Problem / Need:
Customers with established internal evaluation frameworks need the ability to configure scoring and weighting to match their unique methodologies. Currently, Responsive’s fixed scoring model (e.g. default 0–10 scale, static weighting) forces teams to adapt their evaluation process to the platform, rather than configuring the platform to align with their process.
This limitation creates confusion, inefficiency, and inaccurate total scores that don’t reflect real evaluation priorities.
Impact:
Because the system doesn’t support dynamic weighting or flexible scoring logic, clients experience:
- Misaligned results: Final total scores (e.g., “625 points”) don’t correlate with their internal logic or weighting standards.
- Manual work: Admins must manually edit question weights, simulate section weighting, and calculate totals offline in Excel.
- Evaluator confusion: Evaluators are instructed to ignore the total score because it doesn’t reflect the true weighted result.
- Error risk: Repetitive manual adjustments increase the chance of inconsistent scoring setup across evaluations.
Proposed Solution:
Enable full customization of scoring and weighting at both the section and question levels, including:
- Assigning custom weights or priorities per question and section that accurately reflect internal scoring models.
- Easily marking non-scored questions (e.g., informational fields) as 0% weight without editing each one individually.
- Supporting custom scoring scales (e.g., 0–5, 0–7, 0–10) configurable per evaluation or per section.
- Allowing admins to save and reuse custom scoring templates for consistency across evaluations.
Value / Benefits:
- Aligns Responsive scoring logic with each organization’s established internal methodology.
- Reduces manual configuration time and scoring errors.
- Improves evaluator understanding by displaying meaningful, interpretable total scores.
- Enhances transparency and credibility of results for internal stakeholders.
- Streamlines setup and increases adoption among enterprise customers with complex scoring models.
