Project Requirements: We have to conduct an exploration on the use of Analytics
in an industry (we chose Healthcare) and summarize it as a report. The use of
Analytics may support any business function in the industry/firm: marketing,
product development, finance, supply chain, etc. The report prepared should
address all or most of the following: description of the industry/firm, the problem/ problems that are being solved in the industry/firm through Analytics, the tools
being used, the changing trends in the use of Analytics in that industry/firm and
any new breakthroughs that are anticipateed such as the adoption of artificial
intelligence or any other.
The project scope offers considerable flexibility to accomodate a student’s
individual interests and area that they want to explore as long as a significant
portion of the report is centered around a discussion on the need and application
of handling/analyzing data. This could include data visualization, data modeling, predictions/forecasts, optimization, simulations, to name a few of the topics
that we specifically cover in BUS 609 or any that may be outside of this list as
well.
Project Deliverable: The output will be a 3-5 page paper, single-spaced,
including any visuals and tables that you include in the report. Please cite your
sources in a concluding section titled “References.”
As a clarification, the project requirements do not require you to collect data and
analyze it. The focus is on uncovering the use of analytics in a certain industry
and summarizing in a report.
Category: Business Analytics
Utilise Monte
Carlo simulation to perform a risk analysis of profitability levels in the Aberdeen
Homeware department (Note: the analysis should assume overall gross profit
margins between 60% to 70% on revenue sales. The department also makes a daily
contribution to overheads of £4,250. Use
non-promotion sales only for your simulation).
This is the steps suggested in class
1. Gross Profit Margin (GPM): Randomly generate the gross profit margin as a percentage between 60% and 70%.
2. Daily Sales Revenue: This value can be estimated based on historical data or assumed based on average market conditions. If not available, you might assume a range and then randomly generate sales data from within this range for the simulation.
3. Fixed Daily Overheads: £4,250 contribution to overheads per day.
4 Simulation Size: Decide how many simulations you want to run. A larger number, like 1,000, would typically provide more robust results.
5 Revenue Model: Define the range or distribution of daily sales revenue. This can be modeled based on historical data (e.g., normal distribution, log-normal distribution).
6 Profit Calculation: For each iteration, calculate the daily profit using:
Daily Profit
=
(
Daily Sales Revenue
×
Gross Profit Margin
)
−
Fixed Daily Overheads
Daily Profit=(Daily Sales Revenue×Gross Profit Margin)−Fixed Daily Overheads
Utilise Monte
Carlo simulation to perform a risk analysis of profitability levels in the Aberdeen
Homeware department (Note: the analysis should assume overall gross profit
margins between 60% to 70% on revenue sales. The department also makes a daily
contribution to overheads of £4,250. Use
non-promotion sales only for your simulation).
This is the steps suggested in class
1. Gross Profit Margin (GPM): Randomly generate the gross profit margin as a percentage between 60% and 70%.
2. Daily Sales Revenue: This value can be estimated based on historical data or assumed based on average market conditions. If not available, you might assume a range and then randomly generate sales data from within this range for the simulation.
3. Fixed Daily Overheads: £4,250 contribution to overheads per day.
4 Simulation Size: Decide how many simulations you want to run. A larger number, like 1,000, would typically provide more robust results.
5 Revenue Model: Define the range or distribution of daily sales revenue. This can be modeled based on historical data (e.g., normal distribution, log-normal distribution).
6 Profit Calculation: For each iteration, calculate the daily profit using:
Daily Profit
=
(
Daily Sales Revenue
×
Gross Profit Margin
)
−
Fixed Daily Overheads
Daily Profit=(Daily Sales Revenue×Gross Profit Margin)−Fixed Daily Overheads
Demand for French bread at Howie’s Bakery
Howie’s Bakery is one of the most popular bakeries in town, and the favorite at Howie’s is French bread. Each day of the week, Howie’s bakes a number of loaves of French bread, more or less according to a daily schedule. To maintain its fine reputation, Howie’s gives away to charity any loaves not sold on the day they are baked. Although this occurs frequently, it is also common for Howie’s to run out of French bread on any given day—more demand than supply. In this case, no extra loaves are baked that day; the customer have to go elsewhere (or come back to Howie’s the next day) for their French bread. Although French bread at Howie’s is always popular, Howie’s stimulates demand by running occasional 10% off sales.
Howie’s has collected data for 20 consecutive weeks, 140 days in all. These data are listed in the file Case3_French Bakery.xlsx. The variables are Day (Monday—Sunday). Supply (number of loaves baked that day), On Sale (whether French bread is on sale that day), and Demand (loaves actually sold that day). Howie’s would like you to see whether regression can be used successfully to estimate Demand from the other data in the file. Howie’s reasons that if these other variables can be used to predict Demand, then he might be able to determine his daily supply (number of loaves to bake) in a more cost-effective way.
How successful is regression with these data? Is Howie correct that regression can help him determine his daily supply?
Is any information missing that would be useful? How would you obtain it? How would you use it? Is this extra information really necessary?
Please submit a WORD document of at least two pages, 12 font Times New Roman, single-spaced, including background information, data analysis, results and interpretation, and managerial conclusions for the specific company.
Link on how to write an equation in word
https://support.microsoft.com/en-us/office/write-an-equation-or-formula-4f799df7-4ca4-4670-afd3-6135768b01d0