Performance Management Module

The Performance module helps you manage goals (OKRs), reviews, feedback, and team calibration to drive employee growth and organizational success.

Overview

The Performance module provides:

  • Goals & OKRs - a compact, expandable list of goal alignment
  • Performance Reviews - 360° feedback and formal reviews
  • Continuous Feedback - Real-time recognition and feedback
  • Talent Calibration - 9-box grid for succession planning
  • Check-ins - Regular 1-on-1 meetings

Goals & OKRs (Objectives and Key Results)

Goal View

Goals are shown as a compact, expandable row list — click a row to expand its key results. Each row shows the objective, owner, KR count, and a progress bar.

Visual Indicators:

  • Progress Bars - Real-time completion percentage
  • Status Badges - On Track (green), At Risk (yellow), Behind (red)

Alignment Benefits:

  • See how your work contributes to company goals
  • Identify orphaned goals (not aligned to anything)
  • Understand department priorities
  • Track cascading progress

Creating Goals

Two ways to create goals:

  1. Quick Create - Simple form for experienced users
  2. Guided Wizard - Step-by-step with AI suggestions

Wizard Flow:

  1. Set objective and description
  2. Define 3-5 key results
  3. Align to parent goal (optional)
  4. Set timeframe (Q1, Q2, etc.)
  5. Assign owner and collaborators

Key Results

Each goal should have 3-5 measurable Key Results (KRs) that define success:

Good Key Results:

  • ✅ "Close 100 enterprise deals"
  • ✅ "Reduce churn to <5%"
  • ✅ "Launch mobile app to 10,000 users"

Bad Key Results:

  • ❌ "Improve sales" (not measurable)
  • ❌ "Work on product" (not specific)
  • ❌ "Be better" (not actionable)

Progress Tracking

Manual Updates:

  • Update progress percentage directly
  • Mark key results as complete
  • Add progress notes

Automated Updates:

  • Jira Integration - Sync progress from epic completion
  • Linear Integration - Track project completion
  • Asana Integration - Sync from project boards

Goal Alignment

Parent-Child Relationships:

  • Company goals cascade to department goals
  • Department goals cascade to team goals
  • Team goals cascade to individual goals

Alignment Rules:

  • Maximum 2-3 children per parent (avoid overcommitting)
  • All department goals should align to company goals
  • Individual goals should align to team/department goals
  • Orphaned goals trigger warnings

Skills & Analytics on OKRs

  • Link skills to an OKR — attach career-framework skills to an objective, either manually or via AI auto-suggestion from the objective's text. Skill progress then rolls up across every OKR it's linked to.
  • Timeline & prediction — each OKR has a timeline view of its historical check-ins plus an AI-projected completion probability.

Strategic Roadmap

A dedicated space for department/company-level initiatives that are bigger than a single OKR cycle. Create and manage roadmap items, get AI field suggestions while filling one out, and convert a roadmap item straight into an OKR — the AI conversion flow also runs a team-gap analysis and recommends which teams should own the resulting goal.

Performance Reviews

360° Feedback

Comprehensive feedback from:

  • Manager (formal review)
  • Peers (lateral feedback)
  • Direct reports (upward feedback)
  • Self-assessment

Review Cycle:

  1. Launch review cycle (HR/Admin)
  2. Employees complete self-assessment
  3. Peers/managers provide feedback
  4. Manager completes final review
  5. Calibration session (managers align ratings)
  6. Share results with employees

Before launching, HR/Admin can run an audience preview — a dry-run that resolves exactly which employees the cycle's audience scope/config will include, without committing anything, so you can catch an over- or under-broad audience before the cycle goes live.

During a calibration session, a budget-impact view overlays the recommended salary adjustments coming out of calibration decisions against the active merit-cycle budget envelope, so calibrators can see the cost of their decisions in real time.

Once a review is delivered, the employee reads and acknowledges it on the final review page. An Export PDF button on that page opens the browser's print dialog with a clean, chrome-free copy of the finalized review for saving or printing.

Review Templates & Question Library

Admins build the questions employees and managers answer during a cycle. Open the builder at Performance > Reviews > Templates (/performance/reviews/templates).

Question library (your reusable bank). Every question you write is saved to a tenant-wide bank so you can reuse it across templates instead of retyping it. Each question is one of two kinds:

  • Reflection. A self-assessment prompt the employee answers about their own work.
  • Open. An open-ended question a reviewer answers about the employee.

Composed templates. A template is a named set of bank questions tied to a review type: Annual, Semi-annual, Quarterly, or Custom. Compose it by picking questions already in the bank or typing new ones inline (new text is added to the bank automatically). Each review type has a default template the cycle picks up when none is chosen.

Draft a template with AI. Click AI generate, choose the review type, and describe what you want the review to cover in a sentence or two. Sparko drafts a full set of questions you can edit, reorder, or swap before saving. As with all Sparko AI, no cost is shown to you.

Viewing templates and the bank needs performance.review_templates.view (everyone who runs reviews has it). Building and editing them needs performance.review_templates.manage (HR Admin / Super Admin).

Growth Trajectory

An employee's profile Performance tab plots their growth trajectory: the overall review rating as a dot-and-line across every completed review cycle, plus the four fixed component ratings (goal achievement, technical skills, collaboration, leadership). It appears once there are two or more completed reviews, so there is a trend to draw. Before that the profile says there is not enough review history yet. It is a read view of ratings the employee has already been given, not a new rating surface.

AI-Powered Performance Review Generation

Sparko's AI can now generate high-quality performance reviews automatically by synthesizing data from across the platform.

Two Ways to Get AI-Generated Reviews

1. Via AI Chat Assistant (Enterprise Tier)

Ask the AI assistant to write a performance review:

"Write a performance review for Sarah Chen for Q4 2025"

The AI will:

  • ✅ Pull data from OKRs, 1-on-1 notes, 360 feedback, and learning records
  • ✅ Structure feedback in STAR format (Situation, Task, Action, Result)
  • ✅ Check for plagiarism and template overuse
  • ✅ Generate uniqueness score (minimum 70% unique)
  • ✅ Provide quality warnings if issues detected
  • ✅ Display rich preview in chat with sections and badges

✍️ AI-Generated Performance Review

✓ Uniqueness: 87%

✨ Accomplishments

Situation: Sarah was assigned to lead the Enterprise tier launch with a team of 4 developers...

Task: Her goal was to deliver 3 major features by Q4 end while maintaining code quality...

Action: She implemented daily standups, code review automation, and mentored 2 junior devs...

Result: All 3 features shipped on time, customer satisfaction increased 23%, and team velocity improved 40%.

📈 Areas for Improvement

Situation: During the Q3 incident with the payment system...

Task: Sarah needed to communicate the root cause to stakeholders...

Action: She focused primarily on the technical fix but delayed stakeholder updates...

Result: While the fix was excellent, executive team expressed concern about communication gaps.

Review Period: Q4 2025  |  Rating: 4 - Exceeds Expectations  |  Sources: 3 OKRs, 8 1:1 notes, 5 feedback items

2. Manual Creation with AI Assist (Coming Soon)

When creating a review manually, click the "AI Assist" button to:

  • Get suggestions based on employee data
  • Fill in sections automatically
  • Improve language and structure
  • Ensure STAR format compliance

AI Review Quality Features

STAR Format Enforcement:

  • All accomplishments and improvement areas structured as:
    • Situation - Context and background
    • Task - What needed to be done
    • Action - What the employee did
    • Result - Measurable outcome

Multi-Source Data Synthesis: The AI pulls information from:

  • ✅ OKRs - Goal progress and key results achieved
  • ✅ 1-on-1 Notes - Manager feedback and discussion points
  • ✅ 360 Feedback - Peer and upward feedback
  • ✅ Growth Data - Development-plan milestones completed, certifications earned
  • ✅ Project Work - Jira/Linear/Asana progress (if connected)

Plagiarism & Quality Detection:

  • ✅ N-gram Fingerprinting - Detects template overuse
  • ✅ Uniqueness Scoring - Minimum 70% unique content required
  • ✅ Template Detection - Flags generic phrases
  • ✅ Quality Warnings - Suggests improvements if score is low

⚠️ Quality Warnings

  • Review contains 3 common template phrases - consider making more specific
  • Accomplishments section has low uniqueness (62%) - add more concrete examples
  • Missing measurable outcomes in 2 STAR examples

Approval Workflow

For AI-Generated Reviews:

  1. Review Created - AI generates draft and saves as "in_progress"
  2. Manager Review - Manager receives notification
  3. Quick Approve - If review looks good, click "Quick Approve" (Business+ tier)
  4. Detailed Review - Click "Review & Approve" to:
    • Read full content section by section
    • See uniqueness score and quality warnings
    • Add optional manager notes
    • Approve or reject with feedback
  5. Employee Access - Once approved, employee can view

Consolidated Approvals Dashboard:

  • All pending performance reviews appear in the Approvals page
  • View employee name, review period, and uniqueness score
  • Approve multiple reviews efficiently
  • Track approval history

Benefits of AI-Generated Reviews

✅ Save Time - Reduce review writing from 2 hours to 10 minutes ✅ Increase Quality - STAR format ensures structured, actionable feedback ✅ Reduce Bias - Data-driven insights reduce subjective bias ✅ Ensure Consistency - All reviews follow same high-quality structure ✅ Improve Fairness - Plagiarism detection prevents copy-paste reviews ✅ Drive Development - Actionable feedback linked to real achievements

Rating Scales

Standard 5-point Scale:

  • 5 - Exceptional: Consistently exceeds expectations
  • 4 - Exceeds: Frequently exceeds expectations
  • 3 - Meets: Consistently meets expectations
  • 2 - Needs Improvement: Sometimes meets expectations
  • 1 - Unsatisfactory: Rarely meets expectations

Continuous Feedback

Real-Time Feedback

Give and receive feedback anytime, not just during reviews.

Types:

  • Praise - Recognize good work
  • Constructive - Improvement-focused feedback

Public recognition, kudos, awards, and milestones are a separate module — see Engagement for the recognition wall, awards, and points.

Talent Calibration

9-Box Grid

Calibrate talent using a 2x2 grid:

  • X-Axis: Performance (ratings from reviews)
  • Y-Axis: Potential (manager assessment)

9 Boxes:

  1. High Potential, High Performance - Stars (promote, retain)
  2. High Potential, Medium Performance - Diamonds in rough (develop)
  3. High Potential, Low Performance - Question marks (improve or exit)
  4. Medium Potential, High Performance - Solid performers (reward)
  5. Medium Potential, Medium Performance - Core contributors (maintain)
  6. Medium Potential, Low Performance - Performance issues (needs a development or exit plan)
  7. Low Potential, High Performance - Specialists (keep happy)
  8. Low Potential, Medium Performance - Limited growth (role fit)
  9. Low Potential, Low Performance - Action needed (exit)

Calibration Sessions

Process:

  1. Each manager places their team members on grid
  2. Leadership team reviews placements together
  3. Discuss and debate (avoid bias)
  4. Align on ratings and potential
  5. Create development plans

Known limitation: dragging an employee's chip to a different box on the grid does not currently save — the move is visual only and is lost on refresh. Use the calibration session canvas below (with its per-row decision status) to actually record calibration outcomes.

Calibration Session Canvas

The session page at /performance/calibration/sessions/{id} is a facilitator-led analysis tool with four blocks:

  • Rating distribution — bars per rating bucket (1–5) with target bands. Bars at rating 5 turn amber when >10% of the cohort lands there; bars at rating 1 turn amber when >15% lands there. Click any bucket to drill into its detail panel.
  • Cohort breakdown — toggle Manager / Level to see per-cohort mini-distributions. Cohorts with 2+ employees at rating 5 OR any at rating 1 get flagged as outliers.
  • Rating detail — table of employees in the selected bucket with Self / Manager / Final scores, decision status pill, and a Discuss/Update action (manage-permission gated).
  • Session outcomes — three tiles tracking Ready for promotion, Needs developing, and Adjustments made.

Each row's decision is recorded as pending (default) / discussed / adjusted via the decision modal. Status drives the outcomes tile + the sticky-bottom tally + the exported CSV.

Finalize calibration marks the session complete (read-only afterward). Export decisions log downloads a CSV of every result + status + notes for record-keeping.

Check-ins & 1-on-1s

Regular Check-ins

Recommended Frequency:

  • Weekly: For new hires or struggling employees
  • Bi-weekly: Standard for most employees
  • Monthly: For senior/autonomous employees

Check-in Agenda:

  1. Wins & celebrations
  2. Challenges & blockers
  3. Goal progress
  4. Career development
  5. Action items

Meeting Notes

  • Take notes during 1-on-1s
  • Tag action items
  • Review previous action items
  • Share notes with employee

Known limitation: the "Generate AI agenda" button on the 1-on-1 detail pane doesn't currently do anything — it's not wired up yet, even though the backend endpoint behind it exists. Prepare your agenda manually for now.

Performance Analytics

Manager Dashboards

View:

  • Team performance distribution
  • Goal completion rates
  • Review cycle completion
  • Feedback frequency
  • Calibration data

Company-Wide Insights

  • Performance trends over time
  • High/low performers by department
  • Goal alignment coverage
  • Review completion rates
  • Feedback culture metrics

Cohort Comparison

The Performance Analytics page at /analytics/performance includes a Cohort comparison tab that surfaces how performance signals move across teams over time. Select any combination of:

  • Metric — Avg rating (review overall_rating averaged per cell), Promotion rate (career-path level changes per cohort headcount), or Attrition (terminations per cohort headcount)
  • Cohort — Department, Tenure band (<1y, 1–2y, 2–4y, 4–7y, 7+y), or Hire cohort (e.g., "Hired Q3 2024")
  • Period — Quarter, Half, or Year (always 6 buckets, newest-right)

The resulting heatmap uses a diverging red↔neutral↔green color scale for Avg rating (centered on 3.0) and a sequential single-hue ramp for Promotion rate and Attrition (both non-evaluative percentages).

Click any cell to drill into the employees behind that (cohort, period) bucket. The drill table shows Name · Level · Rating · QoQ delta · Suggested next step (Promotion packet / Stretch assignment / Calibration discussion / PIP risk).

Scope behavior: Callers with performance.analytics.view_team see cells/drills restricted to their org subtree; view_all sees company-wide.

Best Practices

Goal Setting

  1. Use the SMART framework:
    • Specific, Measurable, Achievable, Relevant, Time-bound
  2. Limit goals to 3-5 per person/team
  3. Align all goals to company objectives
  4. Review quarterly, update as needed

Feedback Culture

  1. Give feedback frequently (not just during reviews)
  2. Be specific with examples
  3. Focus on behavior, not personality
  4. Balance positive and constructive
  5. Follow up on feedback given

Reviews

  1. No surprises - Discuss performance regularly
  2. Use data - Reference goals, projects, feedback
  3. Be fair - Calibrate to avoid bias
  4. Focus forward - Development plans for growth

Integration with Other Modules

  • People - Review employee profiles during calibration
  • Recruiting - Performance data informs promotion/hiring
  • Career - OKRs link to career-framework skills; skill gaps surface stretch assignments
  • Compensation - Performance ratings inform merit increases

Still need help? Reach us at support@sparko.app.

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