Ka Lei Lai.
Active — last recorded decision May 2026
A case officer at Waltham Forest with an approval rate of 78% across 369 decided planning applications, spanning 23 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×.
Lai's GPDO permitted-development checklists are distinctive for precise millimetre/metre-level quantification of every measured criterion (eaves height, boundary proximity, roof-space volume) with the specific shortfall stated explicitly where a scheme fails ('would measure 3.4m, which would exceed the eaves height of the existing dwellinghouse (2.6m) by 0.8m') rather than a bare compliant/non-compliant tick. On larger full applications she runs the same forensic quantification against the Local Plan's space-standard and biodiversity policies, and is willing to allow a marginal shortfall in one metric (a studio flat's lack of private amenity space) where the wider context (town-centre location, high PTAL, proximity to open space) can be shown to justify it on balance, rather than applying the standard mechanically regardless of context.
· states the exact numerical shortfall against a GPDO/space-standard threshold ('would exceed... by 0.8m') rather than a bare compliant/non-compliant finding
· on marginal space-standard or amenity shortfalls, explicitly weighs contextual mitigating factors (PTAL rating, proximity to open space, town-centre location) before deciding whether to allow the shortfall on balance
· cross-references stated application-form dimensions against her own measurements from submitted plans, and flags any discrepancy explicitly
· the precise numerical margin by which a proposal complies with or exceeds a GPDO/space-standard threshold, not just a pass/fail judgement
· whether a marginal shortfall against a space or amenity standard can be justified on balance by the site's wider context (PTAL, proximity to parks, town-centre location)
· whether the dimensions stated on the application form match officers' own measurements taken from the submitted plans
“would measure 3.4m, which would exceed the eaves height of the existing dwellinghouse (2.6m) by 0.8m”
231286
“given its town centre location, well connectivity, small sized dwelling type and high accommodation quality, the lack of amenity space for this studio flat would be allowed and justified in this instance”
242347
“the proposed dwelling would fail to comply with the minimum space requirement set out by Policy DM7”
231531
Measured from 103 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 103 parsed reports. Whether refusals citing each survive appeal isn't traced per policy yet.
Show all 23 rows
Where this officer's caseload concentrates, 2021–26.[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, 2021–26. · 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 103 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.