Week 2 Statistical Report

Week 2 Statistical Report

Week 2 Statistical Report

Resources: Pastas R Us, Inc. Database & Microsoft Excel®, Wk 1: Descriptive Statistics Analysis Assignment

Purpose 

This assignment is intended to help you learn how to apply statistical methods when analyzing operational data, evaluating the performance of current marketing strategies, and recommending actionable business decisions. This is an opportunity to build critical-thinking and problem-solving skills within the context of data analysis and interpretation. You’ll gain a first-hand understanding of how data analytics supports decision-making and adds value to an organization.

Scenario: 

Pastas R Us, Inc. is a fast-casual restaurant chain specializing in noodle-based dishes, soups, and salads. Since its inception, the business development team has favored opening new restaurants in areas (within a 3-mile radius) that satisfy the following demographic conditions:

• Median age between 25 – 45 years old
• Household median income above national average
• At least 15% college educated adult population

Last year, the marketing department rolled out a Loyalty Card strategy to increase sales. Under this program, customers present their Loyalty Card when paying for their orders and receive some free food after making 10 purchases.

The company has collected data from its 74 restaurants to track important variables such as average sales per customer, year-on-year sales growth, sales per sq. ft., Loyalty Card usage as a percentage of sales, and others. A key metric of financial performance in the restaurant industry is annual sales per sq. ft. For example, if a 1200 sq. ft. restaurant recorded $2 million in sales last year, then it sold $1,667 per sq. ft.

Executive management wants to know whether the current expansion criteria can be improved. They want to evaluate the effectiveness of the Loyalty Card marketing strategy and identify feasible, actionable opportunities for improvement. As a member of the analytics department, you’ve been assigned the responsibility of conducting a thorough statistical analysis of the company’s available database to answer executive management’s questions.

Report: 

Write a 750-word statistical report that includes the following sections:

• Section 1: Scope and descriptive statistics
• Section 2: Analysis
• Section 3: Recommendations and Implementation

Section 1 – Scope and descriptive statistics

• State the report’s objective.
• Discuss the nature of the current database. What variables were analyzed?
• Summarize your descriptive statistics findings from Excel. Use a table and insert appropriate graphs.

Section 2 – Analysis 

• Using Excel, create scatter plots and display the regression equations for the following pairs of variables:
• “BachDeg%” versus “Sales/SqFt”
• “MedIncome” versus “Sales/SqFt”
• “MedAge” versus “Sales/SqFt”
• “LoyaltyCard(%)” versus “SalesGrowth(%)”
• In your report, include the scatter plots. For each scatter plot, designate the type of relationship observed (increasing/positive, decreasing/negative, or no relationship) and determine what you can conclude from these relationships.

Section 3: Recommendations and implementation

• Based on your findings above, assess which expansion criteria seem to be more effective. Could any expansion criterion be changed or eliminated? If so, which one and why?
• Based on your findings above, does it appear as if the Loyalty Card is positively correlated with sales growth? Would you recommend changing this marketing strategy?
• Based on your previous findings, recommend marketing positioning that targets a specific demographic. (Hint: Are younger people patronizing the restaurants more than older people?)
• Indicate what information should be collected to track and evaluate the effectiveness of your recommendations. How can this data be collected? (Hint: Would you use survey/samples or census?)

Cite references to support your assignment.

Format your citations according to APA guidelines.

ChartDataSheet_

Restaurant chain

Pastas R Us, Inc. 9

Restaurant chain

David Leonard

University of Phoenix

DAT/565

Scope and descriptive statistics

Analyzing and transforming data sets that are related to company operations into information that can be utilized to make business decisions is the goal of data analytics. For pasta, the information gleaned from the data research will be put to good use in refining restaurant regulations, menus, training programs for employees, and advertising initiatives. Larger establishments, such as Pasta, may have upwards of ten suppliers on their payroll, making it necessary to invest in an accurate analytics system. The majority of restaurants employ analytic tools to find ways to analyze and use big data in order to acquire insights.

Objective

This study’s major goal is to analyze statistics in order to:

I. Comprehend if the current expansion criteria can be upgraded

II. II. Assess the recent introduction of the Loyalty Card marketing strategy’s efficacy.

III. III. Create an assessment of the attainable, tangible possibilities which demand enhancement

The descriptive analysis in this example made use of such a number of different variables. The variables used in this study were: company area in sq ft, average expenditure per customer in a restaurant, sales rise throughout the period, loyalty program share of net sales, annual sales per sq. ft., median wage and population age (Liu & Tse, 2018).

The descriptive analysis

Seventy-four samples were used for analysis in total. The median sq ft According to the following table’s specific research, a bulk of restaurants are 2580 square feet in size. (Kadim & Sunardi, 2019). Revenue growth is 7.4 percent on average, while sales per person are 7.0, with an average of 420 sales per square foot for businesses.

Analysis

Scatter plot of BachDeg% versus Sales/SqFt

The association between BachDeg/sales/square feet is positive because when the X-values go right, the Y-values rise up, increasing the relationship (Mavridou, Bergmans, Barendregt & Lambrechts, 2017). The evidence exhibits a positive association which implies as the revenue for capacity of the establishment increases the BachDeg rises..

Scatter plot for Med Income versus Sales/SqFt

A similar pattern can be seen here, with the scatter plot showing an increase in sales per square foot in correlation with a rise in median income. The sort of connection that develops in this scenario is a positive marriage. This is because when the X-values rise (move right), the Y-values tend to increase (move up) (move up). The action takes place mostly in the middle of the frame (Liu & Tse, 2018). It is because of this focus that we deduce that med earnings increases against revenues per square.

Scatter Plot MedAge versus Sales/SqFt

In this particular instance, there is no such link. According to the assessment, the measured values show no sharp rise on either the X-axis or the Y-axis.

LoyaltyCard (%) versus Sales Growth (%)

Consequently, there seems to be a favorable connection in this situation since there is a large rise in the X-axis as the Y-axis grows..

Recommendations and implementation

As per the analysis, BachDeg percent and Sales/SqFt correspond and are much more economical when employed by the firm to make the necessary adjustments to enhance everyday operations (Mavridou, Bergmans, Barendregt & Lambrechts, 2017). Also, the scatter plot of MedAge vs Sales/SqFt shows no association between age and sales per square foot. We may also use the line graph to see whether their current connection.

According to the line graph above, there appears to be no significant correlation seen between age category and sales per square foot that is significant (Liu & Tse, 2018). It doesn’t matter how many sales square feet a business has since the average life span doesn’t change.. Ultimately, the new loyalty card and increased sales have a beneficial link.

Recommendations

Based on the aforementioned descriptive study, the firm needs adjust and enhance several tactics to boost revenue. This includes marketing based on Bachelor’s degrees (3 miles) and sales per square foot. Aside from the general market, the firm should target those under the age of 35. The majority of adults aged 34 like to be served in restaurants.

Unlike other organizations, obtaining data from a restaurant is not difficult. Data may be collected from passports and national identity cards. With the exception of the ID cards, the information may be retrieved from the contact details supplied by the clients upon registering in. Many Point – of – sale technologies allow restaurants to access restaurant demographic data, which may be supplemented by public information. This data storage and management will supply unlimited effective segmentation information.

References

Kadim, A., & Sunardi, N. (2019, May). Eviews Analysis; Determinan Tourism, Restaurant and Hotel Company’s Soundness and Performance. In Proceeding Interuniversity Forum for Strengthening Academic Competency (Vol. 1, No. 1, pp. 332-340).

Mavridou, A. M., Bergmans, L., Barendregt, D., & Lambrechts, P. (2017). Descriptive analysis of factors associated with external cervical resorption. Journal of endodontics, 43(10), 1602-1610.

Liu, P., & Tse, E. C. Y. (2018). Exploring factors on customers’ restaurant choice: an analysis of restaurant attributes. British Food Journal.

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