Active Economics & Business Public Health & Healthcare

The University of Essex and Foundation for Women's Health Research and Development KTP 24_25 R5

In plain English

AI plain-English summary

A women’s health charity is building the financial systems and evaluation tools it needs to turn unrestricted donations into a reliable, growing income stream. Most charities rely on restricted grants—money tied to specific projects—which limits their flexibility. This charity wants to shift toward unrestricted income: donations it can spend where the need is greatest, without strings attached. The problem is that attracting that kind of funding requires sophisticated impact evaluation and fundraising processes that many charities lack. This project will design and test those systems, creating a repeatable model for generating unrestricted revenue. If successful, the charity could become more financially resilient, able to respond quickly to emerging health needs rather than waiting for a grant to open up. The systems developed here could also be adapted by other women’s health organisations, strengthening the entire sector’s ability to operate independently. This is applied organisational research—it does not ask a fundamental scientific question, but it directly addresses a practical barrier to delivering better health outcomes.

View original technical description
To develop impact evaluation capabilities, and novel systems and processes, to maximise unrestricted income generation opportunities within a women's health charity

View the original record at the funder ↗

Related Research

Grants with similar aims, by meaning.

The University of Essex and Royal Hospital Chelsea KTP 24_25 R5
The University of Essex and Pursuing Independent Paths KTP 23_24 R3
The University of Essex and Community360 KTP 22_23 R4
The University of Essex and Iceni Projects Limited KTP 22_23 R4
Buckinghamshire New University and The Oasis Partnership UK KTP 22_23 R2

Original classification

Knowledge Transfer Partnership

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.