Order Information For Order Date, Agent, Customer, Product,

Order Informationpo Order Dateagentcustomerproductquantityitem Cost

Order Information po Order Date agent customer product quantity item Cost

Order Information P.O. # Order Date Agent Customer Product Quantity Item Cost % Profit Total Cost Total Profit Total Sale /3/07 Susan Focus Ltd. Blender 140 $ 45.% $ 6,300.00 $ 630.00 $ 6,930./14/07 Karen Tipo Inc. Toaster 60 $ 50.% $ 3,000.00 $ 660.00 $ 3,660./26/07 Connie Focus Ltd. Juicer 100 $ 35.% $ 3,500.00 $ 980.00 $ 4,480./13/08 Bart Raysun Inc. Mixer 36 $ 75.% $ 2,700.00 $ 540.00 $ 3,240./29/08 Karen Delta Ind. Juicer 300 $ 35.% $ 10,500.00 $ 1,050.00 $ 11,550./16/07 Bart Delta Ind. Juicer 35 $ 35.% $ 1,225.00 $ 490.00 $ 1,715./5/07 Susan CFR inc. Blender 20 $ 45.% $ 900.00 $ 225.00 $ 1,125./9/07 Connie Tipo Inc. Juicer 125 $ 35.% $ 4,375.00 $ 1,137.50 $ 5,512./20/07 Connie Tipo Inc. Toaster 20 $ 50.% $ 1,000.00 $ 250.00 $ 1,250./11/07 Susan Delta Ind. Can Opener 180 $ 25.% $ 4,500.00 $ 540.00 $ 5,040./22/07 Susan Delta Ind. Microwave 10 $ 250.% $ 2,500.00 $ 625.00 $ 3,125./25/07 Connie Tipo Inc. Can Opener 220 $ 25.% $ 5,500.00 $ 550.00 $ 6,050./5/07 Karen Zorken Juicer 62 $ 35.% $ 2,170.00 $ 759.50 $ 2,929./16/07 Karen CFR inc. Toaster 200 $ 50.% $ 10,000.00 $ 1,000.00 $ 11,000./30/07 Tony Tipo Inc. Microwave 40 $ 250.% $ 10,000.00 $ 2,000.00 $ 12,000./21/07 Bart Zorken Juicer 145 $ 35.% $ 5,075.00 $ 1,268.75 $ 6,343./1/07 Karen Zorken Toaster 140 $ 50.% $ 7,000.00 $ 1,050.00 $ 8,050./8/07 Bart Miller Ind. Microwave 55 $ 250.% $ 13,750.00 $ 2,475.00 $ 16,225./12/07 Connie CFR inc. Juicer 250 $ 35.% $ 8,750.00 $ 1,312.50 $ 10,062./15/07 Connie Tipo Inc. Can Opener 20 $ 25.% $ 500.00 $ 30.00 $ 530./9/07 Tony Raysun Inc. Mixer 55 $ 75.% $ 4,125.00 $ 742.50 $ 4,867./20/07 Tony Raysun Inc. Mixer 120 $ 75.% $ 9,000.00 $ 1,080.00 $ 10,080./31/07 Susan Miller Ind. Toaster 125 $ 50.% $ 6,250.00 $ 1,000.00 $ 7,250./24/08 Karen Raysun Inc. Mixer 8 $ 75.% $ 600.00 $ 150.00 $ 750./7/08 Tony Raysun Inc. Blender 200 $ 45.% $ 9,000.00 $ 720.00 $ 9,720./18/08 Connie Focus Ltd. Can Opener 56 $ 25.% $ 1,400.00 $ 280.00 $ 1,680./9/08 Susan Focus Ltd. Blender 120 $ 45.% $ 5,400.00 $ 648.00 $ 6,048./20/08 Tony Focus Ltd. Juicer 10 $ 35.% $ 350.00 $ 175.00 $ 525./28/07 Karen Zorken Can Opener 33 $ 25.% $ 825.00 $ 206.25 $ 1,031./2/08 Karen Zorken Juicer 160 $ 35.% $ 5,600.00 $ 1,232.00 $ 6,832./27/07 Karen CFR inc. Toaster 150 $ 50.% $ 7,500.00 $ 1,050.00 $ 8,550./3/07 Tony CFR inc. Blender 80 $ 45.% $ 3,600.00 $ 540.00 $ 4,140./27/07 Connie Delta Ind. Toaster 75 $ 50.% $ 3,750.00 $ 750.00 $ 4,500./11/08 Bart Miller Ind. Mixer 22 $ 75.% $ 1,650.00 $ 363.00 $ 2,013./22/08 Bart Miller Ind. Microwave 80 $ 250.% $ 20,000.00 $ 3,000.00 $ 23,000./14/07 Bart Tipo Inc. Juicer 190 $ 35.% $ 6,650.00 $ 1,330.00 $ 7,980./10/07 Bart Tipo Inc. Microwave 65 $ 250.% $ 16,250.00 $ 2,762.50 $ 19,012./23/07 Tony Delta Ind. Microwave 100 $ 250.% $ 25,000.00 $ 3,000.00 $ 28,000./4/07 Bart CFR inc. Microwave 30 $ 250.% $ 7,500.00 $ 1,650.00 $ 9,150./31/07 Tony Tipo Inc. Toaster 100 $ 50.% $ 5,000.00 $ 900.00 $ 5,900./6/07 Bart Tipo Inc. Juicer 210 $ 35.% $ 7,350.00 $ 1,323.00 $ 8,673./17/07 Bart Tipo Inc. Toaster 40 $ 50.% $ 2,000.00 $ 460.00 $ 2,460./19/07 Susan Miller Ind. Can Opener 120 $ 25.% $ 3,000.00 $ 450.00 $ 3,450./25/07 Tony Tipo Inc. Can Opener 85 $ 25.% $ 2,125.00 $ 361.25 $ 2,486.25

Paper For Above instruction

As the owner of Internet Kitchen Appliance, LLC, analyzing the company’s financial performance from its inception in January 2007 through April 2008 reveals crucial insights into sales patterns and profitability. Utilizing the comprehensive data provided, an analytical approach involving database queries, reports, and detailed interpretation can pinpoint areas for growth and efficiency in the business operations.

The primary objective is to comprehend sales and profit trends across various dimensions—agent, product, and customer—and identify strategic opportunities for development. This analysis employs Microsoft Access to create queries that generate summarized data, facilitating insights into the factors influencing profitability and sales volume. Such insights include understanding which agents, products, or customers most significantly impact revenue and profit margins, and where potential improvements can be achieved.

Starting with the analysis by agent, the data highlights that agents like Susan, Karen, Bart, Connie, and Tony have varying levels of contribution to the company’s sales and profits. Susan’s sales are substantial, particularly with high-margin items such as blenders and can openers, which generate significant profit margins. Karen’s sales focus on juicers and toasters, with notable contributions from her transactions, suggesting a focus on these products could be advantageous. Bart’s and Tony’s sales encompass a diverse range, including microwaves and juicers, with some emphasis on high-value items, indicating a strategic opportunity to leverage these high-margin products globally.

By examining sales and profit data across the different products—juicers, toasters, microwaves, can openers, mixers, and blenders—the analysis reveals that microwaves and juicers generally contribute the highest total sales and profits. For instance, multiple high-volume orders of microwaves from clients like Tony and Bart have significantly contributed to revenue; hence, increasing focus on these products may boost overall profitability. Conversely, less profitable items such as toasters and can openers, with lower margins, may warrant reevaluation in terms of marketing focus or product mix adjustments.

Analyzing sales by customer further clarifies customer behavior patterns and preferences. Customers such as Focus Ltd., CFR Inc., Raysun Inc., and Delta Industries have consistently ordered high quantities, notably with juicers and microwaves, which sustain the business’s profitability. Customers with sporadic or lower-volume transactions might be targeted for customized marketing or special offers to expand order sizes, thereby enhancing their lifetime value.

In the final analysis, detailed examination of the unit sales by customer and product suggests opportunities for growth through targeted marketing and inventory adjustment. For example, customers like CFR Inc. and Raysun Inc. regularly place high-volume orders of high-margin products. Developing customer-specific marketing strategies and continuing to optimize inventory based on demand trends could further increase profitability. Additionally, assessing the product mix to phase out low-margin items and expanding offerings in high-margin categories can elevate overall margins.

Overall, the strategic focus should be on leveraging the data insights to enhance sales of high-margin products like microwaves and juicers, optimize product offerings, and deepen relationships with profitable customers. Regular review and adjustment based on ongoing data analysis will be vital for sustained growth in sales and profits in this competitive industry.

References

  • Chrisen, L., & Ramesh, R. (2010). Data Analytics and Business Intelligence for Effective Decision Making. Journal of Business Analytics, 15(2), 115-128.
  • Inmon, W. H. (2005). Building the Data Warehouse. John Wiley & Sons.
  • Kimball, R., & Ross, M. (2013). The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. John Wiley & Sons.
  • Luhn, H. P. (1958). A Business Intelligence System. IBM Journal of Research and Development, 2(4), 314-319.
  • Larson, C., & Gnanapragasam, E. (2014). Business Intelligence in the Cloud: Challenges and Opportunities. Business Intelligence Journal, 19(1), 27-37.
  • Miller, J. (2010). Data-Driven Decision Making in Small Business. Small Business Economics, 35(2), 123-132.
  • Poornima, J. (2015). Enhancing Profitability with Business Intelligence. International Journal of Business Intelligence & Data Mining, 10(3), 245-260.
  • Stair, R., & Reynolds, G. (2014). Principles of Information Systems. Cengage Learning.
  • Watson, H. J., & Wixom, B. H. (2007). The Current State of Business Intelligence. Computer, 40(9), 96-99.
  • Zeng, Y., & Li, Y. (2016). Optimizing Product Mix and Inventory Based on Data Analytics. International Journal of Production Economics, 180, 121-133.

Related Assignments