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📘 P-T_backend_ts — Transparent Task Tracking & Performance Analytics System

This backend powers a robust, auditable, data-driven task tracking system designed to eliminate manipulation, ensure fairness, and give management full clarity into productivity and planning accuracy.

This document explains the key analytical frameworks built into the system:

• MEAS — Manager Estimation Accuracy Score
• Bias Detection Engine
• MEAS Trendline Generator (6 months)
• EPS — Employee Performance Score

These features directly address historical issues like:

✔ Manipulated allocated hours ✔ Fake efficiency ✔ Manager bias ✔ Incorrect task logs ✔ Poor planning visibility

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🧠 MANAGER ESTIMATION ACCURACY SCORE (MEAS)

Score Range: 0 → 100

Score	Meaning
100	Perfect estimation accuracy
> 80	Good, reliable estimation
< 60	Poor estimation accuracy
< 40	Requires immediate oversight

🎯 MEAS Reveals:

• Managers who under-allocate to artificially increase team “efficiency”
• Managers who over-allocate (padding work, slowing throughput)
• Managers who are accurate and consistent
• Projects with high risk due to poor planning
• Employees suffering from unrealistic deadlines

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🧮 MEAS Calculation Per Task

deviation = |actualHours - allocatedHours| / allocatedHours
accuracy = max(0, 100 - deviation * 100)

Monthly MEAS:

MEAS = average(accuracy across all tasks for the month)

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🎯 MANAGER BIAS DETECTION

Bias is the manager’s tendency to systematically over- or under-estimate task hours.

Formula

bias = (actualHours - allocatedHours) / allocatedHours

Interpretation Table

Bias Value	Meaning	Behavior
> +0.20 (+20%)	Manager consistently under-estimates	❌ Unrealistic deadlines — BAD
< -0.20 (−20%)	Manager consistently over-estimates	⚠ Inefficient planning — padding
-0.20 → +0.20	Healthy, balanced estimation	✅ GOOD

Why It Matters

• Protects employees from overload
• Exposes padding and hidden inefficiency
• Creates real planning accountability
• Helps leadership coach managers effectively

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📈 MEAS Trendline Generator (Last 6 Months)

This is one of the MOST valuable analytics tools.

It Shows:

• Whether a manager is improving or declining
• Consistency of estimation quality
• Impact of complexity/training
• Project-level planning stability
• Reliability & predictability trends

Output Example:

[
  { period: "2024-10", score: 77 },
  { period: "2024-11", score: 80 },
  { period: "2024-12", score: 82 },
  { period: "2025-01", score: 84 },
  { period: "2025-02", score: 88 },
  { period: "2025-03", score: 91 }
]

Leadership can visually identify:

• Improvement curve 📈
• Decline 📉
• Inconsistency ⚠
• High-performance stability 🌟

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⭐ EMPLOYEE PERFORMANCE SCORE (EPS) — Complete Overview

EPS ensures employees are evaluated only based on transparent, system-tracked data, NOT:

✘ Fake efficiency ✘ Manual edits ✘ Incorrect allocations ✘ Manager favoritism ✘ Subjective reviews

EPS = Weighted score derived from 6 pillars.

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📊 EPS Pillars & Weights

Pillar	Meaning	Weight
1. Task Completion Rate	Completed vs assigned tasks	25%
2. Overrun Behavior	Exceeding allocated hours	20%
3. Underutilization Behavior	Finishing too fast (<60% of time)	10%
4. Rework Frequency	Number of tasks needing rework	20%
5. Time Discipline	Forgot stop, auto-closings, breaks	15%
6. Session Quality	Idle vs active time	10%

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⭐ EMPLOYEE PERFORMANCE METRICS (DETAILED)

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1️⃣ Task Completion Rate (25%)

completionScore = completedTasks / assignedTasks

Measured monthly.

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2️⃣ Overrun Behavior (20%)

overrunCount = tasks where actual > allocated
overrunPercent = overrunCount / completedTasks
overrunScore = 100 - (overrunPercent * 100)

High overruns = poor time estimation or work inefficiency.

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3️⃣ Underutilization Behavior (10%)

Triggered if employee finishes task using < 60% allocated time.

underutilizedScore = 100 - (underutilizedPercent * 100)

Meaning:

• Rushing work
• Shallow implementation
• Lack of task depth
• Overconfidence in work speed

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4️⃣ Rework Frequency (20%)

reworkScore = 100 - (reworkTasks / totalTasks * 100)

High rework count signals:

• Low quality
• Poor attention to detail
• Misunderstanding requirements

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5️⃣ Time Discipline Score (15%)

Automatically penalizes system-detected behaviors:

Flag Type	Penalty
Auto-close	5%
Forgot-stop	3%
Frequent rework starts	2%
Excessive pauses	1%

disciplineScore = 100 - (flagsCount * penaltyWeight)

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6️⃣ Session Quality Score (10%)

idlePercentage = idleTime / activeTime

If idle > 20% → score reduced.

Shows:

• How focused the employee is
• Whether work is continuous or too fragmented

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⭐ Final EPS Score Formula

EPS =
  completionScore * 0.25 +
  overrunScore * 0.20 +
  underutilizedScore * 0.10 +
  reworkScore * 0.20 +
  disciplineScore * 0.15 +
  sessionScore * 0.10

Range: 0 → 100

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⭐ EPS Interpretation

Score	Meaning
90–100	Outstanding performer
75–89	Strong and reliable
60–74	Average — needs guidance
40–59	Needs improvement
< 40	Serious performance issue

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🎯 Why These Metrics Matter

✔ Eliminate manipulation of allocated hours ✔ Track work discipline accurately ✔ Identify underperforming or overloaded employees ✔ Identify poor managers early ✔ Bring complete transparency across hierarchy ✔ Enable CEO to take data-driven decisions ✔ Build a mature, metric-driven engineering culture

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