| name | schedule-cost-link |
| description | Link schedule activities to cost items. Create cost-loaded schedules, generate cash flow curves, and track earned value. |
| homepage | https://datadrivenconstruction.io |
| metadata | {"openclaw":{"emoji":"📅","os":["darwin","linux","win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":["python3"]}}} |
Schedule-Cost Linker
Business Case
Problem Statement
Integrating schedule and cost requires:
- Linking activities to budget items
- Creating cost-loaded schedules
- Generating cash flow forecasts
- Tracking earned value metrics
Solution
Systematic linkage between schedule activities and cost data to enable integrated project control.
Technical Implementation
import pandas as pd
import numpy as np
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass, field
from datetime import date, timedelta
from enum import Enum
from collections import defaultdict
class LoadingMethod(Enum):
UNIFORM = "uniform"
FRONT_LOADED = "front_loaded"
BACK_LOADED = "back_loaded"
BELL_CURVE = "bell_curve"
@dataclass
class ScheduleActivity:
activity_id: str
name: str
start_date: date
finish_date: date
duration: int
percent_complete: float = 0
@dataclass
class CostItem:
cost_code: str
description: str
budgeted_cost: float
labor_cost: float
material_cost: float
equipment_cost: float
@dataclass
class ActivityCostLink:
activity_id: str
cost_code: str
budgeted_cost: float
loading_method: LoadingMethod
@dataclass
class EarnedValueMetrics:
data_date: date
bcws: float
bcwp: float
acwp: float
sv: float
cv: float
spi: float
cpi: float
eac: float
etc: float
vac: float
class ScheduleCostLinker:
"""Link schedule activities to cost items."""
def __init__(self, project_name: str, budget_at_completion: float):
self.project_name = project_name
self.bac = budget_at_completion
self.activities: Dict[str, ScheduleActivity] = {}
self.cost_items: Dict[str, CostItem] = {}
self.links: List[ActivityCostLink] = []
self.actual_costs: Dict[str, float] = {}
def add_activity(self,
activity_id: str,
name: str,
start_date: date,
finish_date: date,
percent_complete: float = 0):
"""Add schedule activity."""
duration = (finish_date - start_date).days + 1
self.activities[activity_id] = ScheduleActivity(
activity_id=activity_id,
name=name,
start_date=start_date,
finish_date=finish_date,
duration=duration,
percent_complete=percent_complete
)
def add_cost_item(self,
cost_code: str,
description: str,
budgeted_cost: float,
labor_pct: float = 0.4,
material_pct: float = 0.5,
equipment_pct: float = 0.1):
"""Add cost item."""
self.cost_items[cost_code] = CostItem(
cost_code=cost_code,
description=description,
budgeted_cost=budgeted_cost,
labor_cost=budgeted_cost * labor_pct,
material_cost=budgeted_cost * material_pct,
equipment_cost=budgeted_cost * equipment_pct
)
def link_activity_cost(self,
activity_id: str,
cost_code: str,
loading_method: LoadingMethod = LoadingMethod.UNIFORM):
"""Link activity to cost item."""
if activity_id not in self.activities:
return
cost_item = self.cost_items.get(cost_code)
budgeted = cost_item.budgeted_cost if cost_item else 0
self.links.append(ActivityCostLink(
activity_id=activity_id,
cost_code=cost_code,
budgeted_cost=budgeted,
loading_method=loading_method
))
def record_actual_cost(self, activity_id: str, actual_cost: float):
"""Record actual cost for activity."""
self.actual_costs[activity_id] = actual_cost
def _distribute_cost(self,
cost: float,
start_date: date,
duration: int,
method: LoadingMethod) -> Dict[date, float]:
"""Distribute cost over activity duration."""
daily_costs = {}
if duration <= 0:
return {start_date: cost}
if method == LoadingMethod.UNIFORM:
daily = cost / duration
for i in range(duration):
daily_costs[start_date + timedelta(days=i)] = daily
elif method == LoadingMethod.FRONT_LOADED:
total_weight = sum(range(duration, 0, -1))
for i in range(duration):
weight = (duration - i) / total_weight
daily_costs[start_date + timedelta(days=i)] = cost * weight
elif method == LoadingMethod.BACK_LOADED:
total_weight = sum(range(1, duration + 1))
for i in range(duration):
weight = (i + 1) / total_weight
daily_costs[start_date + timedelta(days=i)] = cost * weight
elif method == LoadingMethod.BELL_CURVE:
mid = duration / 2
for i in range(duration):
distance = abs(i - mid)
weight = 1 - (distance / mid) * 0.5
daily_costs[start_date + timedelta(days=i)] = cost * weight / duration
return daily_costs
def generate_cost_loaded_schedule(self) -> pd.DataFrame:
"""Generate cost-loaded schedule."""
data = []
for link in self.links:
activity = self.activities.get(link.activity_id)
cost_item = self.cost_items.get(link.cost_code)
if activity and cost_item:
data.append({
'Activity ID': activity.activity_id,
'Activity Name': activity.name,
'Cost Code': link.cost_code,
'Description': cost_item.description,
'Start': activity.start_date,
'Finish': activity.finish_date,
'Duration': activity.duration,
'Budget': link.budgeted_cost,
'% Complete': activity.percent_complete,
'Earned Value': link.budgeted_cost * activity.percent_complete / 100,
'Loading': link.loading_method.value
})
return pd.DataFrame(data)
def generate_cash_flow(self,
project_start: date = None,
project_end: date = None) -> pd.DataFrame:
"""Generate cash flow curve."""
if not self.links:
return pd.DataFrame()
if project_start is None:
project_start = min(self.activities[l.activity_id].start_date for l in self.links)
if project_end is None:
project_end = max(self.activities[l.activity_id].finish_date for l in self.links)
daily_totals = defaultdict(float)
for link in self.links:
activity = self.activities.get(link.activity_id)
if not activity:
continue
daily_costs = self._distribute_cost(
link.budgeted_cost,
activity.start_date,
activity.duration,
link.loading_method
)
for day, cost in daily_costs.items():
daily_totals[day] += cost
data = []
cumulative = 0
current = project_start
while current <= project_end:
daily = daily_totals.get(current, 0)
cumulative += daily
data.append({
'Date': current,
'Daily': round(daily, 2),
'Cumulative': round(cumulative, 2),
'Cumulative %': round(cumulative / self.bac * 100, 1) if self.bac > 0 else 0
})
current += timedelta(days=1)
return pd.DataFrame(data)
def calculate_earned_value(self, data_date: date) -> EarnedValueMetrics:
"""Calculate earned value metrics at data date."""
bcws = 0
for link in self.links:
activity = self.activities.get(link.activity_id)
if not activity:
continue
daily_costs = self._distribute_cost(
link.budgeted_cost,
activity.start_date,
activity.duration,
link.loading_method
)
for day, cost in daily_costs.items():
if day <= data_date:
bcws += cost
bcwp = 0
for link in self.links:
activity = self.activities.get(link.activity_id)
if activity:
bcwp += link.budgeted_cost * activity.percent_complete / 100
acwp = sum(self.actual_costs.values())
sv = bcwp - bcws
cv = bcwp - acwp
spi = bcwp / bcws if bcws > 0 else 0
cpi = bcwp / acwp if acwp > 0 else 0
eac = self.bac / cpi if cpi > 0 else self.bac
etc = eac - acwp
vac = self.bac - eac
return EarnedValueMetrics(
data_date=data_date,
bcws=round(bcws, 2),
bcwp=round(bcwp, 2),
acwp=round(acwp, 2),
sv=round(sv, 2),
cv=round(cv, 2),
spi=round(spi, 2),
cpi=round(cpi, 2),
eac=round(eac, 2),
etc=round(etc, 2),
vac=round(vac, 2)
)
def get_monthly_cash_flow(self) -> pd.DataFrame:
"""Aggregate cash flow by month."""
daily = self.generate_cash_flow()
if daily.empty:
return pd.DataFrame()
daily['Month'] = pd.to_datetime(daily['Date']).dt.to_period('M')
monthly = daily.groupby('Month').agg({
'Daily': 'sum',
'Cumulative': 'last'
}).reset_index()
monthly.columns = ['Month', 'Monthly Cost', 'Cumulative']
return monthly
def export_to_excel(self, output_path: str) -> str:
"""Export integrated data to Excel."""
with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
schedule = self.generate_cost_loaded_schedule()
schedule.to_excel(writer, sheet_name='Cost-Loaded Schedule', index=False)
cash_flow = self.generate_cash_flow()
if not cash_flow.empty:
cash_flow.to_excel(writer, sheet_name='Cash Flow', index=False)
monthly = self.get_monthly_cash_flow()
if not monthly.empty:
monthly.to_excel(writer, sheet_name='Monthly', index=False)
evm = self.calculate_earned_value(date.today())
evm_df = pd.DataFrame([{
'Data Date': evm.data_date,
'BCWS (PV)': evm.bcws,
'BCWP (EV)': evm.bcwp,
'ACWP (AC)': evm.acwp,
'SV': evm.sv,
'CV': evm.cv,
'SPI': evm.spi,
'CPI': evm.cpi,
'EAC': evm.eac,
'ETC': evm.etc,
'VAC': evm.vac
}])
evm_df.to_excel(writer, sheet_name='Earned Value', index=False)
return output_path
Quick Start
from datetime import date, timedelta
linker = ScheduleCostLinker("Office Building", budget_at_completion=5000000)
linker.add_activity("A-001", "Foundation", date(2024, 6, 1), date(2024, 6, 30), percent_complete=100)
linker.add_activity("A-002", "Structure", date(2024, 7, 1), date(2024, 9, 30), percent_complete=60)
linker.add_activity("A-003", "MEP", date(2024, 8, 1), date(2024, 11, 30), percent_complete=30)
linker.add_cost_item("01-FOUND", "Foundation Work", 500000)
linker.add_cost_item("02-STRUCT", "Structural Work", 2000000)
linker.add_cost_item("03-MEP", "MEP Systems", 1500000)
linker.link_activity_cost("A-001", "01-FOUND")
linker.link_activity_cost("A-002", "02-STRUCT", LoadingMethod.BELL_CURVE)
linker.link_activity_cost("A-003", "03-MEP", LoadingMethod.BACK_LOADED)
linker.record_actual_cost(, )
linker.record_actual_cost(, )
Common Use Cases
1. Earned Value Analysis
evm = linker.calculate_earned_value(date.today())
print(f"CPI: {evm.cpi}")
print(f"SPI: {evm.spi}")
print(f"EAC: ${evm.eac:,.2f}")
2. Cash Flow Forecast
cash_flow = linker.generate_cash_flow()
print(cash_flow.tail(10))
3. Monthly Breakdown
monthly = linker.get_monthly_cash_flow()
print(monthly)
Resources
- DDC Book: Chapter 4.2 - Schedule-Cost Integration