GCRI · Agency
Team formation
Most technical assistance is delivered by teams that combine disciplines: law and economics, engineering and safeguards, data and public finance. The risk lies less in any one member than in the interfaces between them and in who answers for the whole. This page sets out how teams are composed, where accountability breaks, how composition changes propagate through a work plan, and what the institutions that commission and receive the work need to see.
Team formation in seven parts.
- 01The questionTeam formation: how the risk develops
- 02In the five domainsTeams combine domains when the problem crosses them
- 03IndicatorsWhat is measured, and how well
- 04SourcesWhere the evidence comes from
- 05DecisionsWho decides, and what the evidence serves
- 06Core questionsWhat a team lead must settle first
- 07MechanismsWhy interdisciplinary teams struggle
Team formation: how the risk develops.
Interdisciplinary assignments and accountability. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Interfaces carry the risk
Each discipline works to its own standards and vocabulary. Gaps open where an engineer’s design assumes a safeguard measure no one costed, or an economist’s model assumes a legal power the lawyer has not confirmed.
Shared work, diffused accountability
When a deliverable has several contributors and no single accountable holder, quality checks fall between them. A named team leader with documented authority over content and schedule is the usual remedy, and often missing.
Composition drifts
Members leave, are reassigned or are replaced mid-assignment. Each change loses context, relationships with counterparts and undocumented decisions, and the replacement inherits work they did not scope.
Delays follow the critical path
One late input, such as a survey or a legal opinion, holds back every deliverable that depends on it. Downstream experts wait or proceed on assumptions, and rework compounds the original delay.
People and hazards in East Africa.
Population density, night lights and flood water over East Africa, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
People and hazards, for this page
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
- Provider
- NASA LAADS DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite radiance, corrected for moonlight and atmosphere
- Newest at build
- 2026-10-12
- Resolution
- about 500 m grid
- Uncertainty
- Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS Global Flood Product (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite detection; clouds leave gaps. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- MODIS Terra EVI (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite index; clouds leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 250 m grid
- Uncertainty
- Satellite vegetation index for the 8 days to the date shown, a habitat condition indicator; not a measure of species or biodiversity.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
People and hazards, framed on East Africa.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA JPL OPERA DIST-ALERTSources and licences
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Optional layers (5 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
Teams combine domains when the problem crosses them.
Team records feed the Portfolio and Readiness series. Conflicts are declared before work starts.
- Team design proposals.
- Lessons on interdisciplinary work.
Assignment and team board.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Assignment and team board
Team formation · Assignment pool · Quarter 3
Assignments
Team record
| Team lead | Disaster risk management | None declared | Confirmed |
| Hydrologist | Flood modelling | Declared, managed | Confirmed |
| Data engineer | Pipelines | None declared | Invited |
| Reviewer | Independent | None declared | Confirmed |
Scope
- Requester
- Requesting institution
- Duration
- 8 weeks
- Authority
- stays with the requester
- Fee
- no fee stated
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Deliverables with a single accountable holder | percent of deliverables | per work plan | Inception reports, responsibility matrices | DECLARED |
| Disciplines required against disciplines staffed | ratio | per assignment | Terms of reference against team roster | REPORTED |
| Documented interface agreements between workstreams | count per assignment | per work plan | Inception and work-plan records | REPORTED |
| Team member changes during the assignment | count per assignment | per assignment | Contract variation records | Published statistics |
| National and local expert input | percent of expert person-days | per assignment | Timesheets and contract records | REPORTED |
| Gender composition of expert teams | percent of team members | per assignment | Team rosters | DECLARED |
| Schedule variance on team deliverables | days | per deliverable | Work plan against acceptance dates | OBSERVED |
Model team formation as a system. Run the cascade.
Assembled from the Nexus Standards area profile Disaster risk reduction: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Tropical cyclone
- Flash flood
- Heatwave
- Ice-jam flood
- HIV epidemic
- Earthquake
- Storm surge (set off downstream)
- Intense rainfall (set off downstream)
- River flood (set off downstream)
- Dangerous surf (set off downstream)
- Widespread power outage (set off downstream)
- Mass displacement (set off downstream)
- Coastal flood (set off downstream)
- Extreme fire weather (set off downstream)
- Wildfire (set off downstream)
- Heat-driven grid stress (set off downstream)
- Agricultural drought (set off downstream)
- Flash drought (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-1The UNI and the artefact catalogue (grammar v0.2: domain, sector, region and environment segments)NS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-3bDataset and product metadata profile (STAC, DCAT, PROV-O)NS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-14Conformance and crosswalk to external standardsNRS-C15Loss, damage and impact accountingNRS-H114Hazard family: Macroeconomic and fiscal shocks (NHS-1 soc.macro-fiscal)NRS-K20Domain pack profile: Climate adaptation (DOMAIN-020)NRS-H54Hazard family: Signal and platform disruption (NHS-1 cyber.platform)NRS-H65Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)NRS-H119Hazard family: Cultural heritage loss (NHS-1 soc.heritage)
Observation
- DesInventar disaster loss databases (listed for reference)
- INFORM Risk Index (listed for reference)
- Global SDG Indicators Database (listed for reference)
- EM-DAT international disaster database (listed for reference)
- Number of deaths and missing persons attributed to disasters per 100,000 population
- Number of directly affected people attributed to disasters per 100,000 population
- Direct economic loss attributed to disasters in relation to global GDP
- Damage to critical infrastructure attributed to disasters
- Number of countries that adopt and implement national DRR strategies
- Total public international support for national disaster risk reduction actions (Sendai indicator F-1)
- Number of countries that have multi-hazard early warning systems
- Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 population
Example geography
- Bangladesh: 134 hexagonal cells
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Surface air temperature, daytime (AIRS), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| World Bank Implementation Completion and Results Reports | Records of team, implementation arrangements and lessons on delivery | Public documents under the World Bank access to information policy |
| OECD DAC Evaluation Resource Centre | Published evaluations of programmes, including team and management arrangements | Public reports, terms per evaluating agency |
| EU Results Oriented Monitoring reports | Structured monitoring of EU-funded actions, including implementation and management findings | Published reports, European Commission reuse terms |
| IATI Datastore | Participating organisations and roles in each activity | Open, licence declared per publisher |
| National audit office performance audits | Findings on the management and accountability of consultancy teams | Public records, terms per audit office |
How team formation is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Datasets and provenance
The data classes behind team formation and what is recorded about each before it is used.
| Data class | Provenance recorded | Resolution stated | Licence checked |
|---|---|---|---|
| Satellite imagery, optical and radar | sensor, processing level, acquisition date | pixel size and revisit | per scene |
| Reanalysis and climate model output | model, experiment, member, version | grid and time step | per release |
| In-situ sensors and gauges | station, instrument, calibration record | point and sampling rate | per network |
| Population and asset exposure | method, vintage, input sources | cell size and unit | per release |
| Boundaries and reference geography | producer, edition, date | scale | per edition |
- Lineage
- W3C PROV record from source to figure
- Principles
- FAIR: findable, accessible, interoperable, reusable
- Gaps
- shown as missing, never filled silently
Who decides, and what the evidence serves.
Agency prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Client project implementation unit or programme director | Whether the proposed team covers every discipline the work requires and names who answers for each deliverable | Composition matrix and responsibility matrix against the terms of reference |
| Funding agency task team leader | Whether a mid-assignment team change keeps the competence and continuity the contract assumed | Substitution evidence and continuity plan |
| Employing firm or institution management | Whether it can field and retain the team for the assignment’s duration | Availability commitments and interface register |
| Programme steering committee | Whether delays on one workstream require rescoping the others | Interface register and schedule variance on dependent deliverables |
Outputs this topic produces
- Team composition matrices that map each requirement to a discipline and a holder
- Responsibility matrices with one accountable holder per deliverable
- Interface registers between workstreams with agreed inputs and dates
- Continuity plans for planned and unplanned team changes
What a team lead must settle first.
- What is the question, and which disciplines does it genuinely need?
- Who is the one accountable lead, and to whom do they answer?
- How will different methods and vocabularies be integrated into one answer?
- Who reviews the integrated output independently?
Why interdisciplinary teams struggle.
Teams fail when each discipline produces its own report and nobody integrates them, when assumptions made by one member are invisible to another, or when responsibility is shared so widely that no one answers for the result. Status differences between disciplines can silence the people closest to the affected communities.
Well-run teams agree a shared problem statement and a common set of assumptions early, make interfaces between workstreams explicit and schedule integration as work in its own right rather than an afterthought.
Signals of a healthy team.
- A one-page problem statement every member can explain in their own words.
- A shared register of assumptions, updated when any workstream changes one.
- Integration time scheduled in the plan, not left to the final week.
- Voices from affected communities and operators heard alongside technical specialists.
How it is studied, and what the methods cannot say.
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
Why name one accountable holder per deliverable?
What is an interface agreement?
How should national expertise be counted?
Is a team a legal entity or joint venture?
How is disagreement within a team handled?
Can institutions second staff to a team?
How large should a team be?
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