Background
The rapid digitization of the business world has paved the way for a multitude of virtual startups. These companies, unhindered by physical infrastructure, leverage wireless internet services to run their operations. Your startup, Tech Solutions, consists of a diverse team scattered worldwide, collaborating on projects, and sharing large files.
Objective
Your task is to identify the optimal wireless internet plan for the different profiles of users in your team, ensuring cost efficiency without compromising on the needed data. The team profiles are:
Developers who regularly upload and download large files.
Designers who utilize heavy graphics software and share high-resolution visuals.
Managers who mainly focus on communication (e.g., emails, video calls).
Sales and Marketing team that often requires a mix of communication tools, media sharing, and heavy browsing.
Three service providers have put forth their packages:
Mega Net: $20/month for up to 200 K-bytes. Additional data: $0.16/K-byte.
Ultra Connect: $50/month for up to 1000 K-bytes. Additional data: $0.08/K-byte.
Speed Wave: $100/month for up to 3000 K-bytes. Additional data: $0.04/K-byte.
Tasks:
(a) User Profiles: Estimate the monthly data usage for each team profile. Make an educated guess and tell which provider you think will eventually be chosen. Justify your assumptions. You will use these estimates to answer part (d).
(b) Algebraic Models: Develop cost functions, C(x), for each plan based on data usage, x. Each function should be in the form of a piece-wise function.
(c) Graphical Analysis: Plot the functions for each service provider. Analyze intersections to understand the best plan for different data usage levels. Graphing Utility InstructionsLinks to an external site.
Plotting the Functions:
Create a graph where the x-axis represents the amount of data usage, and the y-axis represents the cost.
For each service provider, there should be a distinct curve or line representing the cost as a function of data usage.
Each curve or line should be labeled or color-coded with a legend to distinguish between the service providers.
The graph should be appropriately scaled and labeled to ensure clarity and accuracy.
Identifying Intersections:
Accurately identify and mark the points where the curves or lines for the service providers intersect.
These intersections represent the data usage levels at which two service providers offer the same price.
Analysis of Intersections:
Analyze each intersection point to determine which service provider offers the best value before and after that data usage level.
For example, if Provider A and Provider B intersect at a certain point, students should be able to state which provider offers the best value for data usage levels below that point and which provider offers the best value for data usage levels above that point.
Implications for Best Plan Choices:
Based on the graph and the intersections, provide insights on which service provider offers the most cost-effective plan at different levels of data usage.
Highlight specific data usage thresholds where one plan becomes more cost-effective than another.
For example, “For data usage below X KB, Provider A is the most cost-effective, but for data usage above X KB, Provider B offers better value.”
(d) Optimal Plans: Determine which plan is most cost-effective for each user profile based on the estimated data usages from part (a).
(e) Company Savings: If Tech Solutions consists of 5 developers, 3 designers, 2 managers, and 4 sales/marketing members, calculate the potential savings of choosing the optimal plan for each profile versus the most expensive plan for all.
(f) Feedback to Providers: Based on your findings, draft a proposal to one of the providers suggesting improvements to their packages to make them more competitive for your startup’s needs.
Compose your project using MS Word and save as a .docx format. All information should be clear and legible, size 12 font.
Project 1 Rubric
Project 1 Rubric
Criteria Ratings Pts
This criterion is linked to a Learning OutcomeUser Profiles: Estimate the monthly data usage for each team profile. Make an educated guess and tell which provider you think will eventually be chosen. Justify your assumptions.
15 to >13.0 pts
Meets Expectations
Provides clear and well-estimated monthly data usage figures for each team profile; Offers a robust justification for each assumption made, grounding them in logical or researched reasoning; Demonstrates a deep understanding of the user profiles and how their usage patterns might differ.
13 to >11.0 pts
Approaches Expectations
Provides estimated monthly data usage for each team profile, but some figures may lack precision; Justifies most assumptions, though some explanations might be brief or lack depth; Shows a general understanding of the user profiles but may not fully account for specific nuances in their usage patterns.
11 to >9.0 pts
Below Expectations
Provides estimates for monthly data usage, but several figures are questionable or lack clarity; Offers limited justifications for assumptions, and some may be based on unclear or flawed reasoning; Demonstrates a surface-level understanding of the user profiles with significant oversights in estimating their usage.
9 to >0 pts
Limited Evidence
Fails to provide coherent estimates for monthly data usage or omits several team profiles; Provides minimal to no justification for assumptions or bases them on entirely flawed reasoning; Lacks a clear understanding of the user profiles, leading to largely incorrect or misguided estimates.
15 pts
This criterion is linked to a Learning OutcomeAlgebraic Models: Develop cost functions, C(x), for each plan based on data usage, x. Each function should be in the form of a piece-wise function
15 to >13.0 pts
Meets Expectations
Accurately develops cost functions C(x) for each plan. Each function is correctly structured as a piece-wise function, capturing all pricing tiers and overage costs. Demonstrates a comprehensive understanding of the plan structures and represents them correctly in algebraic form.
13 to >11.0 pts
Approaches Expectations
Develops cost functions C(x) for each plan but may have minor inaccuracies or omissions. Most functions are in the form of a piece-wise function, but there might be slight formatting or structural errors. Generally, understands the plan structures but may miss some subtleties in their algebraic representation.
11 to >9.0 pts
Below Expectations
Attempts to develop cost functions C(x), but there are notable errors or missing elements. Some functions are not in the correct piece-wise structure or contain significant misrepresentations of the plan costs. Demonstrates a limited understanding of the plan structures, leading to flawed algebraic models.
9 to >0 pts
Limited Evidence
Fails to provide coherent cost functions C(x) for the plans or omits significant portions. Does not correctly use the piece-wise structure or misapplies it entirely. Lacks a clear understanding of the plans, leading to largely incorrect or incomplete algebraic models.
15 pts
This criterion is linked to a Learning OutcomeGraphical Analysis: plot the functions for each service provider. Analyze intersections to understand the best plan for different data usage levels.
15 to >13.0 pts
Meets Expectations
Accurately plots the functions for each service provider on a suitable and well-labeled scale. Clearly identifies and marks intersections. Provides a comprehensive analysis of the intersections, correctly interpreting the implications for the best plan choice at different data usage levels.
13 to >11.0 pts
Approaches Expectations
Plots the functions for each service provider but may have minor inaccuracies or scale issues. Identifies intersections, but annotations may lack clarity. Provides an analysis of the intersections but may miss some subtleties in interpreting the best plan choice at specific data usage levels.
11 to >9.0 pts
Below Expectations
Attempts to plot the functions, but there are notable inaccuracies, or the scale is inappropriate. Struggles to correctly identify and mark intersections. Provides a partial or flawed analysis of the intersections and struggles to relate them to the best plan choices.
9 to >0 pts
Limited Evidence
Does not correctly plot the functions for the service providers or omits them entirely. Fails to identify intersections or misidentifies them. Offers little to no analysis of the intersections, and any provided interpretation is largely incorrect or unrelated to the task.
15 pts
This criterion is linked to a Learning OutcomeOptimal Plans: Determine which plan is most cost-effective for each user profile based on the estimated data usages from part (a).
15 to >13.0 pts
Meets Expectations
Accurately determines the most cost-effective plan for each user profile, making full use of the estimated data usages provided in part (a). Provides clear justification for each plan selection, grounding choices in the developed algebraic models. Demonstrates a comprehensive understanding of how data usage impacts plan cost and correctly applies this knowledge to the user profiles.
13 to >11.0 pts
Approaches Expectations
Determines the cost-effective plan for most user profiles, but there might be minor oversights or inaccuracies. Provides justifications for most plan selections, though some might be brief or lack depth. Shows a general understanding of the relationship between data usage and plan cost but may miss specific nuances in cost-effectiveness for some user profiles.
11 to >9.0 pts
Below Expectations
Attempts to determine the most cost-effective plan for user profiles, but several choices are questionable. Offers limited justifications for selected plans, with some explanations based on unclear or flawed reasoning. Demonstrates a limited understanding of how data usage impacts plan cost, leading to significant errors in plan selection for some user profiles.
9 to >0 pts
Limited Evidence
Fails to coherently determine the most cost-effective plans for the user profiles or omits significant portions. Provides minimal to no justification for selected plans or bases them on entirely flawed reasoning. Lacks a clear understanding of data usage implications on plan cost, resulting in largely incorrect or misguided plan recommendations.
15 pts
This criterion is linked to a Learning OutcomeCompany Savings: If Tech Solutions consists of 5 developers, 3 designers, 2 managers, and 4 sales/marketing members, calculate the potential savings of choosing the optimal plan for each profile versus the most expensive plan for all.
15 to >13.0 pts
Meets Expectations
Accurately calculates the total cost of the optimal plan for each profile, considering the number of team members in each category. Correctly calculates the total cost of the most expensive plan for all members. Precisely determines the potential savings between the two scenarios and presents the result clearly.
13 to >11.0 pts
Approaches Expectations
Calculates the total cost for most profiles accurately but might have minor inaccuracies or omissions. Mostly accurate in calculating the total cost of the most expensive plan, with slight discrepancies. Determines the potential savings, but the calculation might have minor errors or lack clarity in presentation.
11 to >9.0 pts
Below Expectations
Attempts to calculate the total cost for each profile, but there are notable errors or missing elements. Significant discrepancies in calculating the total cost of the most expensive plan. Struggles to correctly determine the potential savings, with multiple errors present.
9 to >0 pts
Limited Evidence
Fails to provide coherent calculations for the total costs or omits significant portions. Cannot correctly calculate the total cost of the most expensive plan. Provides minimal to no determination of the potential savings or gets it entirely incorrect.
15 pts
This criterion is linked to a Learning OutcomeFeedback to Providers: Based on your findings, draft a proposal to one of the providers suggesting improvements to their packages to make them more competitive for your startup’s needs.
15 to >13.0 pts
Meets Expectations
Presents a well-structured proposal that clearly addresses specific shortcomings of the chosen provider’s package based on the findings. Provides concrete suggestions for improvements that are aligned with the startup’s needs. Incorporates relevant data and analysis from previous parts to support the recommendations.
13 to >11.0 pts
Approaches Expectations
Presents a proposal that addresses some of the shortcomings of the provider’s package but might lack depth or detail in some areas. Offers suggestions for improvements, though some might be general or not entirely aligned with the startup’s needs. Uses some data and analysis from previous parts but might not fully integrate them into the recommendations.
11 to >9.0 pts
Below Expectations
Attempts to draft a proposal, but it lacks coherence or misses significant elements. The suggestions for improvements are either too vague, not particularly relevant, or lack justification. Limited use of data and previous findings, leading to weakly supported recommendations.
9 to >0 pts
Limited Evidence
The proposal is either extremely brief, largely off-target, or missing entirely. Provides minimal to no meaningful suggestions for improvements. Fails to incorporate any relevant data or findings from previous parts.
15 pts
This criterion is linked to a Learning OutcomeOrganization and Flow
5 to >4.0 pts
Meets Expectations
Cohesive/ Effective organization and flow
4 to >2.0 pts
Approaches Expectations
Adequate organization and flow
2 to >1.0 pts
Below Expectations
There are issues with the organization and flow
1 to >0 pts
Limited Evidence
The organization and flow are unclear
5 pts
This criterion is linked to a Learning OutcomeSpelling and Grammar
5 to >4.0 pts
Meets Expectations
No spelling or grammar errors
4 to >2.0 pts
Approaches Expectations
Spelling and grammar are mostly error-free
2 to >1.0 pts
Below Expectations
There are a few spelling and grammar errors
1 to >0 pts
Limited Evidence
There are many spelling and grammar errors
5 pts
Total Points: 100
