| Course | DAM-7020 Predictive Analytics for Business Intelligence |
|---|---|
| Module | Module 1 |
| Paper type | Discussion forum: initial post and replies |
| Length | About 401 words |
| Format | Discussion post with APA 7 citations |
| School | Thomas Edison State University |
| Program | MBA in Data Analytics |
| Updated | October 2026 |
Free sample paper for DAM 7020 Module 1
Module 1 Discussion: Which Decisions Should Analytics Serve First?
From What Happened to What Will Happen: Choosing the First Analytics Decision at an Auto Service Chain
Our chain runs 40 shops that replace tires, brakes and batteries and do inspections and oil changes. Every Monday, store managers decide how many technicians to schedule and how many tires to order from the regional warehouse. They use last year's numbers and instinct. Some stores run out of popular tire sizes in November while others carry excess stock into spring.
Holsapple et al. (2014) reviewed definitions of business analytics and proposed a unified foundation that treats analytics as evidence-based problem recognition and solving, with three common orientations: descriptive analytics, which reports what has happened; predictive analytics, which estimates what will happen; and prescriptive analytics, which recommends what to do. They stress that these are parts of one decision process, not separate technologies.
Today we are almost entirely descriptive: weekly sales by store, average ticket, tires sold by size. That is useful for looking back but not for Monday's decisions. Loshin (2012) stresses that information has value only when it reaches the people who act on it in time; our weekly report reaches store managers on Tuesday, after the schedule and the tire order are already set. Predicting next week's demand by store and service type would change both staffing and stocking. Later, a prescriptive tool could recommend tire transfers between stores. Davenport and Harris (2007) argue that organizations gain most when analytics is aimed at distinctive capabilities; for a service chain, having the right tire and a free technician when a customer arrives is that capability.
I would start with demand forecasting for the eight busiest stores, measure how much it reduces stockouts and overtime, and expand only if it does.
A pilot also answers a question no framework can: whether store managers will trust a forecast enough to change an order. If they override it constantly, we will learn why before investing further, and their reasons will improve the model.
Overrides will be logged with a reason.
Reply to Leah
Leah, your hospital pharmacy already forecasts drug use. Does anyone check how accurate last month's forecast was, and do pharmacists trust it enough to change orders?
Reply to Marco
Marco, your bakery bakes the same quantity every day. Even a simple forecast by day of week and weather might reduce waste; would you be willing to test it at one location first?
References
Davenport, T. H., & Harris, J. G. (2007). Competing on analytics: The new science of winning. Harvard Business School Press.
Holsapple, C., Lee-Post, A., & Pakath, R. (2014). A unified foundation for business analytics. Decision Support Systems, 64, 130-141. https://doi.org/10.1016/j.dss.2014.05.013
Loshin, D. (2012). Business intelligence: The savvy manager's guide (2nd ed.). Morgan Kaufmann.
DAM 7020 Module 1 instructions, in plain terms
DAM-7020 grades five discussion forums at 30 percent, a written assignment that prepares for the later papers at 10 percent, a midterm paper, a synchronous event and a final project at 30 percent, with Loshin's Business Intelligence as the text. A first post and replies are expected each time. In Module 1 you introduce business analytics and decision making: explain the kinds of analytics, connect them to real decisions in an organization you know and say where analytics should begin. Use Loshin and one study, and ask classmates whether their analytics would really alter a choice. Explain how you will judge whether the first project changed a decision, and over what period.
How the DAM 7020 Module 1 example is put together
The post opens with the chain's Monday decisions and the stockouts and surpluses that follow. Holsapple, Lee-Post and Pakath's unified foundation defines descriptive, predictive and prescriptive analytics as parts of one decision process. The chain is placed at the descriptive stage, and weekly demand by store is chosen as the first predictive target, with Davenport and Harris's point about distinctive capabilities supporting the choice. A pilot in eight stores keeps the start small. Two replies ask a hospital analyst about forecast accuracy and a bakery owner about a one-store test. The post closes by treating managers' overrides as information for improving the model. A pilot in eight stores keeps the start small.
Reading the DAM 7020 Module 1 grading rubric
This forum is marked on analytics ideas used correctly, Loshin and a study in support, one organization as the case and replies that move classmates ahead. Posts that connect kinds of analytics to particular decisions show understanding beyond definitions. Choosing a realistic first project and a way to measure it shows managerial judgment. Citing research on what analytics is, rather than vendor material, shows scholarly practice. Replies that ask whether a decision would change are especially useful. Mentors also credit plans to learn from how managers respond to a pilot. Distinguishing the three kinds of analytics as steps in one decision process, rather than separate tools, shows command of the framework.
DAM 7020 Module 1 help from the desk
Weak posts define descriptive, predictive and prescriptive analytics without an organization, recommend advanced tools before simple ones or reply only with agreement. Describe how decisions are made now, sort them by the kind of analytics that would help, choose one to start and say how you will judge success. Ask classmates whether their analytics would change an actual decision. A free first draft of your DAM-7020 Module 1 discussion post can be built on your workplace. Say how you will learn whether people use the analysis, not only whether it is accurate. Keep the first project small, frequent and measurable, such as one weekly decision in a few locations.
Write yours, or have the desk draft it
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DAM 7020 Module 1 questions, answered
Where can I find a free DAM 7020 Module 1 sample paper?
The discussion post above chooses a first predictive analytics project for a tire and auto service chain, with two replies.
What are descriptive, predictive and prescriptive analytics?
Analytics that report what happened, estimate what will happen and recommend what to do.
What is business analytics?
Holsapple and colleagues describe it as evidence-based problem recognition and solving that supports decisions.
Where should an organization start with predictive analytics?
With a frequent decision where better predictions would change actions, tested on a small scale first.
How is DAM-7020 graded?
Five discussions 30 percent, a written assignment 10 percent, a midterm paper, a synchronous event and a final project 30 percent.