Nonprofit ERP for programme proposals and delivery fees

Explain the services behind a sponsored programme
Quote a community digital-skills workshop with facilitation hours, participant learning packs and delivery coordination as separate lines. The native proposal viewer shows the programme client, reference and amount, with quantities and rates in Details. Both teams can review the contracted services and understand how the programme delivery fee is formed.

Give volunteer and material preparation clear ownership
Assign volunteer briefing, learning-pack checks and delivery-summary preparation as ordinary tasks. Each carries a work description, owner, priority and due date, making responsibility visible across the team. Coordinators update the board as people perform the work and can open Task Details to inspect what is still needed for the programme.

Review programme invoices against agreed delivery stages
Use the programme service order’s Billing Plan for preparation approval, workshop delivery and the final delivery summary. The progress invoice identifies the selected milestone, work package, description and amount. These are fees for contracted programme services, and the office chooses what to invoice under the agreement independently of task-board status.

Share the service proposal for sponsor review
Prepare the programme proposal with a document language, expiry date and optional signature request in Share settings. Review the sponsor’s commercial reference and the service descriptions before sharing. These native controls support discussion of the contracted delivery scope, giving the sponsor and programme coordinator the same itemized proposal to review.

Give programme delivery a clear commercial record.
Nonprofit ERP for Programme Proposals & Delivery | DNA
- Organize sponsored programme proposals, preparation tasks and staged service invoices in DNA ERP. Review contracted delivery fees and clear sponsor documents.
- Utilize structured and semi-structured data storage
- Analyze data using graph, spatial, and machine learning engines
- Start with the basic trial using sample data; no set-up required






