GIST Impact - Social Impact
Data category
Social dataThe data offers solutions for:
- Reporting: Impact
- Reporting: Other Regulations
- Social impact analysis and insight
Who are the data users?
- Corporates
- Financial institutions
Brief description of the data offering
GIST Impact offers a dedicated social impact assessment toolkit to calculate the positive and negative changes in well-being stemming from specific social programmes, volunteering, clean energy, sports and apprenticeships. This includes:
1. Social Return on Investment (SROI)
A monetised calculation of returns stemming from the programme, incorporating positive and negative externalities on specific beneficiaries as well as the wider society and environment. The calculation is place-based and goes beyond traditional models such as TOMs by accounting for the future value generated beyond the scope of the current programme (e.g. income increase following skill development).
2. Dedicated Platform - PowerSROI
A user-friendly platform for the input and analysis of data and results, built in partnership with Microsoft.
3. Programme-Specific Data Drill-Down
Additional insights including the age, gender, income deprivation and location of beneficiaries; as well as programme-specific analytics such as amount of carbon sequestered and carbon emissions avoided.
4. Flexible Data Input and Gap Filling
Programme-specific data input templates with the ability to gap-fill data using place-based, institutional-level databases (e.g. income, deprivation level) and to tweak key assumptions such as attribution, deadweight, displacement and drop off.
5. Benchmarking
Curated database of 2,200+ social programmes worldwide for improved performance evaluation and target-setting.
6. Standards and Regulations
Outputs aligned to the UN Sustainable Development Goals, the UK Social Value Model, and the Social Value standards.
Where and how do you source your data?
1. Direct from client and/or partner: programme-specific templates are filled in by the user, with clear demarcation of mandatory and voluntary fields.
2. Assumptions: users are able to tweak key assumptions such as attribution, deadweight, displacement and drop-off, with default settings drawn from proprietary research.
3. Institutional-level databases: used for data gap filling and calculation of social return on investment - including macroeconomic data such as population and income levels.
4. Proprietary impact pathways: research-driven, theory-of-change models linking impact drivers, to outcomes, to impacts for specific programmes.
Impact calculation is generated with context- and place-based specificity.
What is the cost for your data offering?
Please get in touch to discuss pricing.
Contacts
Mahima Sukhdev ([email protected])
