Problem Creating A Spreadsheet For Decision Support In This

Problemcreating A Spreadsheet For Decision Supportin This Assignment

Develop a comprehensive spreadsheet model for Philly Landscaping’s 2017 revenues, expenses, and profits. The spreadsheet should forecast cash flows over 10 years, starting from 2017, with the capability to input variables to analyze different scenarios. The model must include sections for constants (assumptions), inputs, key results summaries, and detailed calculations. It should account for customer base growth or decline, loan repayment, and retirement income goals, allowing for scenario testing via Excel’s Scenario Manager. The spreadsheet must appropriately calculate service revenues, expenses, taxes, net income, and other relevant metrics, supporting decision analysis, including whether the company can hire a manager and meet retirement income needs. Finally, prepare a Word memorandum summarizing your analysis, testing scenarios, and conclusions, supported by graphical and tabular data derived from the Excel model.

Paper For Above instruction

The development of a decision support spreadsheet for Philly Landscaping encapsulates strategic financial planning, scenario analysis, and forecasting critical for business decision-making and retirement planning. This project aims to comprehensively model the company's financial future from 2017 through 2027, providing insights into revenue streams, expense management, cash flows, and the feasibility of various retirement income goals, all within an adaptable framework capable of scenario testing.

The spreadsheet design begins with defining constants, capturing essential assumptions such as service prices, average surface and linear measurements for each service, and historical cost data supplied by Steve. These constants serve as the foundation for calculating revenues and expenses across the modeled years. For each service—yard work, gutter cleaning, power washing, lawn mowing, driveway sealing, leaf clearing, and snow removal—the model multiplies the average service requests (determined by customer base and service request rates) by unit prices from the constants, thereby deriving annual revenues.

Next, the model incorporates input variables such as the expected percentage change in the customer base, the annual loan payment ($120,000), and the desired retirement income ($75,000 to $100,000). These inputs enable the simulation of business growth or contraction, loan repayment capacity, and retirement income sufficiency. The model then calculates intermediate results—such as total revenue, labor and material costs, loan repayment, total expenses, income before taxes, taxes at a 25% rate, and net income—breaking down complex calculations into manageable steps for easier troubleshooting.

A vital component of the spreadsheet is the scenario analysis setup. Four scenarios are outlined to evaluate different growth and financial assumptions, tested through Excel's Scenario Manager. This feature allows for dynamic assessment of how changes in customer base growth, loan repayment, and other inputs influence the company's cash flows and ability to meet retirement objectives. The key results—annual income, managerial hiring feasibility, and income surpassing the desired annuity—are summarized to compare scenarios effectively.

Analysis of the results from these modeled scenarios yields critical insights. For instance, with moderate customer growth and aggressive loan repayment, the business may generate sufficient cash flow to hire a manager and reach retirement needs. Conversely, unfavorable growth or high expenses might jeopardize retirement goals. These findings are visually supported through graphs and tables, facilitating clear communication of complex quantitative data.

The final step involves constructing a succinct Word memo that details the business context, explains the tested scenarios, and articulates the conclusions. The memo employs a structured format, beginning with an overview, followed by scenario descriptions, findings, and strategic recommendations supported by the model's graphical data. This document enables Steve to understand the financial trajectory and make informed decisions regarding business operations and retirement planning.

In conclusion, this project demonstrates the practical application of spreadsheet modeling for decision support in a small business context. It integrates financial data, scenario analysis, and strategic forecasting into a single, versatile tool. Such modeling not only aids in operational decisions but also supports long-term planning, ensuring that Philly Landscaping's owner can achieve his retirement objectives while maintaining a sustainable business growth trajectory.

References

• Brigham, E. F., & Ehrhardt, M. C. (2016). Financial Management: Theory & Practice. Cengage Learning.
• Heisinger, K., & Hoyle, J. (2018). Managerial Accounting. McGraw-Hill Education.
• Excel Campus. (2020). Mastering Scenario Manager. https://www.excelcampus.com
• Benninga, S. (2014). Financial Modeling. The MIT Press.
• Ross, S. A., Westerfield, R. W., & Jordan, B. D. (2019). Corporate Finance. McGraw-Hill Education.
• Shim, J. K., & Siegel, J. G. (2012). Financial Management. Barron's Educational Series.
• Albrecht, W. S., & Sack, R. J. (2014). Accounting Standards: A Decision Framework. Wiley.
• Microsoft Office Support. (2021). Use Scenario Manager to compare what-if scenarios. https://support.microsoft.com
• Investopedia. (2023). Cash Flow Forecast. https://www.investopedia.com
• Khan, M. Y., & Jain, P. K. (2007). Financial Management. Tata McGraw-Hill Education.