Activity 4 Submission Please Refer To The Case Overview In U
Activity 4 Submissionplease Refer To The Case Overview In Units 1
Please refer to the case overview in Units 1 & 2 for the business premise and situation. This week, you will continue to work on The Broadway Café as it struggles to compete in the 21st century. Each week, you will submit your response to the business situation presented. Your paper should be in APA format with a Title page and a References page. The paper must be double-spaced using Times New Roman size 12 font and written in an essay format; do not use a question and answer format.
Data are raw facts describing characteristics of an event, such as date, item number, description, quantity ordered, customer name, and shipping details. Information is data converted into a meaningful and useful context, for example, identifying best-selling or worst-selling items or customers.
Business intelligence involves using information to support decision-making. An analogy from Sun Tzu’s The Art of War suggests that success depends on understanding one’s strengths and weaknesses, as well as those of the enemy. In business, this means collecting data, discerning patterns, and responding accordingly to gain competitive advantage.
Business Dilemma Part 1
You maintain various customer lists (e.g., Music, Art Gallery, Book Club). You plan to send a monthly newsletter discussing coffee trends and community events, primarily using postal mail. You currently have customer data for email addresses but are unsure of their accuracy and wish to include physical mailing addresses. Since you want to include a coupon for a free coffee in each newsletter, you prefer to use postal mailing rather than email to control the distribution of the coupons.
Part 1: Data Analysis
Analyze the provided customer data and determine whether it is suitable for mailing your newsletters. Highlight issues with the data, potential causes, and solutions to correct these issues. The data is as follows:
- ID: 434; First Name: Pam; Middle Initial: J; Last Name: Hetz; Address: 13 First Ave, Denver, CO; Phone: Brain F Hoover; Lake Ave., Columbus, CO; Other details missing or incomplete.
- Bob X Kenzie, 65 Apple Lane, Golden, CO
- Alana B 567 55 St., Denver, CO
- Debbie F Fernandez, 567 55 St., Denver, CO
- Diego J Quintos, 2121 One St., Golden, CO 65667
Note: The data is inconsistent; some entries lack complete address information, and some contain extraneous or corrupted data like phone numbers or mixed data formats. This impairs the ability to reliably send physical mail.
Part 2: Business Decisions
You have extensive data to inform strategic decisions for the café. Consider various dimensions and rank them from 1 (highest value) to 5 (lowest value) based on their importance for a data mart focused on sales and market analysis. If limited to 10 dimensions, choose the top variables accordingly. The dimensions are:
- Product Price
- Weather
- Customer Gender
- To Go or Dine In
- Order Quantity Sold
- Stock Market Closing Price
- Order Date
- Employee Number
- Payment Method
- Promotion Number
- Product Cost
- Customer Age
- Order Time
- Customer Religious Affiliation
- Exchange Rate
- Manufacturer or Vendor Number
- Interest Rate
- Music Playing in Store
- Season
- Customer Name
- Customer’s Political Affiliation
- Product Number
- Store Hours
- Customer Language
- Commission Policy
- Traffic Report
Based on strategic value, select and rank ten dimensions for inclusion in the data mart for effective analysis.
Paper For Above instruction
Introduction
The success of modern businesses relies heavily on effective data collection and analysis to inform strategic decision-making. The Broadway Café, like many establishments competing in the 21st century, must leverage business intelligence to remain relevant and competitive. This paper addresses two key challenges: first, assessing the quality and suitability of customer data for physical mailing campaigns; second, selecting the most valuable data dimensions for creating a sales and market analysis data mart to support strategic planning.
Part 1: Data Quality and Mailing Suitability
The provided customer data exhibits significant issues that impede its immediate use for physical mailing campaigns. Notably, there are incomplete addresses, inconsistent formatting, and extraneous data, such as phone numbers or other non-address information. For example, one entry lists "Brain F Hoover" in the street address field, which clearly indicates data corruption or entry errors. Such inaccuracies compromise the ability to reliably deliver physical mail, risking lost or misdelivered newsletters. A secondary issue involves missing or partial address data, such as the unclear address entries for individuals like Alana B and Debbie F Fernandez, which do not specify full street addresses or ZIP codes.
The root causes of these issues are likely lapses in data entry protocols, inconsistent data collection methods, and possibly inadequate data validation processes. The data collection process appears to prioritize email addresses, which may have led to neglecting or improperly recording physical mailing information.
To rectify these issues, implementing standardized data collection templates and validation rules is critical. Such rules should enforce complete addresses, correct ZIP code formats, and separate contact data into distinct fields. Regular data cleaning procedures, including duplicate checks, address verification tools (such as USPS address validation services), and manual audits, can significantly improve data accuracy. Investing in customer relationship management (CRM) software with integrated validation features can prevent future issues and ensure consistency in data collection.
Part 2: Strategic Data Dimension Selection
When constructing a data mart for sales and market analysis, selecting dimensions that offer high strategic value is essential. The prioritized dimensions enable a comprehensive understanding of sales patterns, customer preferences, and operational efficiency. Based on their potential usefulness, the top five dimensions are:
- Order Date: Critical for trend analysis and seasonal forecasting.
- Product Price: Enables profit margin calculations and pricing strategy development.
- Customer Age: Helps segmentation and targeted marketing.
- Order Quantity Sold: Acts as a measure of sales volume and demand.
- Payment Method: Provides insight into payment preferences and potential credit risk.
Other dimensions such as Weather and Store Hours are valuable but secondary; they offer context but are less directly impactful on strategic decisions compared to core sales data. Dimensions like Traffic Report and Music Playing in Store, while influencing customer experience, are less critical for data analysis than primary transactional and demographic data.
In conclusion, an effective data mart should incorporate the above high-value dimensions to enable detailed sales analysis, enhance customer segmentation, and optimize operational strategies. The cleaning and validation of customer data are preliminary yet vital steps before leveraging these insights for business growth.
Conclusion
Effective business intelligence depends on high-quality data and strategic selection of key variables. Addressing data integrity issues ensures reliable mailing campaigns, while thoughtful dimension selection empowers better decision-making. By implementing robust data collection and management practices, The Broadway Café can improve its competitive position and effectively harness the power of business intelligence for sustained growth.
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