feedback-summarization

Feedback Summarization

Overview

This skill summarizes feedback collected from agile ceremonies, stakeholder surveys, and project reviews within ServiceNow SPM. It covers:

Extracting feedback from sprint retrospective records and comments in rm_sprint
Analyzing sprint review notes and stakeholder assessments from asmt_assessment_instance
Identifying recurring themes across multiple feedback sources
Categorizing feedback into actionable themes (process, tools, communication, quality, workload)
Generating prioritized action items from aggregated feedback
Tracking action item resolution across sprints for continuous improvement

When to use: When scrum masters need to summarize retrospective feedback, when project managers want to aggregate stakeholder sentiment, when leadership needs a cross-team view of recurring improvement themes, or when preparing for quarterly planning sessions.

Value proposition: Transforms scattered feedback into structured insights, reveals cross-sprint patterns that individual retros miss, and creates accountability for improvement actions by tracking them across iterations.

Prerequisites

Plugins: com.snc.sdlc.agile.2.0 (Agile Development 2.0), com.snc.assessment (optional, for surveys)
Roles: scrum_master, scrum_admin, pa_admin, or admin
Access: Read access to rm_sprint, rm_story, asmt_assessment_instance, and journal field tables
Knowledge: Understanding of agile ceremonies, retrospective formats, and the team's sprint cadence

Procedure

Step 1: Gather Sprint Retrospective Data

Retrieve retrospective feedback from sprint records and associated journal entries.

Using MCP (Claude Code/Desktop):

Tool: SN-Query-Table
Parameters:
  table_name: rm_sprint
  query: release.product.sys_id=[product_sys_id]^state=3^ORDERBYDESCend_date
  fields: sys_id,number,short_description,start_date,end_date,state,story_points,capacity,retrospective_notes,velocity
  limit: 6

Using REST API:

GET /api/now/table/rm_sprint?sysparm_query=release.product.sys_id=[product_sys_id]^state=3^ORDERBYDESCend_date&sysparm_fields=sys_id,number,short_description,start_date,end_date,state,story_points,capacity,retrospective_notes,velocity&sysparm_limit=6&sysparm_display_value=true

Retrieve journal/work notes for detailed feedback:

Tool: SN-Query-Table
Parameters:
  table_name: sys_journal_field
  query: name=rm_sprint^element=work_notes^element_id=[sprint_sys_id]
  fields: value,sys_created_on,sys_created_by
  limit: 30
  order_by: -sys_created_on

Step 2: Collect Stakeholder Survey Responses

Gather assessment data from sprint review or stakeholder surveys.

Using MCP:

Tool: SN-Query-Table
Parameters:
  table_name: asmt_assessment_instance
  query: metric_type.nameLIKEsprint review^ORmetric_type.nameLIKEstakeholder^state=complete^taken_on>=javascript:gs.monthsAgoStart(3)
  fields: sys_id,number,metric_type,user,user.department,taken_on,percent,state,trigger_id
  limit: 50
  order_by: -taken_on

Get individual question responses:

Tool: SN-Query-Table
Parameters:
  table_name: asmt_assessment_instance_question
  query: instance.metric_type.nameLIKEsprint review^instance.taken_on>=javascript:gs.monthsAgoStart(3)^metric.datatype=string^string_valueISNOTEMPTY
  fields: string_value,metric.name,metric.question,instance.taken_on,instance.user.name
  limit: 100
  order_by: -instance.taken_on

Using REST API:

GET /api/now/table/asmt_assessment_instance_question?sysparm_query=instance.metric_type.nameLIKEsprint%20review^metric.datatype=string^string_valueISNOTEMPTY^instance.taken_on>=javascript:gs.monthsAgoStart(3)&sysparm_fields=string_value,metric.name,instance.taken_on,instance.user.name&sysparm_limit=100&sysparm_display_value=true

Step 3: Analyze Sprint Performance Metrics

Correlate feedback with actual sprint performance data.

Using MCP:

Tool: SN-Execute-Background-Script
Parameters:
  description: Analyze sprint performance metrics for feedback context
  script: |
    var productId = '[product_sys_id]';
    var sprintMetrics = [];

    var sprint = new GlideRecord('rm_sprint');
    sprint.addQuery('release.product.sys_id', productId);
    sprint.addQuery('state', 3); // Complete
    sprint.orderByDesc('end_date');
    sprint.setLimit(6);
    sprint.query();

    while (sprint.next()) {
      var metrics = {
        sprint: sprint.short_description.toString(),
        number: sprint.number.toString(),
        dates: sprint.start_date.getDisplayValue() + ' to ' + sprint.end_date.getDisplayValue(),
        planned_points: parseInt(sprint.capacity) || 0,
        completed_points: parseInt(sprint.story_points) || 0,
        velocity: 0,
        stories: { total: 0, completed: 0, carried_over: 0 },
        defects_found: 0
      };

      metrics.velocity = metrics.planned_points > 0
        ? Math.round((metrics.completed_points / metrics.planned_points) * 100) : 0;

      // Story completion
      var stories = new GlideAggregate('rm_story');
      stories.addQuery('sprint', sprint.sys_id);
      stories.addAggregate('COUNT');
      stories.groupBy('state');
      stories.query();
      while (stories.next()) {
        var count = parseInt(stories.getAggregate('COUNT'));
        metrics.stories.total += count;
        var state = parseInt(stories.state);
        if (state >= 3) metrics.stories.completed += count;
        else metrics.stories.carried_over += count;
      }

      // Defects
      var defects = new GlideAggregate('rm_story');
      defects.addQuery('sprint', sprint.sys_id);
      defects.addQuery('classification', 'Defect');
      defects.addAggregate('COUNT');
      defects.query();
      if (defects.next()) metrics.defects_found = parseInt(defects.getAggregate('COUNT'));

      sprintMetrics.push(metrics);
    }

    gs.info(JSON.stringify(sprintMetrics, null, 2));

Step 4: Identify Themes from Feedback

Analyze collected feedback to extract recurring themes.

Using MCP:

Tool: SN-Execute-Background-Script
Parameters:
  description: Categorize feedback into themes
  script: |
    var sprintIds = ['sprint_sys_id_1', 'sprint_sys_id_2', 'sprint_sys_id_3'];
    var themes = {
      process: { count: 0, items: [] },
      tools: { count: 0, items: [] },
      communication: { count: 0, items: [] },
      quality: { count: 0, items: [] },
      workload: { count: 0, items: [] },
      positive: { count: 0, items: [] },
      other: { count: 0, items: [] }
    };

    // Keyword mapping for theme detection
    var keywords = {
      process: ['standup', 'ceremony', 'planning', 'refinement', 'workflow', 'process', 'methodology', 'sprint', 'retro'],
      tools: ['jira', 'servicenow', 'jenkins', 'pipeline', 'tooling', 'environment', 'infrastructure', 'slow', 'broken'],
      communication: ['communication', 'unclear', 'alignment', 'stakeholder', 'meeting', 'update', 'inform', 'silos'],
      quality: ['bug', 'defect', 'testing', 'review', 'code review', 'quality', 'regression', 'production issue'],
      workload: ['overloaded', 'capacity', 'bandwidth', 'too many', 'burnout', 'deadline', 'overtime', 'scope creep'],
      positive: ['great', 'improved', 'well done', 'excellent', 'good job', 'kudos', 'thank', 'appreciate']
    };

    sprintIds.forEach(function(sprintId) {
      var journal = new GlideRecord('sys_journal_field');
      journal.addQuery('name', 'rm_sprint');
      journal.addQuery('element_id', sprintId);
      journal.addQuery('element', 'work_notes');
      journal.query();

      while (journal.next()) {
        var text = journal.value.toString().toLowerCase();
        var categorized = false;

        for (var theme in keywords) {
          keywords[theme].forEach(function(kw) {
            if (text.indexOf(kw) >= 0 && !categorized) {
              themes[theme].count++;
              themes[theme].items.push({
                text: journal.value.toString().substring(0, 200),
                sprint: sprintId,
                date: journal.sys_created_on.getDisplayValue()
              });
              categorized = true;
            }
          });
        }

        if (!categorized) {
          themes.other.count++;
          themes.other.items.push({
            text: journal.value.toString().substring(0, 200),
            sprint: sprintId
          });
        }
      }
    });

    gs.info(JSON.stringify(themes, null, 2));

Step 5: Generate Action Items

Create trackable action items from identified themes.

Using MCP:

Tool: SN-Create-Record
Parameters:
  table_name: rm_story
  fields:
    short_description: "Retro Action: Implement automated regression test suite for checkout flow"
    description: |
      ## Source
      Sprint retrospective feedback across Sprints 23-25

      ## Theme
      Quality - recurring defects in checkout flow detected late in sprint

      ## Feedback Summary
      - Sprint 23: "We found 3 production bugs in checkout that should have been caught"
      - Sprint 24: "Still seeing regression issues in payment processing"
      - Sprint 25: "Need automated tests before we add more features"

      ## Action
      Create ATF test suite covering all checkout scenarios. Target: 80% coverage of critical paths.

      ## Success Criteria
      - ATF suite running in CI/CD pipeline
      - Zero checkout regressions for 2 consecutive sprints
    classification: Improvement
    priority: 2
    state: -6
    epic: [improvement_epic_sys_id]
    sprint: [next_sprint_sys_id]
    story_points: 8
    product: [product_sys_id]

Step 6: Generate the Feedback Summary Report

Compile all analysis into a comprehensive summary.

Using MCP:

Tool: SN-Add-Work-Notes
Parameters:
  table_name: rm_sprint
  sys_id: [current_sprint_sys_id]
  work_notes: |
    === FEEDBACK SUMMARY REPORT ===
    Product: Customer Portal
    Period: Sprints 23-25 (Feb 3 - Mar 14, 2026)
    Sources: 3 sprint retros, 12 stakeholder surveys, 45 work note entries

    SPRINT PERFORMANCE TREND:
    - Sprint 23: 34/40 pts completed (85% velocity)
    - Sprint 24: 38/40 pts completed (95% velocity) - Improved
    - Sprint 25: 32/45 pts completed (71% velocity) - Declined (scope increase)

    TOP THEMES (by frequency):
    1. QUALITY (18 mentions) - Recurring defects in checkout flow, need for automated testing
    2. WORKLOAD (14 mentions) - Scope creep in Sprint 25, team overloaded with support tickets
    3. COMMUNICATION (11 mentions) - Stakeholder requirements changing mid-sprint
    4. TOOLS (7 mentions) - CI/CD pipeline reliability issues causing deployment delays
    5. POSITIVE (9 mentions) - Improved sprint planning, better story refinement

    RECURRING ISSUES (appeared in 2+ sprints):
    - Checkout regression bugs (Sprints 23, 24, 25)
    - Mid-sprint scope changes (Sprints 24, 25)
    - Environment instability (Sprints 23, 25)

    ACTION ITEMS GENERATED:
    1. [P2] Create automated regression suite for checkout (8 pts) - Sprint 26
    2. [P2] Implement change freeze policy for mid-sprint scope (3 pts) - Sprint 26
    3. [P3] Investigate and stabilize CI/CD pipeline (5 pts) - Sprint 27
    4. [P3] Establish support ticket rotation to protect sprint capacity (2 pts) - Sprint 26

    STAKEHOLDER SENTIMENT:
    - Overall satisfaction: 72% (down from 78% last quarter)
    - Key concern: "Delivery predictability has decreased"
    - Key positive: "Quality of delivered features has improved"

    PREVIOUS ACTION ITEM STATUS:
    - [DONE] Improve story refinement process - Completed Sprint 24
    - [IN PROGRESS] Reduce meeting overhead - 50% reduction achieved
    - [NOT STARTED] Cross-training initiative - Deferred to Q2

    RECOMMENDATIONS:
    1. Protect sprint scope with formal change request process
    2. Invest in test automation to reduce manual regression effort
    3. Address stakeholder concern about predictability with revised velocity baseline

Step 7: Track Action Items Across Sprints

Monitor resolution of feedback-generated action items.

Using MCP:

Tool: SN-Query-Table
Parameters:
  table_name: rm_story
  query: classification=Improvement^epic=[improvement_epic_sys_id]
  fields: number,short_description,state,sprint,story_points,assigned_to,priority,sys_updated_on
  limit: 25
  order_by: -sys_created_on

Using REST API:

GET /api/now/table/rm_story?sysparm_query=classification=Improvement^epic=[improvement_epic_sys_id]&sysparm_fields=number,short_description,state,sprint,story_points,assigned_to,priority&sysparm_limit=25&sysparm_display_value=true

Tool Usage

MCP Tools Reference

Tool	When to Use
`SN-Query-Table`	Query sprints, stories, assessments, and journal entries
`SN-Get-Record`	Retrieve specific sprint or assessment details
`SN-Natural-Language-Search`	Find feedback by keyword or topic description
`SN-Create-Record`	Create action items as improvement stories
`SN-Execute-Background-Script`	Aggregate metrics, categorize themes, batch analysis
`SN-Add-Work-Notes`	Post summary reports to sprint or project records

REST API Reference

Endpoint	Method	Purpose
`/api/now/table/rm_sprint`	GET	Query sprint records and retrospective data
`/api/now/table/rm_story`	GET/POST	Query stories and create action items
`/api/now/table/asmt_assessment_instance`	GET	Retrieve stakeholder survey responses
`/api/now/table/asmt_assessment_instance_question`	GET	Get individual survey question answers
`/api/now/table/sys_journal_field`	GET	Read work notes and comments
`/api/now/table/rm_release`	GET	Release-level feedback aggregation

Best Practices

Collect feedback consistently: Use the same retrospective format each sprint so themes can be compared across periods
Categorize before summarizing: Group feedback into themes first, then summarize; raw lists are less actionable
Track action items formally: Create stories or tasks for every action item; verbal commitments are forgotten
Close the loop: Start each retro by reviewing status of previous action items before collecting new feedback
Quantify where possible: "3 production bugs" is more actionable than "quality issues"
Separate observation from recommendation: Clearly distinguish what happened (theme) from what to do about it (action)
Aggregate across teams: Cross-team theme analysis reveals systemic issues that individual team retros miss
Limit action items per sprint: Focus on 2-3 improvement actions per sprint; too many dilutes focus

Troubleshooting

Retrospective Notes Field Is Empty

Cause: Team may store retro feedback in work notes, comments, or external tools rather than the retrospective_notes field Solution: Query sys_journal_field for the sprint record to find work note entries. Check if the team uses an external retro tool that needs integration.

Survey Responses Not Linked to Sprint

Cause: Assessment instances may not have the trigger_id set to the sprint sys_id Solution: Match surveys by date range (survey taken_on within sprint start/end dates) rather than direct reference.

Theme Categorization Misses Feedback

Cause: Keyword-based categorization is limited; feedback may use different terminology Solution: Expand the keyword lists based on your team's language. Consider using NLU or text analysis APIs for more accurate categorization.

Action Items Not Being Completed

Cause: Action items are created but not prioritized or assigned in the next sprint Solution: Add action item review as a mandatory step in sprint planning. Set the sprint field to the next sprint when creating the improvement story.

Examples

Example 1: Single Sprint Retro Summary

Input: "Summarize the retrospective from Sprint 25"

Process: Run Steps 1, 3, and 6 for the specific sprint to generate a focused summary with themes, metrics, and 2-3 action items.

Example 2: Quarterly Improvement Trend

Input: "What improvement themes have recurred over the last quarter?"

Process: Run Steps 1-4 across all sprints in the quarter, then identify themes appearing in 3+ sprints for escalation.

Example 3: Stakeholder Sentiment Analysis

Input: "How do stakeholders feel about our delivery quality this quarter?"

# 1. Query stakeholder assessments (Step 2)
# 2. Aggregate scores by question (quality-related questions)
# 3. Extract free-text comments about quality
# 4. Compare with previous quarter
# 5. Correlate with defect counts from Step 3

Related Skills

spm/agile-story-generation - Generate stories from improvement action items
spm/acceptance-criteria - Define acceptance criteria for improvement stories
spm/project-insights - Project health and velocity tracking
spm/planning-summarization - Sprint and release planning summaries
reporting/survey-analysis - Detailed survey response analysis
reporting/trend-analysis - General trend analysis capabilities

About this skill

Overview

Prerequisites

Procedure

Step 1: Gather Sprint Retrospective Data

Step 2: Collect Stakeholder Survey Responses

Step 3: Analyze Sprint Performance Metrics

Step 4: Identify Themes from Feedback

Step 5: Generate Action Items

Step 6: Generate the Feedback Summary Report

Step 7: Track Action Items Across Sprints

Tool Usage

MCP Tools Reference

REST API Reference

Best Practices

Troubleshooting

Retrospective Notes Field Is Empty

Survey Responses Not Linked to Sprint

Theme Categorization Misses Feedback

Action Items Not Being Completed

Examples

Example 1: Single Sprint Retro Summary

Example 2: Quarterly Improvement Trend

Example 3: Stakeholder Sentiment Analysis

Related Skills