🗓 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.
📊 Ealing
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 70 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 | 88.5% |
| Feb | Submit by end of Dec | 85.4% |
| Mar | Submit by end of Jan | 87.1% |
| Apr | Submit by end of Feb | 89.5% |
| May | Submit by end of Mar | 100% |
| Jun | Submit by end of Apr | 50% |
| Jul | Submit by end of May | 72.7% |
| Aug | Submit by end of Jun | 77.4% |
| Sep | Submit by end of Jul | 82.4% |
| Oct | Submit by end of Aug | 77.4% |
| Nov | Submit by end of Sep | 86% |
| Dec | Submit by end of Oct | 82.1% |
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 Ealing. 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: Prior Approval (39 days). Slowest: Full / Major (98 days).
| Application type | Decisions | Approval rate | Avg days | Range | |
|---|---|---|---|---|---|
| Householder | 222 | 91.4% | 88 d (13 wk) | 25–296 d | Filter ▸ |
| Lawful Development | 206 | 89.3% | 54 d (8 wk) | 11–330 d | Filter ▸ |
| Full / Major | 50 | 26% | 98 d (14 wk) | 34–310 d | Filter ▸ |
| Prior Approval | 48 | 64.6% | 39 d (6 wk) | 22–111 d | Filter ▸ |
| Advertisement | 14 | 85.7% | 81 d (12 wk) | 51–264 d | Filter ▸ |
| Conservation Area (low sample) | 6 | 83.3% | 126 d (18 wk) | 51–258 d | Filter ▸ |
| Listed Building (low sample) | 2 | 100% | 157 d (22 wk) | 90–223 d | Filter ▸ |
| Change of Use (low sample) | 1 | 0% | 93 d (13 wk) | 93–93 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 | 201 |
87.1%
|
41d (~6wk) | → February | 7–75d |
| February | 76 |
89.5%
|
26d (~4wk) | → March | 7–45d |
| March | 4 |
100%
|
15d (~2wk) | → April | 14–16d |
| April | 4 |
50%
|
309d (~44wk) (outlier) | → February | 278–330d |
| May | 11 |
72.7%
|
275d (~39wk) (outlier) | → February | 247–308d |
| June | 31 |
77.4%
|
243d (~35wk) (outlier) | → February | 198–282d |
| July | 17 |
82.4%
|
207d (~30wk) (outlier) | → February | 169–242d |
| August | 31 |
77.4%
|
168d (~24wk) | → February | 131–211d |
| September | 43 |
86%
|
144d (~21wk) | → February | 98–196d |
| October | 56 |
82.1%
|
101d (~14wk) | → January | 64–148d |
| November | 130 |
88.5%
|
67d (~10wk) | → January | 39–121d |
| December | 198 |
85.4%
|
53d (~8wk) | → February | 24–101d |
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 | 182 | 85.2% | 79 |
| Tuesday | 178 | 86.5% | 74 |
| Wednesday | 137 | 81% | 81 |
| Thursday | 129 | 87.6% | 78 |
| Friday | 157 | 89.8% | 78 |
| Saturday | 15 | 60% | 50 |
📊 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.