🗓 Submission Timing Intelligence
When is the best month — and weekday — to submit your planning application? Real approval-rate + decision-speed data from 144,167 dated decisions across UK LPAs.
📊 Doncaster
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.
Use the type chips above to filter to the application type you are actually making — and treat cross-council comparisons of the mixed number with care, since the mix depends on which source fed each council.
🎯 Inverse view — "I want a decision in [month], when do I submit?"
Based on this LPA's typical decision-lag of 97 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 | 100% |
| Feb | Submit by end of Nov | 100% |
| Mar | Submit by end of Dec | 85.7% |
| Apr | Submit by end of Jan | 100% |
| May | Submit by end of Feb | 100% |
| Jun | Submit by end of Mar | 100% |
| Jul | Submit by end of Apr | 100% |
| Aug | Submit by end of May | 88.2% |
| Sep | Submit by end of Jun | 85% |
| Oct | Submit by end of Jul | 66.7% |
| Nov | Submit by end of Aug | 100% |
| Dec | Submit by end of Sep | 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 Doncaster. 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: Tree Works / TPO (24 days). Slowest: Discharge Conditions (79 days).
| Application type | Decisions | Approval rate | Avg days | Range | |
|---|---|---|---|---|---|
| Full / Major | 658 | 92.4% | 66 d (9 wk) | 20–343 d | Filter ▸ |
| Discharge Conditions | 143 | 93% | 79 d (11 wk) | 2–301 d | ✕ clear |
| Tree Works / TPO | 81 | 100% | 24 d (3 wk) | 0–126 d | Filter ▸ |
| Amendment / NMA | 58 | 93.1% | 60 d (9 wk) | 5–246 d | Filter ▸ |
| Advertisement | 27 | 96.3% | 58 d (8 wk) | 23–175 d | Filter ▸ |
| Heritage / LB (low sample) | 5 | 100% | 74 d (11 wk) | 34–125 d | Filter ▸ |
ⓘ Month-by-month stats above are filtered to Discharge Conditions 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 | 6 |
100%
|
89d (~13wk) | → April | 13–205d |
| February | 7 |
100%
|
80d (~11wk) | → May | 47–161d |
| March | 10 |
100%
|
40d (~6wk) | → April | 7–72d |
| April | 8 |
100%
|
88d (~13wk) | → July | 17–253d |
| May | 17 |
88.2%
|
68d (~10wk) | → July | 23–148d |
| June | 20 |
85%
|
51d (~7wk) | → August | 10–192d |
| July | 9 |
66.7%
|
90d (~13wk) | → October | 37–279d |
| August | 11 |
100%
|
63d (~9wk) | → October | 2–292d |
| September | 12 |
100%
|
83d (~12wk) | → December | 22–271d |
| October | 21 |
100%
|
113d (~16wk) | → February | 8–301d |
| November | 8 |
100%
|
42d (~6wk) | → December | 7–62d |
| December | 14 |
85.7%
|
127d (~18wk) | → April | 3–241d |
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 | 31 | 93.5% | 101 |
| Tuesday | 28 | 92.9% | 70 |
| Wednesday | 30 | 83.3% | 88 |
| Thursday | 24 | 95.8% | 66 |
| Friday | 32 | 100% | 93 |
📊 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)
144,167 dated decisions where a submission date and a decision are both known. The submission date is received_date, falling back to validated_date — many council portals publish only the validated date, and the statutory clock runs from it. 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.