NGO Grant Automation Efficiency
This dataset provides detailed metrics on the efficiency of automated grant application workflows in small and medium NGOs, including time savings, bottlenecks resolved, and success rates. It enables operations teams to quantify the impact of digital transformation, identify process improvements, and benchmark automation ROI across different grant programs. The dataset is ideal for performance tracking, process optimization, and strategic decision-making in the nonprofit sector.
Sample rows
preview · 8 of 60 rows · all 19 columns| workflow_idstring | workflow_automation_stagestring | success_ratefloat | bottlenecks_resolvedboolean | ngo_idstring | ngo_namestring | grant_program_namestring | application_period_startdate | application_period_enddate | total_applications_processedinteger | manual_processing_time_hoursfloat | automated_processing_time_hoursfloat | time_saved_hoursfloat | bottlenecks_identifiedstring | error_ratefloat | roi_percentagefloat | feedback_collectedboolean | user_feedback_summarystring | date_recordeddatetime |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| WF-001-A | application intake | 93.2 | true | NGO-1001 | Hope Alliance | Community Health Initiative | 2023-01-10 | 2023-02-25 | 53 | 122 | 34.5 | 87.5 | High volume manual data entry | 6.1 | 67.5 | true | Staff reported much faster processing and reduced overtime. | 2023-03-01T10:22:11 |
| WF-002-B | review | 89.7 | true | NGO-1002 | Green Steps | Urban Greening Fund | 2022-11-05 | 2022-12-30 | 28 | 58 | 21.3 | 36.7 | Delayed approvals due to manual review | 10 | 54.2 | true | Review team noted reduced backlog. | 2023-01-05T09:11:45 |
| WF-003-C | approval | 91 | true | NGO-1003 | WaterWorks Initiative | Clean Water Project | 2023-05-01 | 2023-06-15 | 35 | 73.5 | 31.2 | 42.3 | Lengthy approval cycles | 7.8 | 60.9 | false | blank | 2023-06-20T15:04:53 |
| WF-004-D | reporting | 97.6 | true | NGO-1001 | Hope Alliance | Education Empowerment | 2022-09-02 | 2022-10-18 | 41 | 49.3 | 18.1 | 31.2 | Manual report consolidation | 1.5 | 70 | true | Reporting is more accurate and timely. | 2022-10-20T11:48:36 |
| WF-005-E | application intake | 88.3 | true | NGO-1004 | BrightFutures | Youth Leadership Grant | 2023-03-12 | 2023-05-05 | 65 | 140 | 41 | 99 | Duplicate applications were common | 10.9 | 72.8 | true | Duplicates are now flagged automatically. | 2023-05-07T14:13:19 |
| WF-006-F | review | 85.5 | true | NGO-1005 | SafeShelter | Emergency Housing Support | 2022-12-01 | 2023-01-15 | 21 | 39.2 | 16.8 | 22.4 | Manual checking of eligibility | 14.1 | 47.5 | false | blank | 2023-01-18T17:34:07 |
| WF-007-G | approval | 94.4 | true | NGO-1006 | EcoGuard | Climate Action Fund | 2023-04-10 | 2023-05-25 | 33 | 62 | 27.2 | 34.8 | Slow manual document verification | 5.1 | 55.2 | true | Document checks much faster. | 2023-05-28T13:27:42 |
| WF-008-H | reporting | 96.2 | true | NGO-1007 | Global Literacy Network | Adult Literacy Program | 2022-08-15 | 2022-09-30 | 48 | 61.8 | 23.6 | 38.2 | Complicated manual data aggregation | 2.3 | 68.4 | true | Reporting dashboards are now available. | 2022-10-02T08:16:22 |
| WF-009-I | application intake | 92.5 | true | NGO-1002 | Green Steps | Tree Planting Scheme | 2023-02-01 | 2023-03-16 | 39 | 82.5 | 27.8 | 54.7 | Time-consuming manual sorting | 7.1 | 61.3 | false | blank | 2023-03-19T12:03:55 |
| WF-010-J | review | 86 | false | NGO-1008 | SafeHands Foundation | Women Safety Initiative | 2023-05-15 | 2023-06-30 | 26 | 44 | 19.5 | 24.5 | blank | 13 | 40.5 | true | Some bottlenecks remain at review stage. | 2023-07-02T09:41:38 |
| WF-011-K | approval | 90 | true | NGO-1005 | SafeShelter | Night Shelter Grant | 2023-01-20 | 2023-02-28 | 15 | 26 | 8.9 | 17.1 | Manual eligibility checks | 9.5 | 38.9 | true | Approval process more streamlined. | 2023-03-03T18:22:51 |
| WF-012-L | reporting | 98.1 | true | NGO-1006 | EcoGuard | Ocean Cleanup Grant | 2022-06-10 | 2022-07-25 | 19 | 32.5 | 12.3 | 20.2 | Manual result compilation | 0.7 | 48.2 | false | blank | 2022-07-28T13:55:34 |
| WF-013-M | application intake | 94.9 | true | NGO-1007 | Global Literacy Network | School Library Fund | 2023-06-01 | 2023-07-15 | 24 | 51 | 17.2 | 33.8 | Manual entry of library lists | 4.5 | 56 | true | Library lists now uploaded directly. | 2023-07-17T16:10:21 |
| WF-014-N | review | 92.1 | true | NGO-1009 | CareConnect | Mental Health Support | 2022-10-01 | 2022-11-20 | 38 | 70.4 | 29.6 | 40.8 | Manual scoring of applications | 7 | 59.7 | true | Scoring now automated. | 2022-11-22T11:38:12 |
| WF-015-O | approval | 87.5 | false | NGO-1010 | EmpowerWomen | Microenterprise Grant | 2023-02-18 | 2023-03-21 | 17 | 29.7 | 12 | 17.7 | blank | 12 | 44.1 | false | blank | 2023-03-24T13:02:17 |
| WF-016-P | reporting | 95.7 | true | NGO-1003 | WaterWorks Initiative | Sanitation Improvement | 2022-07-10 | 2022-08-24 | 44 | 53.2 | 20.4 | 32.8 | Manual reporting caused delays | 3.8 | 65.4 | true | Reports sent on time. | 2022-08-28T10:47:09 |
| WF-017-Q | application intake | 90.3 | true | NGO-1011 | FoodBridge | School Meals Grant | 2023-04-02 | 2023-05-16 | 60 | 127 | 35.5 | 91.5 | Manual verification of student lists | 9 | 71.3 | true | Student lists now uploaded directly. | 2023-05-20T14:30:04 |
| WF-018-R | review | 91.8 | true | NGO-1004 | BrightFutures | Scholarship Grant | 2022-11-18 | 2022-12-29 | 23 | 41.5 | 17.1 | 24.4 | Manual eligibility verification | 7.6 | 50.7 | false | blank | 2023-01-02T09:55:12 |
| WF-019-S | approval | 87.2 | true | NGO-1012 | Rights4All | Legal Aid Fund | 2023-03-20 | 2023-04-28 | 32 | 58 | 22.7 | 35.3 | Manual case assignment | 12.2 | 49.8 | true | Cases now assigned automatically. | 2023-05-01T17:42:39 |
| WF-020-T | reporting | 96.8 | true | NGO-1001 | Hope Alliance | Nutrition Support Grant | 2023-08-05 | 2023-09-20 | 37 | 48.9 | 18.7 | 30.2 | Manual collation of nutrition records | 2.7 | 66.9 | true | Nutrition reports now automated. | 2023-09-22T11:58:21 |
What the 60 rows show
from the 60-row sampleReporting (workflow automation stage) stands out: mean success_
- 93%bottlenecks_
resolved = true - 91.8median success_
rate - 41.5median total_
applications_ processed - 49.9median manual_
processing_ time_ hours - 18.3median automated_
processing_ time_ hours - 31.7median time_
saved_ hours
Median 91.8, from 84.7 to 98.5.
- string 7
- integer 1
- float 6
- date 2
- datetime 1
- boolean 2
Columns
19 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 7 columns | |||
workflow_id | string | Unique identifier for each grant application automation workflow instance.unique | WF-001-A |
ngo_id | string | Unique identifier for the NGO utilizing the workflow. | NGO-1001 |
ngo_name | string | Official name of the NGO. | Hope Alliance |
grant_program_name | string | Name of the grant program for which the workflow is used. | Urban Greening Fund |
workflow_automation_stage | string | Stage of the grant process automated (e.g., application intake, review, reporting).application intake · review · approval · reporting · other | application intake |
bottlenecks_identified | string | Description of process bottlenecks resolved by automation.optional | Lengthy approval cycles |
user_feedback_summary | string | Summary of user or staff feedback on the automation process.optional | Scoring now automated. |
| Numbers 7 columns | |||
total_applications_processed | integer | Total number of grant applications processed by the workflow during the period.0 or more | 53 |
manual_processing_time_hours | float | Estimated total hours required for manual processing before automation.0 or more | 122 |
automated_processing_time_hours | float | Total hours spent processing applications after automation.0 or more | 34.5 |
time_saved_hours | float | Total hours saved due to workflow automation (manual - automated).0 or more | 87.5 |
success_rate | float | Percentage of applications successfully processed without manual intervention (0-100).0 to 100 | 93.2 |
error_rate | float | Percentage of applications with errors or requiring manual correction (0-100).0 to 100 | 6.1 |
roi_percentage | float | Estimated return on investment from automation as a percentage (0-100).0 to 100 · optional | 67.5 |
| Dates and times 3 columns | |||
application_period_start | date | Start date of the grant application period. | 2023-01-10 |
application_period_end | date | End date of the grant application period. | 2023-02-25 |
date_recorded | datetime | Timestamp when this workflow efficiency record was created. | 2023-03-01T10:22:11 |
| True or false 2 columns | |||
bottlenecks_resolved | boolean | Indicates if key bottlenecks were resolved by automation. | true |
feedback_collected | boolean | Indicates if user feedback on the workflow was collected. | true |
Use it for
A technology dashboard
The bottlenecks_
resolved rate and success_ rate by workflow_ automation_ stage. Excel, Power BI or Tableau. Why do the 13 reporting rows have a mean success_
rate of 96.0? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Workflows60WF-001-A93.2applicat…WF-002-B89.7reviewWF-010-J86review
A software demo
Believable workflows with ngo_
id, ngo_ name and grant_ program_ name to fill a screen in front of a buyer.
This dataset60 rows19 columns
Yours10,000 rows19 columns
blueprint · ngo-grant-automation-efficiency
Behind this dataset
Same schema. As many rows as you need.
These 60 rows came out of a blueprint — 19 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
Rules it was built with
- Each row represents one completed grant application workflow.
- Includes fields for time-to-completion, automation steps success/failure, manual interventions required, and funding outcome.
- Only applications processed through digital automation software are included.
- Automation bottleneck cause must be categorized by predefined workflow stages.
- Funding outcome must be marked as 'Success', 'Partial', or 'Denied'.
Open the blueprint in Data Factory
1 credit per row. New accounts start with 25 free credits.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- ngo-grant-automation-efficiency