1.1. Introduction to Module 1

Before we can begin to calculate the financial viability of a project, we must first establish a solid foundation. This module provides that foundation by introducing two critical preliminary concepts: the structured process of rational decision-making and the fundamental vocabulary of cost analysis. Mastering this framework is essential, as it prevents flawed analyses and ensures that the choices we make are robust, logical, and defensible. A clear understanding of the decision process and the different types of costs involved is the bedrock upon which all subsequent financial evaluations are built.

1.2. The Decision-Making Framework

Categorizing Engineering Problems

Not all problems are created equal. They vary in difficulty and complexity, and can be grouped into three broad categories:

1. Simple Problems: These are situations that can be resolved with minimal time and effort, often through straightforward logic or simple calculations.
   • Example: “Should I pay cash or use my credit card for a purchase?”
   • Example: “Should I buy a semester parking pass or use parking meters?”
2. Intermediate Problems: These problems are primarily economic in nature and are complex enough that they cannot be solved “in one’s head.” They are the primary focus of engineering economic analysis.
   • Example: “Which equipment should be selected for a new assembly line?”
   • Example: “Which printing press should be purchased: a low-cost press requiring three operators or a more expensive one needing only two?”
3. Complex Problems: These problems represent a mixture of economic, political, and humanistic elements. Decision-making is often influenced by non-economic forces like power dynamics, geographical considerations, and individual impacts.
   • Example: A multinational corporation deciding where to locate a new manufacturing plant, considering economic factors alongside national interests and political stability.

The Role of Engineering Economic Analysis

Engineering economic analysis is most suitable for intermediate problems and the economic aspects of complex problems. A problem is a good candidate for this type of analysis when it possesses two key qualities:

1. The problem is important enough to justify a serious and structured effort.
2. The problem cannot be worked out mentally; it requires a formal analysis to organize the information and lead to a sound decision.

The Rational Decision-Making Process

A structured, rational process is the key to effective decision-making. The following nine-step framework provides a logical method for selecting the best course of action from among feasible alternatives.

1. Recognize the problem. The process begins with the awareness that a problem or opportunity exists. This can be triggered by an obvious event (e.g., a burned-out motor) or through proactive programs like Total Quality Management (TQM) that are designed to identify areas for improvement.
2. Define the goal or objective. A clear objective is necessary to guide the decision. For a firm, the overarching goal is typically to operate profitably. Complex problems may involve multiple, sometimes conflicting, goals.
3. Assemble relevant data. This step involves gathering the facts and information needed to analyze the alternatives. This is often a challenging task.
   • Data Sources: Data may come from published sources, internal accounting records, or may need to be gathered through market research.
   • Financial Consequences:
     • Market Consequences: Items with established prices in the marketplace (e.g., labor, material costs).
     • Extra-Market Consequences: Items not directly priced, but for which a value can be indirectly assigned (e.g., the cost of an employee injury).
     • Intangible Consequences: Consequences that are difficult or impossible to quantify in monetary terms (e.g., employee morale).
   • Use of Accounting Data: Accounting data focuses on past performance and must be used with care. For example, overhead costs are often allocated arbitrarily. Consider a firm’s printing department with high allocated overhead costs. If the shipping department finds an outside printer with a lower quoted price, it might seem like a cost-saving move. However, the printing department’s overhead (rent, utilities) will not decrease if it does less work. The only real savings would be in direct materials and possibly labor. The firm as a whole could end up paying more if the outside printer’s cost exceeds the direct savings, even if the accounting data suggests otherwise. This highlights the need to focus on the true differences between alternatives.
4. Identify feasible alternatives. One of the most critical steps is to generate a comprehensive list of potential solutions. A common oversight is failing to consider the “do-nothing” alternative, which represents maintaining the current course of action. Only feasible alternatives—those that are technologically, financially, and practically viable—are retained for further analysis.
5. Select the criterion to determine the best alternative. To choose the “best” option, we must first define what “best” means. In engineering economic analysis, the criterion is typically to maximize economic efficiency or, more simply, to maximize profit.
6. Construct the model. The objective, data, alternatives, and criterion are merged into a model. This is often a mathematical relationship that represents the interplay between different variables.
7. Predict the outcomes for each alternative. Using the model, we predict the consequences of choosing each feasible alternative. Since our analysis focuses on monetary outcomes, intangible consequences are noted but set aside for consideration in the final decision step.
8. Choose the best alternative. The alternative that best meets the selection criterion is chosen. This step involves combining the quantitative, numerical results of the analysis with a qualitative assessment of the intangible consequences.
9. Audit the results. After a decision is implemented, an audit should be performed to compare the actual results with the initial predictions. This crucial feedback loop helps ensure that projected benefits are realized and improves the accuracy of future analyses by revealing what was overlooked or miscalculated.

Economic Criteria

When the goal is to maximize profit, all problems fall into one of three categories based on the relationship between inputs (costs) and outputs (benefits).

• Fixed Input: The amount of input (e.g., money, labor) is fixed.
  • Economic Criterion: Maximize the benefits or outputs.
  • Example: A project engineer has a fixed budget of $350,000 to overhaul a refinery. The goal is to achieve the maximum improvement possible with that budget.
• Fixed Output: There is a fixed task or objective to be accomplished.
  • Economic Criterion: Minimize the costs or inputs.
  • Example: A civil engineering firm is tasked with surveying a tract of land. The goal is to complete the fixed scope of work at the minimum possible cost.
• Neither Input nor Output Fixed: This is the most general case, where both costs and benefits can vary between alternatives.
  • Economic Criterion: Maximize the difference between outputs and inputs (i.e., Maximize Profit).
  • Example: An investor considering different stocks. The amount invested is not fixed, and the potential returns are not fixed. The goal is to choose the investment that maximizes the return minus the cost.

1.3. A Taxonomy of Engineering Costs

A clear understanding of cost terminology is essential for accurate economic analysis.

Deconstruct Core Cost Concepts

• Fixed, Variable, Marginal, and Average Costs:
  • Fixed Costs: Costs that remain constant regardless of the level of output or activity (e.g., factory rent, equipment costs).
  • Variable Costs: Costs that depend on the level of output (e.g., labor, raw materials).
  • Marginal Cost: The variable cost associated with producing one more unit of output.
  • Average Cost: The total cost divided by the number of units produced.
  • Example: A university charges a flat rate of 1800 for 12-18 credit hours**. For an overload, it charges **120 per credit hour.
    • A student taking 12 hours has an average cost of $1800 / 12 = $150/hour.
    • A student taking 18 hours has an average cost of $1800 / 18 = $100/hour.
    • For a student already taking 17 hours, the marginal cost of taking one more hour (up to 18) is $0. For a student already taking 18 hours, the marginal cost of an additional hour is $120. As shown conceptually in Figure 2-1 of the source text, total cost is the sum of fixed and variable costs, and the slopes of the cost curves relate to marginal costs.
• Sunk Costs: A sunk cost is money that has already been spent as a result of a past decision. A critical principle of engineering economic analysis is that sunk costs must be disregarded because current decisions cannot change the past. We must focus only on present and future consequences.
• Opportunity Costs: An opportunity cost is the benefit forgone by choosing to use a resource in one activity instead of its next best alternative. It represents the value of the missed opportunity.
  • Example: If a firm uses an assembly line to produce Product A, it forgoes the profit it could have made by producing Product B. This lost profit is an opportunity cost. If a company-owned parking lot is used for employee parking, the opportunity cost is the rent that could have been earned by leasing the lot to the public.
• Recurring and Nonrecurring Costs:
  • Recurring Costs: Costs that are repetitive and occur at regular intervals, such as annual maintenance or material purchases.
  • Nonrecurring Costs: One-of-a-kind costs that occur at irregular intervals, such as the initial purchase of equipment or a major overhaul.
• Incremental Costs: When comparing alternatives, the focus should be on the differences in their costs. An incremental cost is the additional cost that results from increasing the output of a system by one (or more) units. This principle ensures the analysis is focused only on what changes between the options.
• Cash Costs Versus Book Costs:
  • Cash Costs: Costs that involve an actual cash transaction or “out-of-pocket” expenditure. These are the primary focus of engineering economic analysis.
  • Book Costs: Costs that do not involve a cash transaction but are recorded in the accounting books of a firm. Depreciation is the most common example. While depreciation itself is not a cash flow, it is tax-deductible and therefore affects income taxes, which are cash flows.

Analyze Life-Cycle Costing

Life-cycle costing is the concept of designing products and services with full recognition of all associated costs over their entire life, from conception to disposal. Two key principles are central to this concept:

1. The later that design changes are made, the higher their cost. A change made during the conceptual phase is far less expensive than a change made during the construction or production phase.
2. Early decisions lock in a majority of later costs. The design phase is critical because it commits the project to a certain path. Statistics show that while only 10-30% of a project’s cumulative cost has been spent by the end of the design phase, 70-90% of the total life-cycle costs have already been locked in by the decisions made during that phase. This underscores the immense importance of thorough analysis and sound decision-making early in a project’s life.

1.4. The Art and Science of Cost Estimating

Accurate cost estimation is fundamental to any economic analysis. It is the process of developing the numerical data needed to compare alternatives.

Evaluate Estimation Types and Trade-offs

Estimates vary in their level of detail and accuracy, depending on their purpose.

1. Rough Estimates: Used for high-level planning and feasibility studies. They are developed with minimal time and resources and have a low level of accuracy, typically in the range of -30% to +60%.
2. Semidetailed Estimates: Used for budgeting purposes during preliminary design. They are more detailed and require more resources to develop than rough estimates.
3. Detailed Estimates: Used during the detailed design and contract bidding phases. They are the most accurate, typically within ±3% to ±5%, but also the most costly and time-consuming to create.

As illustrated conceptually by Figure 2-6 in the source text, there is a direct trade-off between the accuracy of an estimate and the cost required to develop it. The resources spent on an estimate must be justified by the needs of the decision at hand.

Synthesize Estimation Models

Several models are used to develop cost estimates, each suited to different situations.

• Per-Unit Model: This model uses a “per-unit” factor to develop the estimate.
  • Example: To estimate the cost of hosting 24 foreign exchange students at a campground, we would break down the costs. Two 15-person vans are needed for transport. Total van rental is 100 each way, plus gas (1/gallon, 10 mpg, 50 miles), for a round trip transportation cost of $220. Adding per-student costs for food, lodging, and activities allows us to calculate a total cost, which can then be divided by 24 to find the cost per student.
• Segmenting Model (Work Breakdown Structure): This technique decomposes a large project into smaller, more manageable components. The costs of these individual components are estimated and then summed to get the total project cost.
  • Example: To estimate the material cost of a “Grass Grabber” lawn mower, the product is broken down into its major subsystems: Chassis (22.45), **Drive train** (72.70), Controls (52.70), and **Cutting/Collection** (25.60). The total estimated material cost is the sum of these subsystems: $173.45.
• Cost Indexes: A cost index is a dimensionless number that reflects the historical change in price for a commodity or group of commodities. It allows us to update historical costs to the present day.
  • Formula: Cost at time A / Cost at time B = Index at time A / Index at time B
  • Example (Miriam): A facility had annual labor costs of $575,500 ten years ago when the labor index was 124. Today, the index is 188. Annual Cost Today = $575,500 * (188 / 124) = $871,800 Similarly, if material costs were $2,455,000 three years ago when the index was 544, and today it is 715, the updated cost is: Annual Cost Today = $2,455,000 * (715 / 544) = $3,222,000
• Power-Sizing Model: This model is used to estimate the cost of industrial plants and equipment by scaling a known cost up or down. It accounts for nonlinear economies of scale using an exponent.
  • Formula: Cost A / Cost B = (Size A / Size B)^x, where x is the power-sizing exponent.
  • Example: A firm paid $50,000 for a 1000 ft² heat exchanger 5 years ago. It now needs a 2500 ft² exchanger. The power-sizing exponent is 0.55. The cost index was 1306 then and is 1487 now.
    1. Scale up for size: Cost of 2500 ft² (5 years ago) = $50,000 * (2500 / 1000)^0.55 = $82,800
    2. Update for time: Cost of 2500 ft² (today) = $82,800 * (1487 / 1306) = $94,300
• The Learning Curve: This concept captures the phenomenon that as the number of repetitions of a task increases, performance becomes faster and more efficient. The model states that as cumulative output doubles, the time per unit is reduced to a fixed percentage.
  • Formula: TN = T_initial * N^b, where TN is the time for the Nth unit, T_initial is the time for the first unit, and b = log(learning curve decimal) / log(2).
  • Example: The first unit of production takes 32 minutes. The learning curve rate is 80%. What is the time for the 100th unit? b = log(0.80) / log(2) = -0.3219 T_100 = 32.0 * (100)^-0.3219 = 7.27 minutes

1.5. Module 1 Conclusion

A structured decision-making process and an accurate, well-reasoned cost analysis are the indispensable bedrock upon which all sound financial evaluations are built. With these foundational skills in place, we are now ready to introduce the most powerful concept in engineering economics: the time value of money.