Cost Estimation - Resource Method

Business Case

Problem Statement

Traditional costing challenges:

• Fixed unit prices become outdated
• No visibility into cost components
• Difficult to adjust for conditions
• Limited cost analysis capability

Solution

Resource-based costing separates physical resource consumption (norms) from prices, enabling accurate, adjustable, and transparent cost estimation.

Technical Implementation

import pandas as pd
from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from enum import Enum


class ResourceType(Enum):
    LABOR = "labor"
    MATERIAL = "material"
    EQUIPMENT = "equipment"
    SUBCONTRACTOR = "subcontractor"


@dataclass
class Resource:
    code: str
    name: str
    resource_type: ResourceType
    unit: str
    unit_price: float
    currency: str = "USD"


@dataclass
class ResourceNorm:
    resource_code: str
    consumption: float  # Units per work item unit
    waste_factor: float = 1.0  # 1.1 = 10% waste


@dataclass
class WorkItem:
    code: str
    name: str
    unit: str
    resources: List[ResourceNorm] = field(default_factory=list)


@dataclass
class CostLineItem:
    work_item_code: str
    work_item_name: str
    quantity: float
    unit: str
    labor_cost: float
    material_cost: float
    equipment_cost: float
    subcontractor_cost: float
    total_cost: float


class ResourceBasedEstimator:
    """Calculate costs using resource-based method."""

    def __init__(self):
        self.resources: Dict[str, Resource] = {}
        self.work_items: Dict[str, WorkItem] = {}
        self.overhead_rate: float = 0.15
        self.profit_rate: float = 0.10

    def add_resource(self, resource: Resource):
        """Add resource to database."""
        self.resources[resource.code] = resource

    def add_work_item(self, work_item: WorkItem):
        """Add work item with resource norms."""
        self.work_items[work_item.code] = work_item

    def load_resources_from_df(self, df: pd.DataFrame):
        """Load resources from DataFrame."""

        for _, row in df.iterrows():
            resource = Resource(
                code=row['code'],
                name=row['name'],
                resource_type=ResourceType(row['type'].lower()),
                unit=row['unit'],
                unit_price=float(row['unit_price']),
                currency=row.get('currency', 'USD')
            )
            self.add_resource(resource)

    def load_work_items_from_df(self, items_df: pd.DataFrame, norms_df: pd.DataFrame):
        """Load work items and norms from DataFrames."""

        # Group norms by work item
        norms_grouped = norms_df.groupby('work_item_code')

        for _, row in items_df.iterrows():
            code = row['code']
            resources = []

            if code in norms_grouped.groups:
                it...