Supply_Chain_KPI_Optimization_Cheat_Sheet.ipynb

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   "id": "1bb13284-b251-4d09-96f5-c42121f31140",
   "metadata": {},
   "source": [
    "# Supply Chain KPI Optimization Cheat Sheet"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dbced49-0269-4d0f-9e07-a24b966724f3",
   "metadata": {},
   "source": [
    "The code examples demonstrate practical calculations for Supply Chain KPIs using Python classes and methods."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "583fd927-d302-4494-b676-250649fe9c1f",
   "metadata": {},
   "source": [
    "# Use Case (Usage) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfc4f24f-e373-4559-bbdd-fe447ca868b3",
   "metadata": {},
   "source": [
    "Establishing clear and measurable Key Performance Indicators (KPIs) is essential for driving efficiency in any operational process, whether it’s within supply chain management, business operations, or people management. \n",
    "\n",
    "Use these metrics to identify bottlenecks, measure efficiency, and optimize various aspects of your supply chain (Business Operations; People Operations; and, Supply Chain)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfa1fc25-8add-47ca-8f72-cefc7f185c38",
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   "source": [
    "This repository provides key KPIs codes and syntax across the following three domains (business operations; People Operations; and, Supply Chain) and provide insights on their overlaps and unique characteristics:\n",
    "\n",
    "***Business Operations KPIs:***\n",
    "\n",
    "1. Order Fulfillment Rate (overlaps with Supply Chain): Measures successful order completion\n",
    "2. Inventory Turnover Ratio: Indicates inventory management efficiency\n",
    "3. Perfect Order Rate: Tracks flawless order execution\n",
    "4. Cash-to-Cash Cycle Time: Measures financial efficiency\n",
    "5. GMROI (Gross Margin Return on Investment): Evaluates inventory profitability\n",
    "6. Operating Margin: Measures operational efficiency\n",
    "7. Return on Assets: Evaluates asset utilization\n",
    "8. Supply Chain Cost: Total operational costs\n",
    "9. Forecast Accuracy: Prediction precision\n",
    "\n",
    "***People Operations KPIs:***\n",
    "\n",
    "1. Employee Productivity Rate: Output per worker\n",
    "2. Training Completion Rate: Learning progress tracking\n",
    "3. Safety Incident Rate: Workplace safety measure\n",
    "4. Employee Turnover Rate: Workforce stability indicator\n",
    "5. Overtime Hours: Labor utilization tracking\n",
    "6. Employee Satisfaction Score: Workforce contentment\n",
    "7. Time to Fill Positions: Recruitment efficiency\n",
    "8. Training Cost per Employee: Learning investment\n",
    "9. Absenteeism Rate: Attendance tracking\n",
    "10. Labor Cost per Unit: Workforce efficiency\n",
    "\n",
    "***Supply Chain KPIs:***\n",
    "\n",
    "1. On-Time Delivery Rate (overlaps with Business Ops): Delivery performance\n",
    "2. Inventory Accuracy: Stock count precision\n",
    "3. Supplier Lead Time: Procurement efficiency\n",
    "4. Warehouse Utilization: Space efficiency\n",
    "5. Transportation Cost per Unit: Logistics efficiency\n",
    "6. Order Cycle Time: Process speed\n",
    "7. Supplier Defect Rate: Quality control\n",
    "8. Inventory Days of Supply: Stock management\n",
    "9. Fill Rate: Demand fulfillment\n",
    "10. Supply Chain Visibility Score: Process transparency"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a55155df-543b-490e-bb9a-3d9aa380a557",
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   "source": [
    "***To prevent potential mis-interepration of overlapping KPIs, I acknowldege and adress the following Key KPI Overlaps:***\n",
    "\n",
    "1. ***Order metrics (Order Fulfillment Rate, On-Time Delivery) appear in both Business Ops and Supply Chain but focus on different aspects:*** \n",
    "\n",
    "* Business Ops: Financial impact\n",
    "* Supply Chain: Operational efficiency\n",
    "\n",
    "2. ***Inventory metrics appear across domains:*** \n",
    "\n",
    "* Business Ops: Financial perspective (turnover, GMROI)\n",
    "* Supply Chain: Operational perspective (accuracy, days of supply)\n",
    "\n",
    "3. ***Cost metrics are present in all three:***\n",
    "\n",
    "* Business Ops: Overall cost structure\n",
    "* People Ops: Labor and training costs\n",
    "* Supply Chain: Transportation and logistics costs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ec137fc-90a3-496b-8b81-c43bbff3c68f",
   "metadata": {},
   "source": [
    "# KPI Dictionary Structure "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76b9bce2-27d7-47b7-a9f1-ee5e3fe83c1d",
   "metadata": {},
   "source": [
    "Developed a dictionary of key performance indicators (KPIs) across various business domains and converted it into a DataFrame for better visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "18317f97-ab6b-4765-ae9e-a785032a3936",
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     "text": [
      "Supply Chain KPIs Overview:\n",
      "                 Domain                                KPI  \\\n",
      "0   Business Operations             Order Fulfillment Rate   \n",
      "1   Business Operations           Inventory Turnover Ratio   \n",
      "2   Business Operations                 Perfect Order Rate   \n",
      "3   Business Operations            Cash-to-Cash Cycle Time   \n",
      "4   Business Operations  Gross Margin Return on Investment   \n",
      "5   Business Operations             Days Sales Outstanding   \n",
      "6   Business Operations                   Operating Margin   \n",
      "7   Business Operations                   Return on Assets   \n",
      "8   Business Operations                  Supply Chain Cost   \n",
      "9   Business Operations                  Forecast Accuracy   \n",
      "10    People Operations         Employee Productivity Rate   \n",
      "11    People Operations           Training Completion Rate   \n",
      "12    People Operations               Safety Incident Rate   \n",
      "13    People Operations             Employee Turnover Rate   \n",
      "14    People Operations                     Overtime Hours   \n",
      "15    People Operations        Employee Satisfaction Score   \n",
      "16    People Operations             Time to Fill Positions   \n",
      "17    People Operations         Training Cost per Employee   \n",
      "18    People Operations                   Absenteeism Rate   \n",
      "19    People Operations                Labor Cost per Unit   \n",
      "20         Supply Chain              On-Time Delivery Rate   \n",
      "21         Supply Chain                 Inventory Accuracy   \n",
      "22         Supply Chain                 Supplier Lead Time   \n",
      "23         Supply Chain              Warehouse Utilization   \n",
      "24         Supply Chain       Transportation Cost per Unit   \n",
      "25         Supply Chain                   Order Cycle Time   \n",
      "26         Supply Chain               Supplier Defect Rate   \n",
      "27         Supply Chain           Inventory Days of Supply   \n",
      "28         Supply Chain                          Fill Rate   \n",
      "29         Supply Chain      Supply Chain Visibility Score   \n",
      "\n",
      "                                           Definition  Domain Specific  \n",
      "0   Percentage of orders successfully fulfilled on...            False  \n",
      "1   Number of times inventory is sold and replaced...            False  \n",
      "2   Percentage of orders delivered without any issues             True  \n",
      "3   Time between paying for materials and receivin...             True  \n",
      "4                  Measure of inventory profitability             True  \n",
      "5        Average time to collect payment after a sale             True  \n",
      "6         Operating income as a percentage of revenue             True  \n",
      "7                 Net income relative to total assets             True  \n",
      "8               Total cost of supply chain operations            False  \n",
      "9                      Accuracy of demand predictions            False  \n",
      "10     Output per employee in supply chain operations             True  \n",
      "11  Percentage of employees completing required tr...             True  \n",
      "12         Number of safety incidents per worker-hour             True  \n",
      "13     Rate at which employees leave the organization             True  \n",
      "14             Amount of overtime worked by employees             True  \n",
      "15                   Measure of employee satisfaction             True  \n",
      "16              Average time to fill vacant positions             True  \n",
      "17        Average cost spent on training per employee             True  \n",
      "18                   Percentage of unplanned absences             True  \n",
      "19            Labor cost required to produce one unit             True  \n",
      "20              Percentage of deliveries made on time            False  \n",
      "21    Accuracy of inventory records vs physical count            False  \n",
      "22          Time between order placement and delivery             True  \n",
      "23       Percentage of warehouse space being utilized             True  \n",
      "24              Cost to transport one unit of product             True  \n",
      "25              Time from order placement to delivery             True  \n",
      "26       Percentage of defective items from suppliers             True  \n",
      "27  Number of days inventory will last at current ...             True  \n",
      "28  Percentage of customer demand met through imme...             True  \n",
      "29  Measure of supply chain transparency and trace...             True  \n"
     ]
    }
   ],
   "source": [
    "# Create a dictionary structure to hold KPI information\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from datetime import datetime, timedelta\n",
    "\n",
    "kpi_data = {\n",
    "    'Business Operations': {\n",
    "        'Order Fulfillment Rate': {\n",
    "            'definition': 'Percentage of orders successfully fulfilled on time',\n",
    "            'domain_specific': False\n",
    "        },\n",
    "        'Inventory Turnover Ratio': {\n",
    "            'definition': 'Number of times inventory is sold and replaced over a period',\n",
    "            'domain_specific': False\n",
    "        },\n",
    "        'Perfect Order Rate': {\n",
    "            'definition': 'Percentage of orders delivered without any issues',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Cash-to-Cash Cycle Time': {\n",
    "            'definition': 'Time between paying for materials and receiving payment from customers',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Gross Margin Return on Investment': {\n",
    "            'definition': 'Measure of inventory profitability',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Days Sales Outstanding': {\n",
    "            'definition': 'Average time to collect payment after a sale',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Operating Margin': {\n",
    "            'definition': 'Operating income as a percentage of revenue',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Return on Assets': {\n",
    "            'definition': 'Net income relative to total assets',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Supply Chain Cost': {\n",
    "            'definition': 'Total cost of supply chain operations',\n",
    "            'domain_specific': False\n",
    "        },\n",
    "        'Forecast Accuracy': {\n",
    "            'definition': 'Accuracy of demand predictions',\n",
    "            'domain_specific': False\n",
    "        }\n",
    "    },\n",
    "    'People Operations': {\n",
    "        'Employee Productivity Rate': {\n",
    "            'definition': 'Output per employee in supply chain operations',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Training Completion Rate': {\n",
    "            'definition': 'Percentage of employees completing required training',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Safety Incident Rate': {\n",
    "            'definition': 'Number of safety incidents per worker-hour',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Employee Turnover Rate': {\n",
    "            'definition': 'Rate at which employees leave the organization',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Overtime Hours': {\n",
    "            'definition': 'Amount of overtime worked by employees',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Employee Satisfaction Score': {\n",
    "            'definition': 'Measure of employee satisfaction',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Time to Fill Positions': {\n",
    "            'definition': 'Average time to fill vacant positions',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Training Cost per Employee': {\n",
    "            'definition': 'Average cost spent on training per employee',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Absenteeism Rate': {\n",
    "            'definition': 'Percentage of unplanned absences',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Labor Cost per Unit': {\n",
    "            'definition': 'Labor cost required to produce one unit',\n",
    "            'domain_specific': True\n",
    "        }\n",
    "    },\n",
    "    'Supply Chain': {\n",
    "        'On-Time Delivery Rate': {\n",
    "            'definition': 'Percentage of deliveries made on time',\n",
    "            'domain_specific': False\n",
    "        },\n",
    "        'Inventory Accuracy': {\n",
    "            'definition': 'Accuracy of inventory records vs physical count',\n",
    "            'domain_specific': False\n",
    "        },\n",
    "        'Supplier Lead Time': {\n",
    "            'definition': 'Time between order placement and delivery',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Warehouse Utilization': {\n",
    "            'definition': 'Percentage of warehouse space being utilized',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Transportation Cost per Unit': {\n",
    "            'definition': 'Cost to transport one unit of product',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Order Cycle Time': {\n",
    "            'definition': 'Time from order placement to delivery',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Supplier Defect Rate': {\n",
    "            'definition': 'Percentage of defective items from suppliers',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Inventory Days of Supply': {\n",
    "            'definition': 'Number of days inventory will last at current usage',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Fill Rate': {\n",
    "            'definition': 'Percentage of customer demand met through immediate stock availability',\n",
    "            'domain_specific': True\n",
    "        },\n",
    "        'Supply Chain Visibility Score': {\n",
    "            'definition': 'Measure of supply chain transparency and traceability',\n",
    "            'domain_specific': True\n",
    "        }\n",
    "    }\n",
    "}\n",
    "\n",
    "# Convert to DataFrame for better visualization\n",
    "kpi_df = pd.DataFrame([(domain, kpi, data['definition'], data['domain_specific']) \n",
    "                       for domain, kpis in kpi_data.items() \n",
    "                       for kpi, data in kpis.items()],\n",
    "                     columns=['Domain', 'KPI', 'Definition', 'Domain Specific'])\n",
    "\n",
    "print(\"Supply Chain KPIs Overview:\")\n",
    "print(kpi_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4066b1a0-399f-43e0-a5ae-9a5b9a7a5775",
   "metadata": {},
   "source": [
    "# Code Calculations for KPI"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8b1ea6d-a4b8-425b-a5d6-5cae5c169543",
   "metadata": {},
   "source": [
    "# Business Operations KPIs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7e5b43e-d764-4fd5-b78d-a304ea3ed9af",
   "metadata": {},
   "source": [
    "Defined a class to calculate key performance indicators for bsuiness operations management, including order fulfillment rate, inventory turnover, perfect order rate, operating margin, and return on assets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ae4a6eb6-3fa4-405a-b3c8-5859b30a8cf7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "KPI Calculations Example:\n",
      "1. Order Fulfillment Rate: 95.00%\n",
      "2. Inventory Turnover Ratio: 5.56\n",
      "3. Perfect Order Rate: 90.00%\n",
      "4. Operating Margin: 15.00%\n",
      "5. Return on Assets: 18.75%\n"
     ]
    }
   ],
   "source": [
    "# Example calculations for common Business Operations KPIs\n",
    "import numpy as np\n",
    "from datetime import datetime, timedelta\n",
    "\n",
    "# Sample data\n",
    "class SupplyChainKPICalculator:\n",
    "    def __init__(self):\n",
    "        # Sample data for demonstration\n",
    "        self.orders = {\n",
    "            'total_orders': 1000,\n",
    "            'fulfilled_orders': 950,\n",
    "            'on_time_orders': 920,\n",
    "            'perfect_orders': 900\n",
    "        }\n",
    "        \n",
    "        self.inventory = {\n",
    "            'beginning_inventory': 100000,\n",
    "            'ending_inventory': 80000,\n",
    "            'cogs': 500000\n",
    "        }\n",
    "        \n",
    "        self.financial = {\n",
    "            'accounts_receivable': 200000,\n",
    "            'annual_sales': 1000000,\n",
    "            'operating_income': 150000,\n",
    "            'revenue': 1000000,\n",
    "            'total_assets': 800000\n",
    "        }\n",
    "        \n",
    "    def calculate_order_fulfillment_rate(self):\n",
    "        return (self.orders['fulfilled_orders'] / self.orders['total_orders']) * 100\n",
    "    \n",
    "    def calculate_inventory_turnover(self):\n",
    "        avg_inventory = (self.inventory['beginning_inventory'] + self.inventory['ending_inventory']) / 2\n",
    "        return self.inventory['cogs'] / avg_inventory\n",
    "    \n",
    "    def calculate_perfect_order_rate(self):\n",
    "        return (self.orders['perfect_orders'] / self.orders['total_orders']) * 100\n",
    "    \n",
    "    def calculate_operating_margin(self):\n",
    "        return (self.financial['operating_income'] / self.financial['revenue']) * 100\n",
    "    \n",
    "    def calculate_return_on_assets(self):\n",
    "        return (self.financial['operating_income'] / self.financial['total_assets']) * 100\n",
    "\n",
    "# Create calculator instance and demonstrate calculations\n",
    "calculator = SupplyChainKPICalculator()\n",
    "\n",
    "print(\"KPI Calculations Example:\")\n",
    "print(\"1. Order Fulfillment Rate: {:.2f}%\".format(calculator.calculate_order_fulfillment_rate()))\n",
    "print(\"2. Inventory Turnover Ratio: {:.2f}\".format(calculator.calculate_inventory_turnover()))\n",
    "print(\"3. Perfect Order Rate: {:.2f}%\".format(calculator.calculate_perfect_order_rate()))\n",
    "print(\"4. Operating Margin: {:.2f}%\".format(calculator.calculate_operating_margin()))\n",
    "print(\"5. Return on Assets: {:.2f}%\".format(calculator.calculate_return_on_assets()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85ef86f3-c957-45fd-94a5-346b17927cb4",
   "metadata": {},
   "source": [
    "# People Operations KPIs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c6da50d-c58a-4fba-960c-801de36fbea6",
   "metadata": {},
   "source": [
    "Defined a class to calculate various key performance indicators related to people operations, such as productivity rate, training completion rate, and employee turnover rate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c7520908-a7ab-455a-9790-23ae2f463bab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "People Operations KPI Calculations Example:\n",
      "1. Employee Productivity Rate: 80.00%\n",
      "2. Training Completion Rate: 90.00%\n",
      "3. Safety Incident Rate: 0.01 per 1000 hours\n",
      "4. Employee Turnover Rate: 5.00%\n",
      "5. Overtime Percentage: 10.00%\n",
      "6. Average Satisfaction Score: 4.20\n",
      "7. Training Cost per Employee: $500.00\n"
     ]
    }
   ],
   "source": [
    "# People Operations KPIs Example\n",
    "class PeopleOperationsKPICalculator:\n",
    "    def __init__(self):\n",
    "        self.employee_data = {\n",
    "            'total_employees': 100,\n",
    "            'productive_hours': 1600,\n",
    "            'total_hours': 2000,\n",
    "            'completed_training': 90,\n",
    "            'safety_incidents': 2,\n",
    "            'total_work_hours': 160000,\n",
    "            'employees_left': 5,\n",
    "            'overtime_hours': 200,\n",
    "            'satisfaction_scores': [4, 5, 3, 4, 5],  # Scale of 1-5\n",
    "            'training_costs': 50000\n",
    "        }\n",
    "    \n",
    "    def calculate_productivity_rate(self):\n",
    "        return (self.employee_data['productive_hours'] / self.employee_data['total_hours']) * 100\n",
    "    \n",
    "    def calculate_training_completion_rate(self):\n",
    "        return (self.employee_data['completed_training'] / self.employee_data['total_employees']) * 100\n",
    "    \n",
    "    def calculate_safety_incident_rate(self):\n",
    "        return (self.employee_data['safety_incidents'] / \n",
    "                (self.employee_data['total_work_hours'] / 1000))  # Per 1000 hours\n",
    "    \n",
    "    def calculate_turnover_rate(self):\n",
    "        return (self.employee_data['employees_left'] / self.employee_data['total_employees']) * 100\n",
    "    \n",
    "    def calculate_overtime_percentage(self):\n",
    "        return (self.employee_data['overtime_hours'] / self.employee_data['total_hours']) * 100\n",
    "    \n",
    "    def calculate_avg_satisfaction_score(self):\n",
    "        return np.mean(self.employee_data['satisfaction_scores'])\n",
    "    \n",
    "    def calculate_training_cost_per_employee(self):\n",
    "        return self.employee_data['training_costs'] / self.employee_data['total_employees']\n",
    "\n",
    "# Create calculator instance and demonstrate calculations\n",
    "people_calculator = PeopleOperationsKPICalculator()\n",
    "\n",
    "print(\"People Operations KPI Calculations Example:\")\n",
    "print(\"1. Employee Productivity Rate: {:.2f}%\".format(people_calculator.calculate_productivity_rate()))\n",
    "print(\"2. Training Completion Rate: {:.2f}%\".format(people_calculator.calculate_training_completion_rate()))\n",
    "print(\"3. Safety Incident Rate: {:.2f} per 1000 hours\".format(people_calculator.calculate_safety_incident_rate()))\n",
    "print(\"4. Employee Turnover Rate: {:.2f}%\".format(people_calculator.calculate_turnover_rate()))\n",
    "print(\"5. Overtime Percentage: {:.2f}%\".format(people_calculator.calculate_overtime_percentage()))\n",
    "print(\"6. Average Satisfaction Score: {:.2f}\".format(people_calculator.calculate_avg_satisfaction_score()))\n",
    "print(\"7. Training Cost per Employee: ${:.2f}\".format(people_calculator.calculate_training_cost_per_employee()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b880dde9-1311-4feb-adf0-559bf2ebad3e",
   "metadata": {},
   "source": [
    "# Supply Chain KPIs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63be2279-1e37-4044-b2c6-a6a76592c8c4",
   "metadata": {},
   "source": [
    "Defined a class to calculate various supply chain key performance indicators (KPIs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e1a47503-931f-48a8-b457-0e65920ac554",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Supply Chain Specific KPI Calculations Example:\n",
      "1. On-Time Delivery Rate: 95.00%\n",
      "2. Inventory Accuracy: 99.00%\n",
      "3. Average Supplier Lead Time: 30.00 days\n",
      "4. Warehouse Utilization: 85.00%\n",
      "5. Transportation Cost per Unit: $2.00\n",
      "6. Supplier Defect Rate: 1.50%\n",
      "7. Inventory Days of Supply: 50.00 days\n",
      "8. Fill Rate: 95.00%\n"
     ]
    }
   ],
   "source": [
    "# Supply Chain Specific KPIs Example\n",
    "class SupplyChainMetricsCalculator:\n",
    "    def __init__(self):\n",
    "        self.supply_chain_data = {\n",
    "            'deliveries': {\n",
    "                'total': 1000,\n",
    "                'on_time': 950\n",
    "            },\n",
    "            'inventory': {\n",
    "                'system_count': 10000,\n",
    "                'physical_count': 9900\n",
    "            },\n",
    "            'supplier_orders': {\n",
    "                'total_lead_time_days': 15000,  # Sum of all lead times\n",
    "                'total_orders': 500\n",
    "            },\n",
    "            'warehouse': {\n",
    "                'used_space': 8500,\n",
    "                'total_space': 10000\n",
    "            },\n",
    "            'transportation': {\n",
    "                'total_cost': 100000,\n",
    "                'units_shipped': 50000\n",
    "            },\n",
    "            'supplier_quality': {\n",
    "                'defective_items': 150,\n",
    "                'total_items': 10000\n",
    "            },\n",
    "            'inventory_metrics': {\n",
    "                'current_inventory': 5000,\n",
    "                'daily_usage': 100\n",
    "            },\n",
    "            'customer_orders': {\n",
    "                'fulfilled_from_stock': 950,\n",
    "                'total_orders': 1000\n",
    "            }\n",
    "        }\n",
    "    \n",
    "    def calculate_otd_rate(self):\n",
    "        return (self.supply_chain_data['deliveries']['on_time'] / \n",
    "                self.supply_chain_data['deliveries']['total']) * 100\n",
    "    \n",
    "    def calculate_inventory_accuracy(self):\n",
    "        return (self.supply_chain_data['inventory']['physical_count'] / \n",
    "                self.supply_chain_data['inventory']['system_count']) * 100\n",
    "    \n",
    "    def calculate_avg_supplier_lead_time(self):\n",
    "        return (self.supply_chain_data['supplier_orders']['total_lead_time_days'] / \n",
    "                self.supply_chain_data['supplier_orders']['total_orders'])\n",
    "    \n",
    "    def calculate_warehouse_utilization(self):\n",
    "        return (self.supply_chain_data['warehouse']['used_space'] / \n",
    "                self.supply_chain_data['warehouse']['total_space']) * 100\n",
    "    \n",
    "    def calculate_transportation_cost_per_unit(self):\n",
    "        return (self.supply_chain_data['transportation']['total_cost'] / \n",
    "                self.supply_chain_data['transportation']['units_shipped'])\n",
    "    \n",
    "    def calculate_supplier_defect_rate(self):\n",
    "        return (self.supply_chain_data['supplier_quality']['defective_items'] / \n",
    "                self.supply_chain_data['supplier_quality']['total_items']) * 100\n",
    "    \n",
    "    def calculate_inventory_days_of_supply(self):\n",
    "        return (self.supply_chain_data['inventory_metrics']['current_inventory'] / \n",
    "                self.supply_chain_data['inventory_metrics']['daily_usage'])\n",
    "    \n",
    "    def calculate_fill_rate(self):\n",
    "        return (self.supply_chain_data['customer_orders']['fulfilled_from_stock'] / \n",
    "                self.supply_chain_data['customer_orders']['total_orders']) * 100\n",
    "\n",
    "# Create calculator instance and demonstrate calculations\n",
    "sc_calculator = SupplyChainMetricsCalculator()\n",
    "\n",
    "print(\"Supply Chain Specific KPI Calculations Example:\")\n",
    "print(\"1. On-Time Delivery Rate: {:.2f}%\".format(sc_calculator.calculate_otd_rate()))\n",
    "print(\"2. Inventory Accuracy: {:.2f}%\".format(sc_calculator.calculate_inventory_accuracy()))\n",
    "print(\"3. Average Supplier Lead Time: {:.2f} days\".format(sc_calculator.calculate_avg_supplier_lead_time()))\n",
    "print(\"4. Warehouse Utilization: {:.2f}%\".format(sc_calculator.calculate_warehouse_utilization()))\n",
    "print(\"5. Transportation Cost per Unit: ${:.2f}\".format(sc_calculator.calculate_transportation_cost_per_unit()))\n",
    "print(\"6. Supplier Defect Rate: {:.2f}%\".format(sc_calculator.calculate_supplier_defect_rate()))\n",
    "print(\"7. Inventory Days of Supply: {:.2f} days\".format(sc_calculator.calculate_inventory_days_of_supply()))\n",
    "print(\"8. Fill Rate: {:.2f}%\".format(sc_calculator.calculate_fill_rate()))"
   ]
  }
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