BUSI 3014 Week 1 Decision and Figure Discussion Post Example

Course	BUSI 3014 Data Driven Decision Making Workplace Certificate
Week	Week 1
Paper type	Discussion post
Length	About 520 words, 3 pages
Format	Discussion post, APA 7 citations
School	Walden University
Program	BS in Business Administration
Updated	October 2026

Free sample paper for BUSI 3014 Week 1

Week 1 Discussion: A Decision and the Number Behind It

Deciding on a Saturday Route by Counting Jobs per Technician: Why a Pest Control Owner's Spring Decision Rests on a Productivity Figure Built to Answer a Different Question

Every March, the owner of Kestrel Pest Solutions, a composite residential pest control company in Knoxville, Tennessee, where I work as the dispatcher, decides whether to add a Saturday route for the busy months. The company has four technicians on weekday routes. Adding a Saturday route costs a technician's overtime, a truck and fuel, and the owner wants to know it will pay for itself.

The number the owner watches to make that call is jobs completed per technician per week. It comes from a weekly report the company started using years ago to compare technicians' productivity. When the four technicians average more than about 34 jobs a week in late winter, the owner reasons that they are stretched and a Saturday route is justified; when the average is lower, he concludes they have room.

I do not think that figure fits the decision. Jobs completed measures how busy the technicians are, not whether new customers are being served quickly. In a busy spring, technicians can complete the same number of jobs while new callers wait a week or more for a first visit, because the schedule is already full of existing customers' quarterly treatments. From my desk, I see those callers phone back after a few days to cancel, saying they found someone sooner. None of that shows up in jobs completed. Ridgway (1956) warned that performance measures shape what organizations pay attention to and can lead managers to optimize the measure rather than the outcome they care about. Here, a measure built to compare technicians is being used to answer a question about customer waiting.

Has anyone else seen a decision steered by a number that was originally built for a different purpose?

What I would want instead is a figure built for the question: how long new callers wait for their first visit in March, April and May. The job management system already records when a request is logged and when the first treatment is completed, so the number exists; nobody has asked for it.

What this page is doingThe figure's origin is stated, because it explains how a sensible business ended up steering by it.

Reply to Dana

Dana, your clinic decides how many front-desk staff to schedule from the number of patients checked in each day. I wonder what that number would do if the phone lines were overloaded. Checked-in patients could stay level while callers trying to book give up. Provost and Fawcett (2013) argue that data-driven decision making depends on asking which data actually bear on the decision, and here the calls that never become appointments might matter more than check-ins.

What this page is doingThe reply asks what the classmate's figure would look like if the problem were getting worse.

Reply to Marco

Marco, you said your warehouse decides on overtime by the number of orders shipped. Is that number ever high in the same weeks that orders are shipping late? If so, shipped orders might show effort rather than whether customers get what they ordered on time. Wang and Strong (1996) describe data quality as fitness for the user's purpose, which suggests asking whether shipped orders fit the overtime decision at all.

References

Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51-59. https://doi.org/10.1089/big.2013.1508

Ridgway, V. F. (1956). Dysfunctional consequences of performance measurements. Administrative Science Quarterly, 1(2), 240-247. https://doi.org/10.2307/2390989

Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5-33. https://doi.org/10.1080/07421222.1996.11518099

BUSI 3014 Week 1 instructions, in plain terms

The opening discussion of this certificate course asks you to describe one decision your workplace makes with a number and to judge whether the number fits. No calculation is required. Start with the decision and the person who owns it, since a decision described first lets readers judge fit rather than accuracy. Then name the figure the decision currently relies on and where it came from, because many workplace numbers were built for a different purpose. The middle of the post explains the mismatch: a situation where the figure looks fine while the thing the decision cares about gets worse. One citation from the assigned reading and a question to classmates complete a post of about 350 words. Two replies follow, each testing a classmate's figure against that classmate's decision.

How this BUSI 3014 Week 1 example is built

The sample opens with the owner's spring decision, the four weekday technicians and what a Saturday route would cost. The second paragraph names jobs completed per technician per week, its origin in a productivity report and the rule of thumb of about 34 jobs a week. The third explains the mismatch from the dispatcher's desk: technicians can stay busy with existing customers' treatments while new callers wait and then cancel, none of which the figure records. Ridgway's 1956 article on dysfunctional measures supports the argument. A last line invites the group to share numbers that were built for some other job. The reply to Dana asks whether a clinic's check-in count would hide callers who never get an appointment, citing Provost and Fawcett. The reply to Marco asks whether shipped orders can rise while orders ship late, citing Wang and Strong.

BUSI 3014 Week 1 rubric: what earns full marks

This first discussion is graded on fit rather than arithmetic. A post that opens on a named decision, identifies the figure behind it and shows a believable case where the two diverge meets the core of the task. Explaining where the figure came from earns credit, because it shows why a sensible organization ended up using it. Posts that criticize data in general, or propose a better number without describing the decision, miss the point. The citation should support the argument about fit rather than define a term. Replies are judged on whether they hold a classmate's figure against that classmate's own decision, ideally with a concrete situation in which the figure would mislead. Agreement without a test earns little.

Common BUSI 3014 Week 1 mistakes, and how to avoid them

Think of a choice someone at your workplace makes regularly: staffing, ordering, scheduling, pricing. Ask what number they look at when they make it, and find out where that number comes from. Then imagine a week in which the number looks healthy but the outcome the decision cares about gets worse. Write the post in that order: decision, figure, origin, mismatch. Common weaknesses include starting with the number, choosing a decision at the level of company strategy and offering opinions about data quality without a case. Keep it near 350 words. In replies, ask what the classmate's number would show in a bad week. Send the decision and the number it rests on at your workplace, and a sample post can be modeled on them.

Get a BUSI 3014 Week 1 example written to your instructions

Send the Week 1 board prompt with its rubric; the post, and replies if you want them, come back in 24 to 48 hours with the first sample free. If your own workplace has a decision you would rather write about, describe it in a sentence and leave the internal figures out; the sample builds an equivalent case around it.

More BUSI 3014 papers and BS in Business Administration samples

BUSI 3014 Week 1 questions, answered

Where can I find a free BUSI 3014 Week 1 sample paper?

You can read the Saturday route post, plus its pair of replies, here without paying.

What decision does the BUSI 3014 Week 1 example discuss?

A pest control owner's yearly choice about whether to add a Saturday route in the busy season.

Which figure does the decision rely on?

Jobs completed per technician per week, taken from a report originally built to compare technicians' productivity.

Why doesn't the figure fit the decision?

Technicians can complete as many jobs as usual while new callers wait a week or more, so the figure misses the customers the route would serve.

What do the replies ask classmates?

Whether a clinic's check-in count hides callers who never book, and whether a warehouse's shipped-order count can rise while orders ship late.