When should you consider a SmarterSelect alternative?
Consider Sopact as a SmarterSelect alternative when your team needs application evidence, review decisions and recurring participant or grantee data to work together. Start with the unresolved task: reading narrative against clear criteria, connecting follow-up to the right award or answering a reporting question without repeatedly preparing files.
Changing tools is not automatically an improvement. If SmarterSelect runs your intake and review well, first determine whether the remaining issue is a missing question, an unclear definition, a configuration problem or a genuinely different workflow requirement.
This guide serves scholarship, grant, fellowship and award teams comparing the work they will own after implementation. It explains how to evaluate assisted review, plan follow-up and test the proposed change on a complete program cycle.
What does SmarterSelect already provide?
SmarterSelect describes application building for nontechnical users, configurable workflows, communications, reviewer scoring and reporting. Its application-management materials also list automated scoring formulas, applicant surveys, roles and integrations. These capabilities are broader than simply storing an application. Product overview; application-management features.
A published customer example describes ongoing grant-recipient reporting within the system. It is therefore too broad to claim that SmarterSelect always ends at selection or cannot collect follow-up. The relevant question is how your particular reporting and analysis task would work. Source: SmarterSelect’s IAAQLI case study.
Also distinguish automated calculations from AI-assisted interpretation. A formula that totals evaluator scores and an analysis that examines supporting narrative perform different jobs. Ask each vendor to demonstrate the exact type of assistance you need.
Connect the application to the program you actually run
Suppose a fictional professional association selects early-career members for a development award. Applicants describe their proposed activity and goals. Reviewers assess the evidence. Selected members later submit progress updates explaining what they did and what changed.
If those stages use unrelated forms and exports, staff repeatedly reconstruct the relationship between the original proposal and the later result. An AI summary at the end may make the report read better while leaving that preparation work untouched.
Sopact’s approach connects collection and analysis around the relevant applicant, application, award and reporting period. Your team defines the criteria and reporting questions, then examines incoming evidence in that context. The opportunity is to reuse the information already established instead of rebuilding the program’s history for every question.
For the association, the application can provide the proposed activity and intended result. Award onboarding establishes the approved plan. Follow-up asks for evidence relevant to that plan, including an explanation when the activity changes. Reviewers can compare what was proposed, agreed and reported without treating them as the same thing.
A participant might apply again next year. Keep that new application distinct while linking it to the same person. Stable identity helps connect history; it does not mean overwriting earlier answers or automatically matching records with similar names.
Make review faster by making evidence easier to examine
Start with a rubric that tells a reviewer what evidence matters. “Quality” is too vague on its own. Explain what would support each assessment and what information should remain outside the score.
Use AI assistance to help locate and organize relevant passages, identify missing evidence and prepare findings for review. In a Sopact demonstration, ask the reviewer to open the source, question a suggested assessment and record the final judgment. A committee should not have to accept a generated score merely because it looks precise.
Test a concise application, a long application and an application with persuasive language but little relevant evidence. If your program accepts multiple languages or document formats, include those too. Measure errors and omissions alongside time spent reviewing.
Keep eligibility decisions separate from scored criteria. Missing proof may need clarification rather than rejection. Final awards remain the responsibility of authorized people, with their reasons preserved.
WATCH THE APPLICATION WORKFLOW
See how an AI-assisted review process is built
This demonstration is relevant to the intake and assessment part of your evaluation. Use your own criteria and representative application cases to test the approach; the video does not replace a full program pilot.
Use this in your evaluation: select one rubric criterion and two contrasting applications. Record the evidence you expect a reviewer to find and the uncertainty that should remain for human judgment.
Compare the tasks, not the number of features
| Task | Question for your current setup | What to test in Sopact |
|---|---|---|
| Build and maintain intake | Can the program owner change relevant forms and rules without unnecessary handoffs? | Have the intended owner make a routine change, test it and explain what it affects. |
| Assess narrative evidence | Which reading, scoring and clarification tasks remain manual or difficult? | Inspect source-linked assistance, omissions, reviewer corrections and final decision records. |
| Collect follow-up | How are updates connected to the right person, application and award? | Follow an award through several reporting periods, including a correction and missing update. |
| Prepare a program report | Where does staff still match, recode or reconstruct evidence? | Answer a real reporting question using defined measures and inspectable source evidence. |
| Maintain the next cycle | What has to be rebuilt when the program or reporting questions change? | Revise a definition, check historical comparability and document the change. |
SmarterSelect’s configurable tools may already address some of these tasks. Compare the demonstrated process and its maintenance requirements rather than assuming every capability is unique to one platform.
Plan useful follow-up before announcing the awards
For the association example, define the questions the next report must answer: whether the approved activity happened, what the recipient learned and what further support might help. Decide which answers need a structured measure and which need an explanation or supporting document.
Use a limited common set of fields for aggregation, with different follow-up questions where activities differ. A recipient attending a course and one undertaking a placement do not need identical forms, but both can identify the award, period and approved goal.
Keep nonresponse visible. A missing update is not evidence that the award failed, and it should not disappear from the reporting denominator. Retain the original response alongside any reviewed interpretation.
Do not turn a participant’s reported improvement into a causal claim about the award without an appropriate evaluation design. A connected history supports better questions and more transparent reporting; it does not settle every measurement issue.
Keep the program understandable after implementation
The people running the program should be able to explain the fields they collect, what the criteria mean and how a report includes or excludes records. That is the practical test of self-management.
Governance means deciding who may change those rules, who reviews a finding and who can see the underlying evidence. A reviewer’s confidential comment should not automatically appear in recipient-facing material. A donor summary may need approved findings without identifiable personal details.
Have the future owner demonstrate these responsibilities. A specialist-built prototype is useful, but it does not establish whether the team can maintain the next cycle.
Run a contained program evaluation
Use authorized records from one program rather than moving every application at once. Include a returning applicant, missing evidence, a changed proposal and follow-up from more than one period.
- Baseline the work. Record staff effort for preparation, review, clarification and reporting.
- Map the relationships. Distinguish people or organizations from their applications and awards.
- Verify transfer scope. Check which fields, files, evaluator records and history are available from your configuration.
- Test a checked assessment. Inspect the evidence behind suggestions and record human corrections.
- Produce a useful follow-up view. Show the right reporting periods, missing responses and unresolved questions.
- Make a change and export the result. Confirm that staff understand what changed and that the output remains usable outside the pilot.
Keep the current system authoritative for agreed operations while testing. A successful sample import is not proof that every attachment, historical event or permission has migrated. Resolve ambiguous matches instead of assuming an identifier has solved them.
Build the case around total program effort
Count recurring preparation and correction work, not only how quickly an initial assessment is generated. Include setup, training, matching, permissions, definition changes and reconciliation between retained systems.
The strongest evidence for adoption is a checked result produced with less repeated work, plus a process your team can run again. A shorter first draft is not enough if its sources must be reconstructed afterward.
If intake and review are already working, improve the specific gap. If the team needs a connected collection-and-analysis workflow, evaluate Sopact on that job. For a wider category comparison, see application management software. To plan the process first, use the Applications, awards & grants course.
Common questions
Does SmarterSelect support more than initial applications?
Yes. Its published materials describe configurable workflows, applicant surveys, reporting and integrations, and a customer example includes ongoing grant-recipient reporting. Examine the specific workflow you need rather than assuming follow-up is impossible.
Does automated scoring mean AI reads an essay?
Not necessarily. Automated scoring can refer to formulas and calculated totals. Ask how narrative evidence is interpreted, how sources are shown and how a person corrects the result.
What should we test before switching?
Test one complete program with representative exceptions. Include data transfer, review, follow-up, permissions, changes and usable exports, then compare the staff effort to reach a checked result.
Can Sopact connect application and follow-up evidence?
That is the workflow to evaluate: distinct application, award and period records connected to the right person or organization. Verify matching, definitions and access in your actual configuration.
