Afreen Ayesha.
Active — last recorded decision May 2026
A case officer at Waltham Forest with an approval rate of 70% across 62 decided planning applications, spanning 16 wards.[1] Decision speed and appeal performance publish when decision notices are ingested.
Topic mentions per 1,000 words of their own report text (boilerplate stripped), indexed against all parsed Waltham Forest reports. Attention, not stance.
Mark = borough average (1×). Bar capped at 2×.
Ayesha's caseload spans GPDO dormer certificates and retrospective/lawful-use determinations, and she is distinctive for framing a substandard-unit upgrade explicitly as a 'balanced and proportionate' improvement where the EXISTING lawful units are already substandard by NDSS measures, comparing the specific sqm shortfalls before and after rather than requiring full compliance. On retrospective sui-generis/HMO use evidence she runs a methodical named-evidence-type checklist (planning history, trade invoices by specific year, Google Street View imagery, online listings, food hygiene ratings, customer reviews) assessing each type's evidential weight individually before reaching an overall balance-of-probabilities conclusion.
· frames a scheme that leaves individual units still short of NDSS minimums as a 'balanced and proportionate' upgrade where the EXISTING lawful units were already substandard, explicitly comparing the specific sqm shortfall before and after rather than requiring full compliance
· runs a methodical checklist of named evidence types (planning history, dated trade invoices, Google Street View imagery, online listings, food hygiene ratings, customer reviews) for retrospective sui-generis/HMO use claims, weighing each type's evidential value individually
· notes explicitly when NO floorplans or planning statement have been submitted at all, distinguishing a genuine evidential vacuum from merely weak evidence, and refuses accordingly
· the specific sqm shortfall against NDSS minimums for both the existing (already substandard) and proposed units, to assess whether a scheme is a genuine net improvement
· each individual named evidence type (dated invoices, Street View imagery, online listings, hygiene ratings, reviews) and its own evidential weight for a retrospective use claim
· whether any evidence at all (floorplans, planning statement) has been submitted, distinguishing a genuine evidential vacuum from weak-but-present evidence
“Given the existing lawful self?contained units (regularised in 2017) are already substandard by NDSS measures, the scheme represents a balanced and proportionate upgrade to living conditions within a constrained building.”
252508
“Only a title plan/site location plan and an application form have been submitted.”
260245
Measured from 35 published Waltham Forest officer reports written by this officer, with recited policy boilerplate stripped before any counting. These describe how this officer works and writes — they are not outcome predictions. Every quote is from a named public report.
The policies this officer cites most in their own reports — times cited across 35 parsed reports. Whether refusals citing each survive appeal isn't traced per policy yet.
Show all 16 rows
Where this officer's caseload concentrates, 2025–26.[1] Click the map above to focus this page on a ward, or a row to open the ward.
- [1]Applications decided, approval rate, per-year trend and ward breakdown — London Borough of Waltham Forest planning register and published decision notices, 2025–26. · methodology
- [2]Appeal overturn and decision-time benchmarks — Planning Inspectorate (PINS) appeal decisions and application date pairs; not yet computed per officer, shown as a dash until they are. · PINS appeals casework
- [3]Condition load — mean effective conditions attached to Waltham Forest decision notices (grant/split), parsed from the published notice text; a borough figure, not yet split per case officer.
- [4]"How this officer decides", the policy playbook and all quotes — parsed from 35 published Waltham Forest officer reports written by this officer, recited policy boilerplate stripped before counting; disposition text coded from their own reasoning with every quote machine-verified verbatim. Descriptive of how they work — not outcome predictions.