Decision, Outcome, Structure and Data

Model formulation is a process to simplify a problem and formulate a solution. It consists of decision, outcomes, structure and data.

Decision

Decisions are all of the choices that can be made to implement a solution to the problem. Decisions consist of buying, selling, cost and other controlled variables.

Outcomes

Outcomes are the consequences of the decisions made. This will also include metrics used to determine the success of the decisions.

Structure

This is the logic that holds the model together. This would include any mathematical formulas that can be used to determine various decisions and outcomes.

Data

Data is the values to help understand the problem that is being modeled. This data can be real world data or may be estimated from uncontrolled variables.

Summarize section 2.3.2 including the influence chart

Section 2.3.2 is about using influence charts with income statements. We can see with the influence chart that the objective is profits. To get to the objective, we will need to generate revenue which is created by the price of the product. Total cost is arrived by adding the variable cost and the fixed cost. Variable cost is determined by the quantity sold plus the unit price. The quantity sold is also related to the total revenue.

Summarize section 2.3.1 including the influence chart

Section 2.3.1 is about increasing profits by setting the appropriate price of a product. The objective is Profit. To determine the profit, the company will subtract the total cost from the total revenue. To find the total cost, they will need to determine the fixed and variable costs. Variable cost will be broken further down into the quantity sold and the unit cost. Each of these parts will then give the company a high level idea how to determine the appropriate price for the product.

Influence Chart for the Example Invivo Diagnostics

Steps to Derive a Problem

When we are given a problem to solve it is usually undefined and a not very clear mess. The mess must be broken down to its simplest form and organized into a clearly defined problem. Two ways to do this is with divergent and convergent thinking.

Divergent

Divergent thinking is brainstorming different solutions to the problem. This is the process of generating as many solutions and ideas as possible. People are allowed to follow creative solutions to solve the problem.

Convergent

Where divergent is the create process, convergent is not so much. Convergent is a goal centric process with only one solution in mind. This does not allow for many solutions or creativity in those solutions.

Example

In a typical programming project a user will have a problem that needs to be solved. In most cases these problems are not well defined. System analysts will meet with the end users to brainstorm (divergent) different ideas and solutions to their problem. From those solutions one will be picked to be developed and implemented.

Sometimes a problem doesn’t need a meeting of the minds. When there is an issue with a system, sometimes there is only one task that can fix the problem (convergent). In this case, the task is outlined and implemented in the most effective manner.

Principles/Steps/Symbols in Building Influence Charts

Influence charts are free form visual aides to help problem solvers get a high level view of their issues. Theses charts use a variety of symbols to show each part of the problem.





The hexagon represents an the objective or desired outcome. This is the end point of the solution.










The circle represents a variable or unknown value.










The triangle represents a fixed input parameter.










The double circle represents a random input parameter.










The square represents a decision.












Influence charts are similar to flow charts but without the strict rules. Think of an influence chart as a sketch of the problem that needs to be solved.

Six-Stage Problem Solving Process

There are six essential steps to solving a problem. Each of these steps plays an important role in creating a solution.

1. Exploring The Mess

Problems are rarely handed to us with every part neatly defined. Most problems are messy clumps of issues that need to be solved. To get to a solvable problem, each clump needs to be sorted from the mess and compiled into an easy to use list of issues. Once the mess is sorted into a manageable defined problem we can continue with step 2.

2. Search for Information

Now that we have a defined list of problems we need to research for information on a solution. This step gathers any information that could be useful to solving the problem. Data can be gathered from many sources and action steps will start to be compiled. This step will give us most of the information needed to solve the issue and possible solutions.

3. Identifying a Problem

This stage creates a more formal definition of what the problem truly is. It will also answer what is the most import problem gathered from the mess. Once everything is gathered and analyzed we will have a working problem statement to be used in the next steps.

4. Searching for Solutions

Now that we know what the real problem is, we can start to formulate solutions. In this step we will decided on several viable solutions. This could be solutions created by us or by other people who have tackled similar problems. Once this step is completed we will have a list of solutions for our problem.

5. Evaluating Solutions

It’s time to decide on the solution. Many factors must be taken into account in deciding which solution will work best. We must determine which meets our criteria and what factors within and not within our control will affect the final solution. Once one solution is picked it will be time to do step 6.

6. Implementing a Solution

The last step defines how a solution can be implemented to fix the problem. A plan must be created on how to best implement the final solution. Once implemented there must be a system in place to determine the success.

Conclusion

Each of these steps will help anyone solve a complex problem. These steps don’t always need to be done in order and sometimes can be repeated. For example, if a solution is evaluated to not be a viable plan you will need to repeat searching for a solution.