SkillMedev Grant Proposal Writer
The full proposal is where invited organizations lose grants they should win: national statistics standing in for local need, outcomes that are really activities, an evaluation plan the organization cannot execute, and a budget that does not match the narrative. Program officers read for exactly these four failures. This skill builds the proposal in dependency order so each section is forced to agree with the others. It is third in the grants pipeline: it starts from the LOI that grant-loi-writer got invited, and its numbers must match that LOI exactly - a proposal that contradicts its own LOI reads as an organization that does not know its numbers.
Work the example organization throughout: Bright Futures Tutoring, a youth-education nonprofit with a $420,000 annual budget, 3 staff, serving 250 students, invited by the Hearthstone Foundation to propose for $75,000 to expand to 325 students.
Operating procedure
Build in this order - logic model before objectives, objectives before evaluation, activities before budget - because each section is derived from the previous one, and writing them independently is how contradictions get in.
Step 1: Fix the baseline numbers
Copy the LOI's numbers as immutable: ask amount, duration, what it buys, scale, headline outcome. Collect the rest: program costs by line, staff roles and salaries allocated to the program, outcome data from the last two years with sources, and the local need data. Label every guessed number as a guess and resolve it before submission.
Step 2: Write the need statement with local data
The rule: never national statistics alone. National data may frame the problem in one sentence; the case must stand on local numbers - school-district reading scores, county poverty rates, your own waitlist. Bright Futures: "38 percent of third-graders in Riverton County read at grade level (district assessment data), against 61 percent statewide. Bright Futures' waitlist has held above 40 students for three consecutive terms." A funder giving locally wants proof you know the community, and your own waitlist is need data no one else has. Describe the problem as the community's, never as the organization's need for money - funders fund solutions to problems, not organizations' budget gaps.
Step 3: Build the logic model
Four columns, real numbers in every cell, arrows only where you can defend the causal claim:
- Inputs: what goes in (dollars, staff, sites, curriculum).
- Activities: what the organization does with the inputs.
- Outputs: countable units of delivery (sessions held, students enrolled).
- Outcomes: the change in people (reading levels gained, grade promotion). Outputs are what you did; outcomes are what changed. Conflating them is the most common logic-model failure.
The worked artifact below is Bright Futures' model. Its outcome numbers are canonical for the pack: impact-report-builder and donor-communications cite the same 72 percent reading-gain figure, and nonprofit-board-pack tracks it as a program KPI.
Step 4: Convert outcomes to SMART objectives
Each priority outcome becomes one objective: specific, measurable, achievable, relevant, time-bound. Achievable means anchored to your own baseline - improve on last year's actuals by a defensible increment, not a round aspirational number. Bright Futures: "By June 30, at least 70 percent of the 325 enrolled students will gain one or more grade levels in reading, as measured by fall-to-spring benchmark assessment." Three to five objectives; more signals a program that has not chosen its priorities.
Step 5: Write the evaluation plan matched to capacity
The rule: promise only the measurement a 3-person team can actually run. Do not promise an RCT, a comparison group, or an external evaluator on a $75,000 grant - a program officer knows what those cost (external evaluation alone typically runs 5-10 percent of a project budget) and reads the overpromise as inexperience. Right-sized for Bright Futures: pre/post benchmark assessments already administered by partner schools, attendance tracking, teacher feedback surveys twice a year, and a named staff member (the program director) who owns data collection. State who collects what, when, and how results feed back into the program.
Step 6: Build the budget and narrative with line-to-activity tracing
The alignment rule: every budget line traces to a named activity in the logic model, and every activity has a home in the budget. Orphan lines (money with no activity) and unfunded activities (work with no money) are the two flags reviewers circle. Format the narrative as line → amount → activity it enables → basis of estimate. Bright Futures' $75,000: fourth tutor salary and benefits $46,000 (delivers tutoring at Site 2 - Activity 1); Site 2 rent and utilities $12,000 (Activity 1); curriculum licenses and materials for 75 additional students $7,500 (Activity 1); assessment and data tools $3,500 (Activity 3); allocated program-director supervision $6,000 (Activities 1-3). Total $75,000. Keep any admin/overhead allocation within the funder's stated cap, commonly 10-15 percent for project grants.
Step 7: Answer sustainability without fiction
The question means "what happens when our money ends," and the credible patterns are: diversification (the expansion joins a funding mix - for Bright Futures, individual donors and two other pending foundation asks from the grant-prospect-researcher pipeline); earned or committed revenue (school-district contracts under discussion); demonstrated renewal history (funders who have renewed before); and cost-step-down (year-one startup costs like curriculum licenses do not recur). Never promise "the program will be self-sustaining" without a mechanism - reviewers have read that sentence a thousand times and believe it zero.
Step 8: Assemble and cross-check
Assemble in the funder's required order and run the consistency pass: LOI numbers = proposal numbers; every objective appears in the evaluation plan; every budget line traces to an activity; page and attachment limits respected.
Worked artifact: Bright Futures logic model
LOGIC MODEL - Bright Futures Tutoring reading expansion (12 months)
INPUTS ACTIVITIES OUTPUTS OUTCOMES
$75,000 Hearthstone A1. Twice-weekly small- 5,200 tutoring sessions 70%+ of students gain
grant + $34,000 existing group tutoring at 2 delivered (325 students 1+ grade level in
program funds sites, 32 weeks x 32 wks x 0.5 avg) reading (baseline: 72%
of 250 students last yr)
4 tutors (3.0 existing A2. Family engagement: 325 students enrolled;
+ 1.0 new FTE) + 2 family nights per 150+ family-night 85%+ of students
program director (0.2) site per year attendances promoted to next grade
on schedule
2 school sites A3. Benchmark assessment 650 assessments scored
(1 existing + 1 new) fall and spring; teacher (2 per student); 2 Waitlist reduced from
surveys 2x/year survey rounds 40+ to under 15
Licensed curriculum
for 325 students
Read across, not down: inputs fund activities, activities produce countable outputs, outputs drive the outcome claims - and the outcome column is anchored to last year's actual (72 percent of 250 students), which is what makes "70 percent of 325" achievable rather than aspirational.
Deliverable
A submission-ready proposal: local-data need statement, the logic model above, 3-5 SMART objectives, a capacity-matched evaluation plan with a named data owner, a budget narrative with every line traced to an activity, a mechanism-based sustainability answer, and a completed consistency pass against the LOI.
Do NOT
- Do not rest the need statement on national statistics alone; local data is the proof of community knowledge.
- Do not put outputs in the outcome column - sessions delivered is not students improved.
- Do not promise evaluation beyond staff capacity; an RCT promise on a $75,000 grant reads as inexperience, not rigor.
- Do not leave orphan budget lines or unfunded activities; reviewers reconcile the two documents.
- Do not answer sustainability with "we will become self-sustaining" absent a mechanism.
- Do not let any number drift from the LOI that earned the invitation.
Quality bar
- Need statement cites at least two local data points with sources.
- Every logic-model cell has a real number; outcome baselines come from actual prior-year data.
- Every objective is measured in the evaluation plan; the plan names its data owner.
- Budget totals the exact ask; every line names its activity; overhead within the funder's cap.
- Numbers agree with grant-loi-writer, impact-report-builder, and nonprofit-board-pack.
Escalation
Upstream: unqualified funders go back through grant-prospect-researcher; no LOI yet means grant-loi-writer first. After an award, the outcome numbers promised here become the reporting baseline in impact-report-builder, and the award updates the pipeline figures in nonprofit-board-pack. For government proposals with federal compliance requirements (indirect cost rate agreements, single audit), engage a grants professional; this skill covers private foundation proposals and is not legal or accounting advice.