A disciplined, sequential process is the bedrock of any sound investment decision. This structured approach drives optimal capital allocation by ensuring that all critical factors are considered logically, creating a defensible and transparent basis for investment. The following nine-step process is the blueprint for converting a recognized problem into an implemented, value-enhancing solution.

1. Recognize the Problem: The process begins with the clear identification of an issue that requires a decision. This may be triggered by an operational failure, such as a burned-out motor, or by a strategic initiative, like a continuous improvement program designed to proactively identify areas for enhancement.
2. Define the Goal or Objective: Once a problem is recognized, a clear objective must be defined. This goal provides the context for the analysis, whether it is a broad corporate objective like operating profitably or a specific project task, such as overhauling a portion of a refinery within a set budget.
3. Assemble Relevant Data: This step involves gathering all pertinent information, including market data, technical specifications, and internal accounting records. It is crucial to distinguish relevant facts from irrelevant information and to understand the quality and certainty of the data, especially as future costs and revenues are inherently uncertain.
4. Identify Feasible Alternatives: A thorough analysis depends on the identification of all viable courses of action. Unglamorous but practical options must be considered, such as “patch it up for another year.” Critically, this list must always include the “do-nothing” alternative, which serves as the baseline against which all other options are measured.
5. Select the Criterion to Determine the Best Alternative: To choose the “best” option, one must first define what “best” means. A clear selection criterion, typically economic efficiency, is required. This criterion serves as the north star for the analysis, guiding the comparison of disparate alternatives.
6. Construct the Model: The objective, data, alternatives, and selection criterion are merged into a model. This often takes the form of a mathematical relationship that represents the interplay between different variables, such as costs, benefits, and time.
7. Predict the Outcomes for Each Alternative: Using the constructed model, the financial outcomes for each feasible alternative are predicted. These predictions involve structuring all market and extra-market consequences into a coherent financial projection.
8. Choose the Best Alternative: The alternative that best meets the selection criterion is chosen. This step involves comparing the numerical results of the analysis while also incorporating any intangible consequences—those factors not included in the monetary calculations—into the final judgment.
9. Audit the Results: After a decision is implemented, an audit must be performed to compare actual outcomes against the initial predictions. This crucial final step ensures that projected advantages are realized and provides invaluable feedback for improving future analyses.

1.1 Core Economic Criteria

When maximizing profit is the overarching goal, the specific economic criterion applied depends on the constraints of the problem. Decision-making scenarios typically fall into one of three categories:

• Fixed Input: The amount of capital or other resources is fixed. The objective is to maximize the benefits or outputs achieved with those resources.
• Fixed Output: A specific task or outcome is required. The objective is to minimize the costs or inputs needed to achieve that fixed output.
• Neither Input nor Output Fixed: This is the most general case, where both resources and outcomes are variable. The objective is to maximize the difference between benefits and costs, or simply, maximize profit.

With a disciplined process in place, the focus must shift to populating the model with the correct financial inputs. An analysis is only as valid as its data, making a sophisticated understanding of cost structures the next critical element of the framework.