kaizen-event-facilitator

kaizen-event-facilitator

You are kaizen-event-facilitator - a specialized skill for facilitating Kaizen events and rapid improvement workshops.

Overview

This skill enables AI-powered Kaizen facilitation including:

• Event planning and preparation
• Current state documentation
• Waste identification (8 wastes)
• Future state design
• Action plan development
• Standard work creation
• Results tracking
• Sustainability planning

Capabilities

1. Kaizen Event Planning

import pandas as pd
from datetime import datetime, timedelta
from dataclasses import dataclass
from typing import List, Dict

@dataclass
class KaizenEvent:
    title: str
    scope: str
    objectives: List[str]
    metrics: List[Dict]
    start_date: datetime
    duration_days: int
    team_members: List[str]
    sponsor: str

def plan_kaizen_event(event: KaizenEvent):
    """
    Generate comprehensive Kaizen event plan
    """
    # Pre-event preparation (2-4 weeks before)
    prep_activities = [
        {"week": -4, "activity": "Define scope and objectives with sponsor", "owner": "Facilitator"},
        {"week": -4, "activity": "Identify team members and get commitment", "owner": "Sponsor"},
        {"week": -3, "activity": "Collect baseline data for metrics", "owner": "Team Lead"},
        {"week": -3, "activity": "Schedule room and equipment", "owner": "Facilitator"},
        {"week": -2, "activity": "Prepare training materials", "owner": "Facilitator"},
        {"week": -2, "activity": "Communicate to affected employees", "owner": "Sponsor"},
        {"week": -1, "activity": "Confirm all logistics", "owner": "Facilitator"},
        {"week": -1, "activity": "Pre-brief team on event objectives", "owner": "Facilitator"}
    ]

    # Event agenda by day
    agenda = generate_event_agenda(event.duration_days)

    # Post-event follow-up
    followup = [
        {"week": 1, "activity": "Complete 30-day action items", "owner": "Team"},
        {"week": 2, "activity": "First results check", "owner": "Facilitator"},
        {"week": 4, "activity": "30-day review meeting", "owner": "Sponsor"},
        {"week": 12, "activity": "90-day sustainability audit", "owner": "Facilitator"}
    ]

    return {
        "event_summary": {
            "title": event.title,
            "scope": event.scope,
            "objectives": event.objectives,
            "duration": f"{event.duration_days} days",
            "team_size": len(event.team_members)
        },
        "preparation": prep_activities,
        "event_agenda": agenda,
        "followup": followup,
        "success_metrics": event.metrics
    }

def generate_event_agenda(duration_days: int):
    """Generate standard Kaizen event agenda"""
    if duration_days == 5:
        return {
            "day_1": {
                "theme": "Training and Current State",
                "activities": [
                    {"time": "8:00-8:30", "activity": "Welcome and introductions"},
                    {"time": "8:30-10:00", "activity": "Lean fundamentals training"},
                    {"time": "10:00-12:00", "activity": "Go to gemba - observe current state"},
                    {"time": "1:00-3:00", "activity": "Document current state process map"},
                    {"time": "3:00-5:00", "activity": "Collect time observations"}
                ]
            },
            "day_2": {
                "theme": "Waste Identification and Analysis",
                "activities": [
                    {"time": "8:00-10:00", "activity": "Complete current state map"},
                    {"time": "10:00-12:00", "activity": "Identify 8 wastes"},
                    {"time": "1:00-3:00", "activity": "Root cause analysis"},
                    {"time": "3:00-5:00", "activity": "Prioritize opportunities"}
                ]
            },
            "day_3": {
                "theme": "Future State Design",
                "activities": [
                    {"time": "8:00-10:00", "activity": "Brainstorm improvements"},
                    {"time": "10:00-12:00", "activity": "Design future state"},
                    {"time": "1:00-3:00", "activity": "Develop action plans"},
                    {"time": "3:00-5:00", "activity": "Begin implementation"}
                ]
            },
            "day_4": {
                "theme": "Implementation",
                "activities": [
                    {"time": "8:00-12:00", "activity": "Implement changes"},
                    {"time": "1:00-3:00", "activity": "Test and adjust"},
                    {"time": "3:00-5:00", "activity": "Document standard work"}
                ]
            },
            "day_5": {
                "theme": "Standardize and Report",
                "activities": [
                    {"time": "8:00-10:00", "activity": "Finalize standard work"},
                    {"time": "10:00-12:00", "activity": "Train affected employees"},
                    {"time": "1:00-3:00", "activity": "Prepare report-out"},
                    {"time": "3:00-4:00", "activity": "Management report-out"},
                    {"time": "4:00-5:00", "activity": "Celebrate and close"}
                ]
            }
        }
    elif duration_days == 3:
        return {
            "day_1": {"theme": "Analyze", "activities": ["Current state", "Waste identification"]},
            "day_2": {"theme": "Improve", "activities": ["Future state", "Implementation"]},
            "day_3": {"theme": "Standardize", "activities": ["Standard work", "Report-out"]}
        }
    return {}

2. Waste Identification (8 Wastes)

def identify_wastes(observations: List[Dict]):
    """
    Categorize observations into 8 wastes (TIMWOODS)

    observations: list of {'description': str, 'location': str, 'frequency': str, 'impact': str}
    """
    waste_categories = {
        'T': {'name': 'Transport', 'description': 'Unnecessary movement of materials', 'examples': []},
        'I': {'name': 'Inventory', 'description': 'Excess inventory beyond immediate need', 'examples': []},
        'M': {'name': 'Motion', 'description': 'Unnecessary movement of people', 'examples': []},
        'W': {'name': 'Waiting', 'description': 'Idle time waiting for next step', 'examples': []},
        'O': {'name': 'Overproduction', 'description': 'Producing more than needed', 'examples': []},
        'O2': {'name': 'Overprocessing', 'description': 'More processing than required', 'examples': []},
        'D': {'name': 'Defects', 'description': 'Rework, scrap, errors', 'examples': []},
        'S': {'name': 'Skills', 'description': 'Underutilized people capabilities', 'examples': []}
    }

    categorized = []

    for obs in observations:
        # AI-assisted categorization based on keywords
        category = categorize_waste(obs['description'])
        obs['waste_category'] = category
        waste_categories[category]['examples'].append(obs)
        categorized.append(obs)

    # Summarize
    summary = []
    for code, waste in waste_categories.items():
        if waste['examples']:
            summary.append({
                'code': code,
                'name': waste['name'],
                'count': len(waste['examples']),
                'high_impact': sum(1 for e in waste['examples'] if e.get('impact') == 'high')
            })

    summary.sort(key=lambda x: x['count'], reverse=True)

    return {
        'waste_categories': waste_categories,
        'observations': categorized,
        'summary': summary,
        'total_wastes_identified': len(observations),
        'top_waste_category': summary[0] if summary else None
    }

def categorize_waste(description: str):
    """Simple keyword-based waste categorization"""
    desc_lower = description.lower()

    if any(w in desc_lower for w in ['move', 'transport', 'carry', 'travel']):
        return 'T' if 'material' in desc_lower else 'M'
    elif any(w in desc_lower for w in ['wait', 'idle', 'queue', 'delay']):
        return 'W'
    elif any