Process Mining MCP Server

{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# BPI 2017 Event Log: Activity Duration Analysis\n", "\n", "This notebook analyzes activity durations in the BPI 2017 event log and visualizes the top 10 activities by average duration.\n", "\n", "## Dataset Overview\n", "- **Total Cases**: 4,726\n", "- **Total Events**: 181,063\n", "- **Total Activities**: 25\n", "- **Average Events per Case**: 38.31\n", "- **Log Timeframe**: January 1, 2016 - February 1, 2017 (396 days)\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2025-06-10T21:17:47.518678Z", "start_time": "2025-06-10T21:17:47.515187Z" } }, "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import numpy as np\n", "from datetime import datetime\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "\n", "# Set up plotting style\n", "plt.style.use('seaborn-v0_8')\n", "sns.set_palette(\"husl\")\n", "plt.rcParams['figure.figsize'] = (12, 8)\n", "plt.rcParams['font.size'] = 11\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Activity Duration Data\n", "\n", "The following data was extracted using MCP tools from the BPI 2017 event log:\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2025-06-10T21:17:54.607583Z", "start_time": "2025-06-10T21:17:54.596776Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total activities: 25\n" ] }, { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>name</th>\n", " <th>avg_duration</th>\n", " <th>median_duration</th>\n", " <th>frequency</th>\n", " <th>is_bottleneck</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>A_Accepted</td>\n", " <td>0.690419</td>\n", " <td>4.910722e-02</td>\n", " <td>4722</td>\n", " <td>True</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>A_Cancelled</td>\n", " <td>-1.967002</td>\n", " <td>7.777778e-06</td>\n", " <td>1553</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>A_Complete</td>\n", " <td>0.034994</td>\n", " <td>3.749972e-02</td>\n", " <td>4703</td>\n", " <td>True</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>A_Concept</td>\n", " <td>15.669170</td>\n", " <td>1.589177e+00</td>\n", " <td>4724</td>\n", " <td>True</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>A_Create Application</td>\n", " <td>0.000091</td>\n", " <td>1.194444e-05</td>\n", " <td>4726</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>A_Denied</td>\n", " <td>-1.558473</td>\n", " <td>8.888889e-06</td>\n", " <td>601</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>A_Incomplete</td>\n", " <td>-0.011392</td>\n", " <td>8.113611e-03</td>\n", " <td>3485</td>\n", " <td>True</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>A_Pending</td>\n", " <td>-0.857330</td>\n", " <td>8.333333e-07</td>\n", " <td>2561</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>A_Submitted</td>\n", " <td>0.005755</td>\n", " <td>8.194444e-05</td>\n", " <td>3122</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>A_Validating</td>\n", " <td>-0.352590</td>\n", " <td>7.186111e-03</td>\n", " <td>5881</td>\n", " <td>True</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " name avg_duration median_duration frequency \\\n", "0 A_Accepted 0.690419 4.910722e-02 4722 \n", "1 A_Cancelled -1.967002 7.777778e-06 1553 \n", "2 A_Complete 0.034994 3.749972e-02 4703 \n", "3 A_Concept 15.669170 1.589177e+00 4724 \n", "4 A_Create Application 0.000091 1.194444e-05 4726 \n", "5 A_Denied -1.558473 8.888889e-06 601 \n", "6 A_Incomplete -0.011392 8.113611e-03 3485 \n", "7 A_Pending -0.857330 8.333333e-07 2561 \n", "8 A_Submitted 0.005755 8.194444e-05 3122 \n", "9 A_Validating -0.352590 7.186111e-03 5881 \n", "\n", " is_bottleneck \n", "0 True \n", "1 False \n", "2 True \n", "3 True \n", "4 False \n", "5 False \n", "6 True \n", "7 False \n", "8 False \n", "9 True " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Activity duration data from MCP performance analysis\n", "activity_data = [\n", " {\"name\": \"A_Accepted\", \"avg_duration\": 0.6904193755588498, \"median_duration\": 0.04910722222222222, \"frequency\": 4722, \"is_bottleneck\": True},\n", " {\"name\": \"A_Cancelled\", \"avg_duration\": -1.9670015870716178, \"median_duration\": 7.777777777777777e-6, \"frequency\": 1553, \"is_bottleneck\": False},\n", " {\"name\": \"A_Complete\", \"avg_duration\": 0.03499359658137832, \"median_duration\": 0.03749972222222222, \"frequency\": 4703, \"is_bottleneck\": True},\n", " {\"name\": \"A_Concept\", \"avg_duration\": 15.669169839766205, \"median_duration\": 1.5891775, \"frequency\": 4724, \"is_bottleneck\": True},\n", " {\"name\": \"A_Create Application\", \"avg_duration\": 0.0000911527248789204, \"median_duration\": 0.000011944444444444443, \"frequency\": 4726, \"is_bottleneck\": False},\n", " {\"name\": \"A_Denied\", \"avg_duration\": -1.5584728799223517, \"median_duration\": 8.888888888888888e-6, \"frequency\": 601, \"is_bottleneck\": False},\n", " {\"name\": \"A_Incomplete\", \"avg_duration\": -0.011391992826398856, \"median_duration\": 0.008113611111111111, \"frequency\": 3485, \"is_bottleneck\": True},\n", " {\"name\": \"A_Pending\", \"avg_duration\": -0.8573298760249902, \"median_duration\": 8.333333333333333e-7, \"frequency\": 2561, \"is_bottleneck\": False},\n", " {\"name\": \"A_Submitted\", \"avg_duration\": 0.0057549900348779276, \"median_duration\": 0.00008194444444444444, \"frequency\": 3122, \"is_bottleneck\": False},\n", " {\"name\": \"A_Validating\", \"avg_duration\": -0.3525902158552023, \"median_duration\": 0.007186111111111111, \"frequency\": 5881, \"is_bottleneck\": True},\n", " {\"name\": \"O_Accepted\", \"avg_duration\": 2.5747529901196047e-6, \"median_duration\": 1.111111111111111e-6, \"frequency\": 2564, \"is_bottleneck\": False},\n", " {\"name\": \"O_Cancelled\", \"avg_duration\": 3.9989498995848, \"median_duration\": 2.777777777777778e-6, \"frequency\": 2462, \"is_bottleneck\": False},\n", " {\"name\": \"O_Create Offer\", \"avg_duration\": 0.0002950579474472149, \"median_duration\": 0.00026416666666666667, \"frequency\": 6457, \"is_bottleneck\": False},\n", " {\"name\": \"O_Created\", \"avg_duration\": 0.8429984460017552, \"median_duration\": 0.006856944444444444, \"frequency\": 6457, \"is_bottleneck\": True},\n", " {\"name\": \"O_Refused\", \"avg_duration\": 4.1630068803981844e-6, \"median_duration\": 2.777777777777778e-6, \"frequency\": 759, \"is_bottleneck\": False},\n", " {\"name\": \"O_Returned\", \"avg_duration\": 0.675755716680835, \"median_duration\": 0.046227222222222225, \"frequency\": 3529, \"is_bottleneck\": True},\n", " {\"name\": \"O_Sent (mail and online)\", \"avg_duration\": 19.427641378240896, \"median_duration\": 4.722222222222222e-6, \"frequency\": 5974, \"is_bottleneck\": False},\n", " {\"name\": \"O_Sent (online only)\", \"avg_duration\": 57.7194743524712, \"median_duration\": 1.2254244444444444, \"frequency\": 299, \"is_bottleneck\": True},\n", " {\"name\": \"W_Assess potential fraud\", \"avg_duration\": 9.050815332175926, \"median_duration\": 0.021951250000000002, \"frequency\": 480, \"is_bottleneck\": True},\n", " {\"name\": \"W_Call after offers\", \"avg_duration\": 57.61821405288892, \"median_duration\": 0.004465, \"frequency\": 27417, \"is_bottleneck\": False},\n", " {\"name\": \"W_Call incomplete files\", \"avg_duration\": 12.431546881005174, \"median_duration\": 0.023397499999999998, \"frequency\": 24805, \"is_bottleneck\": True},\n", " {\"name\": \"W_Complete application\", \"avg_duration\": 4.692650388086459, \"median_duration\": 0.000012777777777777777, \"frequency\": 21878, \"is_bottleneck\": False},\n", " {\"name\": \"W_Handle leads\", \"avg_duration\": 0.4685871324210429, \"median_duration\": 0.009710416666666666, \"frequency\": 7198, \"is_bottleneck\": True},\n", " {\"name\": \"W_Shortened completion\", \"avg_duration\": 15.885293556763283, \"median_duration\": 0.0035025000000000004, \"frequency\": 46, \"is_bottleneck\": False},\n", " {\"name\": \"W_Validate application\", \"avg_duration\": 7.561561655865125, \"median_duration\": 0.00026277777777777774, \"frequency\": 29934, \"is_bottleneck\": False}\n", "]\n", "\n", "# Create DataFrame\n", "df = pd.DataFrame(activity_data)\n", "print(f\"Total activities: {len(df)}\")\n", "df.head(10)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data Preprocessing and Filtering\n", "\n", "Note: Some activities show negative average durations, which indicates data quality issues or activities with complex timing patterns. For visualization purposes, we'll focus on activities with positive durations.\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2025-06-10T21:17:59.394389Z", "start_time": "2025-06-10T21:17:59.386373Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Activities with positive durations: 20\n", "\n", "Top 10 Activities by Average Duration:\n", " name avg_duration avg_duration_minutes frequency is_bottleneck\n", " O_Sent (online only) 57.719474 3463.168461 299 True\n", " W_Call after offers 57.618214 3457.092843 27417 False\n", "O_Sent (mail and online) 19.427641 1165.658483 5974 False\n", " W_Shortened completion 15.885294 953.117613 46 False\n", " A_Concept 15.669170 940.150190 4724 True\n", " W_Call incomplete files 12.431547 745.892813 24805 True\n", "W_Assess potential fraud 9.050815 543.048920 480 True\n", " W_Validate application 7.561562 453.693699 29934 False\n", " W_Complete application 4.692650 281.559023 21878 False\n", " O_Cancelled 3.998950 239.936994 2462 False\n" ] } ], "source": [ "# Filter out activities with negative durations for clearer analysis\n", "df_positive = df[df['avg_duration'] > 0].copy()\n", "\n", "# Convert durations from hours to more readable units\n", "df_positive['avg_duration_minutes'] = df_positive['avg_duration'] * 60\n", "df_positive['median_duration_minutes'] = df_positive['median_duration'] * 60\n", "\n", "# Sort by average duration (descending) and get top 10\n", "top_10_activities = df_positive.nlargest(10, 'avg_duration')\n", "\n", "print(f\"Activities with positive durations: {len(df_positive)}\")\n", "print(f\"\\nTop 10 Activities by Average Duration:\")\n", "print(top_10_activities[['name', 'avg_duration', 'avg_duration_minutes', 'frequency', 'is_bottleneck']].to_string(index=False))\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "## Visualization 1: Top 10 Activities by Average Duration\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2025-06-10T21:18:03.728315Z", "start_time": "2025-06-10T21:18:03.377746Z" } }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "<Figure size 1500x1200 with 2 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Create the main visualization\n", "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(15, 12))\n", "\n", "# Top plot: Bar chart of average durations\n", "colors = ['#ff4444' if bottleneck else '#4472c4' for bottleneck in top_10_activities['is_bottleneck']]\n", "bars = ax1.bar(range(len(top_10_activities)), \n", " top_10_activities['avg_duration'], \n", " color=colors, alpha=0.8, edgecolor='black', linewidth=0.5)\n", "\n", "ax1.set_title('Top 10 Activities by Average Duration\\n(Red = Bottleneck, Blue = Normal)', fontsize=16, fontweight='bold', pad=20)\n", "ax1.set_xlabel('Activities', fontsize=12, fontweight='bold')\n", "ax1.set_ylabel('Average Duration (Hours)', fontsize=12, fontweight='bold')\n", "ax1.set_xticks(range(len(top_10_activities)))\n", "ax1.set_xticklabels([name.replace('_', '\\n').replace(' ', '\\n') for name in top_10_activities['name']], \n", " rotation=45, ha='right', fontsize=10)\n", "\n", "# Add value labels on bars\n", "for i, (bar, value) in enumerate(zip(bars, top_10_activities['avg_duration'])):\n", " height = bar.get_height()\n", " ax1.text(bar.get_x() + bar.get_width()/2., height + max(top_10_activities['avg_duration']) * 0.01,\n", " f'{value:.1f}h', ha='center', va='bottom', fontweight='bold', fontsize=9)\n", "\n", "ax1.grid(axis='y', alpha=0.3)\n", "ax1.set_ylim(0, max(top_10_activities['avg_duration']) * 1.15)\n", "\n", "# Bottom plot: Frequency vs Duration scatter plot\n", "scatter = ax2.scatter(top_10_activities['frequency'], \n", " top_10_activities['avg_duration'],\n", " c=colors, s=100, alpha=0.7, edgecolors='black', linewidth=1)\n", "\n", "ax2.set_title('Activity Frequency vs Average Duration', fontsize=14, fontweight='bold', pad=15)\n", "ax2.set_xlabel('Frequency (Number of Occurrences)', fontsize=12, fontweight='bold')\n", "ax2.set_ylabel('Average Duration (Hours)', fontsize=12, fontweight='bold')\n", "ax2.grid(alpha=0.3)\n", "\n", "# Add labels to points\n", "for idx, row in top_10_activities.iterrows():\n", " ax2.annotate(row['name'].replace('_', ' '), \n", " (row['frequency'], row['avg_duration']),\n", " xytext=(5, 5), textcoords='offset points', \n", " fontsize=8, alpha=0.8)\n", "\n", "plt.tight_layout()\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "## Visualization 2: Duration Distribution Analysis\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2025-06-10T21:18:12.347622Z", "start_time": "2025-06-10T21:18:11.965937Z" } }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "<Figure size 1600x1200 with 4 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Create a more detailed analysis\n", "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(16, 12))\n", "\n", "# 1. Horizontal bar chart with better readability\n", "y_pos = np.arange(len(top_10_activities))\n", "colors_bottleneck = ['#ff6b6b' if bottleneck else '#4ecdc4' for bottleneck in top_10_activities['is_bottleneck']]\n", "\n", "bars = ax1.barh(y_pos, top_10_activities['avg_duration'], color=colors_bottleneck, alpha=0.8, edgecolor='black')\n", "ax1.set_yticks(y_pos)\n", "ax1.set_yticklabels(top_10_activities['name'], fontsize=10)\n", "ax1.set_xlabel('Average Duration (Hours)', fontsize=12, fontweight='bold')\n", "ax1.set_title('Top 10 Activities by Duration\\n(Horizontal View)', fontsize=12, fontweight='bold')\n", "ax1.grid(axis='x', alpha=0.3)\n", "\n", "# Add value labels\n", "for i, (bar, value) in enumerate(zip(bars, top_10_activities['avg_duration'])):\n", " width = bar.get_width()\n", " ax1.text(width + max(top_10_activities['avg_duration']) * 0.01, bar.get_y() + bar.get_height()/2,\n", " f'{value:.1f}h', ha='left', va='center', fontweight='bold', fontsize=9)\n", "\n", "# 2. Average vs Median Duration Comparison\n", "x = np.arange(len(top_10_activities))\n", "width = 0.35\n", "\n", "bars1 = ax2.bar(x - width/2, top_10_activities['avg_duration'], width, label='Average', color='#ff7f0e', alpha=0.8)\n", "bars2 = ax2.bar(x + width/2, top_10_activities['median_duration'], width, label='Median', color='#2ca02c', alpha=0.8)\n", "\n", "ax2.set_xlabel('Activities', fontsize=12, fontweight='bold')\n", "ax2.set_ylabel('Duration (Hours)', fontsize=12, fontweight='bold')\n", "ax2.set_title('Average vs Median Duration', fontsize=12, fontweight='bold')\n", "ax2.set_xticks(x)\n", "ax2.set_xticklabels([name[:15] + '...' if len(name) > 15 else name for name in top_10_activities['name']], rotation=45, ha='right')\n", "ax2.legend()\n", "ax2.grid(axis='y', alpha=0.3)\n", "\n", "# 3. Bottleneck Analysis\n", "bottleneck_counts = top_10_activities['is_bottleneck'].value_counts()\n", "colors_pie = ['#ff6b6b', '#4ecdc4']\n", "labels = ['Bottleneck', 'Normal']\n", "\n", "wedges, texts, autotexts = ax3.pie(bottleneck_counts.values, labels=labels, colors=colors_pie, \n", " autopct='%1.1f%%', startangle=90, explode=(0.05, 0))\n", "ax3.set_title('Bottleneck Activities in Top 10', fontsize=12, fontweight='bold')\n", "\n", "# 4. Duration vs Frequency Analysis\n", "# Create bins for frequency\n", "freq_bins = pd.cut(top_10_activities['frequency'], bins=3, labels=['Low', 'Medium', 'High'])\n", "duration_by_freq = top_10_activities.groupby(freq_bins)['avg_duration'].mean()\n", "\n", "bars = ax4.bar(duration_by_freq.index, duration_by_freq.values, color=['#ffcc99', '#ff9999', '#ff6666'], alpha=0.8)\n", "ax4.set_xlabel('Frequency Category', fontsize=12, fontweight='bold')\n", "ax4.set_ylabel('Average Duration (Hours)', fontsize=12, fontweight='bold')\n", "ax4.set_title('Duration by Frequency Category', fontsize=12, fontweight='bold')\n", "ax4.grid(axis='y', alpha=0.3)\n", "\n", "# Add value labels\n", "for bar, value in zip(bars, duration_by_freq.values):\n", " height = bar.get_height()\n", " ax4.text(bar.get_x() + bar.get_width()/2., height + max(duration_by_freq.values) * 0.02,\n", " f'{value:.1f}h', ha='center', va='bottom', fontweight='bold')\n", "\n", "plt.tight_layout()\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "## Summary Statistics and Insights\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2025-06-10T21:18:17.597709Z", "start_time": "2025-06-10T21:18:17.589680Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "=== ACTIVITY DURATION ANALYSIS SUMMARY ===\n", "\n", "Dataset Overview:\n", "• Total activities analyzed: 20\n", "• Activities with negative durations (excluded): 5\n", "• Top 10 activities represent: 118,019 events\n", "• Percentage of total events: 65.2%\n", "\n", "Duration Insights:\n", "• Longest average duration: O_Sent (online only) (57.72 hours)\n", "• Shortest average duration (in top 10): O_Cancelled (4.00 hours)\n", "• Most frequent activity (in top 10): W_Validate application (29,934 occurrences)\n", "\n", "Bottleneck Analysis:\n", "• Bottleneck activities in top 10: 4/10\n", "• Average duration of bottlenecks: 23.72 hours\n", "• Average duration of non-bottlenecks: 18.20 hours\n", "\n", "Key Activities:\n", "• O_Sent (online only): 57.72h avg, 299 occurrences (BOTTLENECK)\n", "• W_Call after offers: 57.62h avg, 27,417 occurrences \n", "• O_Sent (mail and online): 19.43h avg, 5,974 occurrences \n", "• W_Shortened completion: 15.89h avg, 46 occurrences \n", "• A_Concept: 15.67h avg, 4,724 occurrences (BOTTLENECK)\n" ] } ], "source": [ "# Calculate summary statistics\n", "print(\"=== ACTIVITY DURATION ANALYSIS SUMMARY ===\")\n", "print(f\"\\nDataset Overview:\")\n", "print(f\"• Total activities analyzed: {len(df_positive)}\")\n", "print(f\"• Activities with negative durations (excluded): {len(df) - len(df_positive)}\")\n", "print(f\"• Top 10 activities represent: {top_10_activities['frequency'].sum():,} events\")\n", "print(f\"• Percentage of total events: {top_10_activities['frequency'].sum() / 181063 * 100:.1f}%\")\n", "\n", "print(f\"\\nDuration Insights:\")\n", "print(f\"• Longest average duration: {top_10_activities.iloc[0]['name']} ({top_10_activities.iloc[0]['avg_duration']:.2f} hours)\")\n", "print(f\"• Shortest average duration (in top 10): {top_10_activities.iloc[-1]['name']} ({top_10_activities.iloc[-1]['avg_duration']:.2f} hours)\")\n", "print(f\"• Most frequent activity (in top 10): {top_10_activities.loc[top_10_activities['frequency'].idxmax(), 'name']} ({top_10_activities['frequency'].max():,} occurrences)\")\n", "\n", "print(f\"\\nBottleneck Analysis:\")\n", "bottleneck_activities = top_10_activities[top_10_activities['is_bottleneck'] == True]\n", "print(f\"• Bottleneck activities in top 10: {len(bottleneck_activities)}/{len(top_10_activities)}\")\n", "print(f\"• Average duration of bottlenecks: {bottleneck_activities['avg_duration'].mean():.2f} hours\")\n", "print(f\"• Average duration of non-bottlenecks: {top_10_activities[top_10_activities['is_bottleneck'] == False]['avg_duration'].mean():.2f} hours\")\n", "\n", "print(f\"\\nKey Activities:\")\n", "for idx, row in top_10_activities.head(5).iterrows():\n", " status = \"(BOTTLENECK)\" if row['is_bottleneck'] else \"\"\n", " print(f\"• {row['name']}: {row['avg_duration']:.2f}h avg, {row['frequency']:,} occurrences {status}\")\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "## Process Improvement Recommendations\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2025-06-10T21:18:24.334828Z", "start_time": "2025-06-10T21:18:24.324205Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "=== PROCESS IMPROVEMENT RECOMMENDATIONS ===\n", "\n", "🎯 HIGH PRIORITY - Focus on these activities for maximum impact:\n", " • W_Call after offers: 57.6h avg × 27,417 times = 1579719 total hours\n", " • O_Sent (mail and online): 19.4h avg × 5,974 times = 116061 total hours\n", "\n", "🔴 BOTTLENECK ACTIVITIES - Require immediate attention:\n", " • O_Sent (online only): 57.72h average duration\n", " • A_Concept: 15.67h average duration\n", " • W_Call incomplete files: 12.43h average duration\n", " • W_Assess potential fraud: 9.05h average duration\n", "\n", "📊 ANALYSIS INSIGHTS:\n", " • The top 3 activities account for 134.8 hours of average process time\n", " • Online-only sending takes 57.7h vs 19.4h for mail+online\n", " • Call-related activities show high duration variability, suggesting inconsistent handling\n", "\n", "💡 RECOMMENDATIONS:\n", " 1. Optimize 'O_Sent (online only)' process - highest duration activity\n", " 2. Streamline 'W_Call after offers' - high frequency AND high duration\n", " 3. Investigate 'O_Sent (mail and online)' efficiency gains\n", " 4. Focus on bottleneck activities marked in red in visualizations\n", " 5. Consider automation for high-frequency, low-complexity activities\n" ] } ], "source": [ "# Generate recommendations based on the analysis\n", "print(\"=== PROCESS IMPROVEMENT RECOMMENDATIONS ===\")\n", "print()\n", "\n", "# Focus on high-duration, high-frequency activities\n", "high_impact = top_10_activities[\n", " (top_10_activities['avg_duration'] > top_10_activities['avg_duration'].median()) & \n", " (top_10_activities['frequency'] > top_10_activities['frequency'].median())\n", "]\n", "\n", "print(\"🎯 HIGH PRIORITY - Focus on these activities for maximum impact:\")\n", "for idx, row in high_impact.iterrows():\n", " impact_score = row['avg_duration'] * row['frequency']\n", " print(f\" • {row['name']}: {row['avg_duration']:.1f}h avg × {row['frequency']:,} times = {impact_score:.0f} total hours\")\n", "\n", "print(\"\\n🔴 BOTTLENECK ACTIVITIES - Require immediate attention:\")\n", "for idx, row in bottleneck_activities.iterrows():\n", " print(f\" • {row['name']}: {row['avg_duration']:.2f}h average duration\")\n", "\n", "print(\"\\n📊 ANALYSIS INSIGHTS:\")\n", "print(f\" • The top 3 activities account for {top_10_activities.head(3)['avg_duration'].sum():.1f} hours of average process time\")\n", "print(f\" • Online-only sending takes {top_10_activities.iloc[0]['avg_duration']:.1f}h vs {top_10_activities[top_10_activities['name'].str.contains('mail and online')]['avg_duration'].iloc[0]:.1f}h for mail+online\")\n", "print(f\" • Call-related activities show high duration variability, suggesting inconsistent handling\")\n", "\n", "print(\"\\n💡 RECOMMENDATIONS:\")\n", "print(\" 1. Optimize 'O_Sent (online only)' process - highest duration activity\")\n", "print(\" 2. Streamline 'W_Call after offers' - high frequency AND high duration\")\n", "print(\" 3. Investigate 'O_Sent (mail and online)' efficiency gains\")\n", "print(\" 4. Focus on bottleneck activities marked in red in visualizations\")\n", "print(\" 5. Consider automation for high-frequency, low-complexity activities\")\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "## Data Export for Further Analysis\n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2025-06-10T21:18:30.448448Z", "start_time": "2025-06-10T21:18:30.433651Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "✅ Results exported to 'bpi2017_top10_activity_durations.csv'\n", "\n", "📋 FINAL SUMMARY TABLE:\n", " Activity Avg Duration (h) Frequency Bottleneck Impact Score\n", " O_Sent (online only) 57.72 299 True 17258.12\n", " W_Call after offers 57.62 27417 False 1579718.57\n", "O_Sent (mail and online) 19.43 5974 False 116060.73\n", " W_Shortened completion 15.89 46 False 730.72\n", " A_Concept 15.67 4724 True 74021.16\n", " W_Call incomplete files 12.43 24805 True 308364.52\n", "W_Assess potential fraud 9.05 480 True 4344.39\n", " W_Validate application 7.56 29934 False 226347.79\n", " W_Complete application 4.69 21878 False 102665.81\n", " O_Cancelled 4.00 2462 False 9845.41\n" ] } ], "source": [ "# Export the analysis results\n", "export_df = top_10_activities[['name', 'avg_duration', 'median_duration', 'frequency', 'is_bottleneck']].copy()\n", "export_df['avg_duration_minutes'] = export_df['avg_duration'] * 60\n", "export_df['median_duration_minutes'] = export_df['median_duration'] * 60\n", "export_df['impact_score'] = export_df['avg_duration'] * export_df['frequency']\n", "\n", "# Save to CSV\n", "export_df.to_csv('bpi2017_top10_activity_durations.csv', index=False)\n", "print(\"✅ Results exported to 'bpi2017_top10_activity_durations.csv'\")\n", "\n", "# Display final summary table\n", "print(\"\\n📋 FINAL SUMMARY TABLE:\")\n", "display_df = export_df[['name', 'avg_duration', 'frequency', 'is_bottleneck', 'impact_score']].copy()\n", "display_df.columns = ['Activity', 'Avg Duration (h)', 'Frequency', 'Bottleneck', 'Impact Score']\n", "print(display_df.to_string(index=False, float_format='%.2f'))\n" ] } ], "metadata": { "language_info": { "name": "python" } }, "nbformat": 4, "nbformat_minor": 2 }