Solved Decision Modeling & Analysis Discussion 1

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Solved Decision Modeling & Analysis Discussion 1

The Modeling Process

We live in the data-driven world. In our personal lives, we are surrounded by websites offering weather or airfare predictions, and in our professional lives we deal with revenue projections and metrics analysis.

Data analysis in the real world is mostly driven by the desire to solve problem(s). In your initial post, share a real-life problem where you have applied (or would like to apply) the seven-step modeling process. Is this problem structured, semi-structured, or unstructured? Explain your decision-making process.

Partial Solution

  1. Define the Problem: As the first step within the seven-step modeling process, the problem needs to be clearly identified. Within the company I work for, each department has its own set of SLA’s to follow. For this particular “problem,” I will solely focus on my department which happens to be Inbound. The problem consists of not achieving SLA (service level agreement) for incoming trailers and its inventory.
  2. Collect and summarize data: This step involves being able to determine all aspects of data regarding the problem previously identified. For the problem I have identified, there are several pieces of information that are crucial. First and foremost is the SLA contracted with each client. We cannot start to achieve SLA if the data is unknown. Other sources of information that will be deemed important to know is the time in which it takes to process an entire trailer from beginning to end. Other variables include trailer capacity, forecasted inventory volume per trailer, forecasted trailer delivery, number of associates, and inventory type.
  3. Develop a model: As it sounds, this step involves creating a model of the data. The types of models that can be utilized depend on both preference and type of data being evaluated. Common forms include spreadsheet, graphical, and algebraic. For simplicity, readability, and familiarity, I would use a spreadsheet model.
  4. Verify the model: 
  5. Select one or more suitable decisions:
  6. Present the results to the organization:
  7. Implement the model and update it over time:


Albright, S.C. & Winston, W.L. (2017). Business analytics: Data analysis and decision making (6th  ed.). Boston, MA: Cengage Learning.

Solved Decision Modeling & Analysis Discussion 1