (38 wk) | 216–319 d | Filter ▸ |
| Change of Use (low sample) | 2 | 100% | 268 d (38 wk) | 216–319 d | Filter ▸ |
📅 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 | 11 |
72.7%
|
26d (~4wk) | → February | 2–36d |
| March | 5 |
80%
|
315d (~45wk) (outlier) | → February | 303–322d |
| April | 3 |
100%
|
304d (~43wk) (outlier) | → February | 289–317d |
| May | 3 |
33.3%
|
270d (~39wk) (outlier) | → February | 260–280d |
| June | 14 |
42.9%
|
222d (~32wk) (outlier) | → January | 199–239d |
| July | 21 |
33.3%
|
213d (~30wk) (outlier) | → February | 165–225d |
| August | 15 |
86.7%
|
168d (~24wk) | → February | 149–184d |
| September | 17 |
100%
|
125d (~18wk) | → January | 102–160d |
| October | 39 |
100%
|
101d (~14wk) | → January | 75–133d |
| November | 101 |
96%
|
66d (~9wk) | → January | 48–99d |
| December | 70 |
95.7%
|
52d (~7wk) | → February | 26–70d |
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 | 63 | 81% | 142 |
| Tuesday | 73 | 93.2% | 147 |
| Wednesday | 64 | 76.6% | 186 |
| Thursday | 59 | 96.6% | 127 |
| Friday | 64 | 93.8% | 131 |
📊 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.