Methodology

What this tool measures

Sweetstep displays scores from the DfT Connectivity Metric 2025 (published — not formally designated as National Statistics), produced by the Department for Transport, covering England and Wales.

The Department for Transport has published this data. It has not been given the formal “National Statistics” label by the UK Statistics Authority. That label is a quality badge — without it, the data is still official and still free to use, but it has not been through that extra check.

The Department for Transport also has a more detailed version of this data, measured in 100-metre squares. That version is only available to councils and other public bodies. Sweetstep uses the Output Area version, which anyone can download — so this is currently the only way for the public to see these scores for their own area.

The metric measures travel-time accessibility to six destination types via four transport modes:

Current release covers England & Wales (188,880 Output Areas) and Scotland (SIMD 2020 travel-time proxy, different methodology). Northern Ireland is pending. See Data coverage below for detail.

Score grades

Sweetstep groups scores into four display grades. These thresholds are display conventions chosen by Sweetstep — they are not defined or endorsed by the Department for Transport.

Geographic units

Scores are assigned at the Output Area (OA) level — the smallest census geography in England and Wales, typically covering around 300 residents.

One OA may contain multiple postcodes; one postcode maps to exactly one OA. OA codes (e.g. E00012345) have no recognisable place names — this is an inherent limitation of the geographic unit.

Limitations

Accessibility

Sweetstep’s walking and public transport scores model travel-time connectivity for the general population. They are derived from the Department for Transport Connectivity Metric 2025, which is based on road network and timetable data — not accessibility infrastructure.

What the scores do not cover: the presence or absence of dropped kerbs, step-free routes, lift availability at stations, surface quality (tarmac vs. cobbles or gravel), pavement width, and temporary obstructions. A postcode could score 85 for walking yet be effectively inaccessible to someone using a wheelchair, a pushchair, or a mobility aid.

Why this gap exists: no national, open dataset maps pedestrian accessibility infrastructure at Output Area granularity. The DfT Connectivity Metric is the best available public data for travel-time modelling; it is simply silent on accessibility.

What Sweetstep is doing about it: Phase A of the accessibility roadmap extends the crowd-validation system to capture accessibility-specific reports — pavement obstructions, surface barriers, transport access barriers, crossing barriers, and temporary barriers. These reports feed a data flywheel that will, over time, let Sweetstep flag OAs where accessibility constraints are known to diverge from the headline score.

Phase B (planned) will incorporate step-free transit data from sources such as OpenStreetMap accessibility tags and National Rail step-free station data, where coverage and licence terms permit.

This is a known limitation. Sweetstep is actively working to address it. Help us build better accessibility data — flag an inaccuracy using the “Flag an inaccuracy” button on any result page and select the accessibility option.

Persona weighting

The persona toggle on a result page re-weights the same DfT scores to reflect what different people most need. It does not change the underlying data — it changes the emphasis across the four transport modes and six destination types, then recomputes a single weighted overall score entirely in your browser. Your raw mode and destination scores stay visible on the same page.

The weighted overall is a weighted average — Σ(score × weight) ÷ Σ(weight) across the 24 mode × destination cells. A mode weighted zero (for example, driving for the “No car” persona) is excluded entirely.

These weights are working heuristics, not DfT-validated persona models. They re-weight what matters most for each persona — not how far you can walk; journey times assume a standard 3 mph walking speed. The “Parent with pram” view does not reflect pavement quality, kerb cuts, or pram-friendly infrastructure — community reports (Sprint 20) will add street-level evidence. A “Shift worker” persona is deliberately excluded because the public transport data reflects daytime service only.

Data coverage

Replicability

The source dataset is publicly available from the Department for Transport under the Open Government Licence v3.0.