Overall maturity distribution
Unweighted
Most assessments cluster around ~50%, with a long tail to both low and high maturity.
Global water governance maturity — a WaterGuide snapshot
This is a single‑page, mobile‑first public report built from 100 synthetic WaterGuide assessments. It demonstrates how your data collection instrument can become an external-facing benchmark and engagement portal.
100
jurisdictions
80
countries
20
basins / states
Average maturity by element
6 elements
A quick scan of which parts of national water architecture tend to be strongest and weakest.
Regional pattern heatmap
Region × element
Where maturity tends to differ by geography (synthetic regions for demo purposes).
Which elements are weighted highest?
Importance mix
High/Medium/Low importance selections aggregated across respondents.
Importance vs outcomes gap
“priority pressure”
Elements where respondents signal high importance but report weaker effectiveness.
Scatter: importance vs maturity (select element)
interactive
Low importance
Medium importance
High importance
Who responded?
Role mix
A proxy for decision-making seniority and institutional locus.
—
Top role
Spider profile
weighted vs unweighted
The same six elements, plotted as averages for the filtered subset.
Weighted
Unweighted
Opportunities for collective action
themes & alignment
Themes inferred from common low‑maturity priority elements. In a real deployment these can map to platform offerings (peer learning, regional compacts, data standards, financing mechanisms).
Most common priority pairs
What jurisdictions tend to struggle with together (useful for packaged reform programs).
Call to action
Want a defensible benchmark using your real assessment data, plus a facilitation and reform program behind it? We can provide the instrument, analytics layer, and targeted advisory support.
Replace
hello@example.com with your firm mailbox.Methodology & dataset notes
Synthetic demo
This public benchmark illustrates how WaterGuide self-assessment data can be aggregated into an external-facing snapshot. Results shown here are generated from a synthetic dataset designed to mimic realistic response patterns and are not intended to represent any real jurisdiction’s performance.
- Coverage: 100 jurisdictions (80 countries; 20 subnational units across 12 of those countries).
- Scoring: each jurisdiction has six element scores (0–100) generated from a bell-curve distribution centred near 50, with light noise by element and region.
- Outcomes/effectiveness: a separate perceived outcomes score is generated per element to enable ‘importance vs outcomes’ analysis.
- Importance weights: respondent-level High/Medium/Low selections are aggregated and applied in the ‘Weighted’ view; unweighted remains a pure maturity view.
- Segmentation: jurisdictions are tagged with UNDP-style region groupings and HDI tiers to demonstrate development-aware benchmarking and filtering.
- Privacy: for live deployments, publish only aggregated results above minimum group sizes; keep respondent-level data restricted.
In a production benchmark, we recommend publishing a transparent scoring rubric, documenting sampling/response rates, and providing confidence bands where multiple respondents per jurisdiction are available.