Tp Fashions - Houston Store Expense Breakdown (Forecast) ✓ Solved

Tp Fashions - Houston Store Breakdown of Expenses (Forecast)

Tp Fashions - Houston Store Breakdown of Expenses (Forecast). Prepare a forecasted income statement using the figures provided: Revenues (Forecast) 1,400,000; Revenues (Actual) 1,260,000. Cost of Sales (Forecast) 790,000; Gross Profit (Forecast) 610,000; Gross Profit (Actual) 500,000; Expenses include Management 182,000; Shop assistants 258,000; Rent 23,000; Utilities 34,000; Misc. expenses 24,000; Total expenses (Forecast) 522,500; Total expenses (Actual) 526,000; Net income (Forecast) 87,500; Net income (Actual) -26,000.

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Introduction and Data Summary

The provided data represent a forecasted and actual view of Tp Fashions’ Houston store, focusing on revenues, cost of sales, gross profit, and a breakdown of operating expenses. The forecasted figures show a revenue of 1,400,000 with cost of sales of 790,000, yielding a forecast gross profit of 610,000. The actual figures show revenue of 1,260,000 and a gross profit of 500,000. From these data, we can derive the implied actual cost of sales as 1,260,000 minus 500,000, which equals 760,000. This aligns with standard income statement construction where Gross Profit = Revenues – Cost of Sales, and where any discrepancy between forecast and actual performance cascades through the expense line and net income (Horngren et al., 2013; Weygandt et al., 2019).

Beyond the gross profit line, the expense categories are listed as Management (182,000), Shop assistants (258,000), Rent (23,000), Utilities (34,000), and Miscellaneous expenses (24,000). Forecast total expenses are 522,500; actual total expenses are 526,000. The forecasted net income is 87,500, while the actual net income is -26,000. These data points provide a clear basis for a variance analysis, which is a common managerial accounting practice used to understand where performance diverges from plan (Hilton et al., 2009; Drury, 2013).

Variance Calculations and Interpretation

Revenue variance (Actual vs. Forecast) = 1,260,000 – 1,400,000 = -140,000. This represents a shortfall of 140,000, or a decline of about 10% relative to forecasted revenue (1,400,000). Cost of sales variance (Forecast vs. Actual) can be inferred from the gross profit figures: Actual Gross Profit (500,000) = Actual Revenues (1,260,000) – Actual Cost of Sales (X). Therefore, Actual Cost of Sales = 1,260,000 – 500,000 = 760,000; Cost of Sales variance = 760,000 – 790,000 = -30,000. The forecast gross profit was 610,000; the actual gross profit is 500,000, so gross profit variance = 500,000 – 610,000 = -110,000, driven primarily by revenue shortfall despite a lower cost of sales (Ni, 2013; Garrison et al., 2019).

Expense variances show total expenses forecast at 522,500 and actual expenses at 526,000, a variance of 3,500 over budget. The net income variance is -113,500 (Forecast 87,500 vs. Actual -26,000), reflecting the combined effect of revenue shortfall and modestly higher expenses (Horngren et al., 2013; Hilton et al., 2009).

From a margin perspective, forecast gross margin = 610,000 / 1,400,000 ≈ 43.6%, while actual gross margin = 500,000 / 1,260,000 ≈ 39.7%. The compression of gross margin, despite lower cost of sales, is primarily due to weaker revenues and the more pronounced impact of fixed or semi-fixed expense levels that do not scale proportionally with revenue (Weygandt et al., 2019; Atkinson et al., 2012).

Fixed vs. Variable Cost Considerations

In a typical retail store, personnel costs (Shop assistants) are largely variable with sales, while rent is fixed. Utilities can be mixed (part fixed, part variable), and management salaries may be semi-fixed or fixed depending on the organization structure. Given the data, the sizable shop personnel costs (258,000) suggest a strong variable component, which would be expected to rise or fall with sales activity. The relatively small rent (23,000) is a fixed cost that would remain unchanged in the short term. Understanding the fixed versus variable composition is essential for short-term decision-making and forecasting accuracy (Drury, 2013; Atkinson et al., 2012).

Discussion of Causes and Implications

The revenue shortfall implies weaker demand or competitive pressures during the forecast period. A 10% shortfall in revenue reduces gross profit and, even with a lower cost of sales (30,000 less than forecast), results in a steep drop in gross profit by 110,000 from forecast to actual. This demonstrates the disproportionate impact of revenue fluctuations on profitability when fixed costs are present and variable costs do not fully offset the decline (Horngren et al., 2013; Garrison et al., 2019).

The modest increase in total expenses (3,500 over forecast) further compresses profitability, turning an expected net income of 87,500 into a negative actual result (-26,000). This outcome emphasizes the importance of robust forecasting, variance analysis, and timely corrective actions in retail budgeting (Bragg, 2013; CFI, 2020).

Recommendations for Management Action

To restore profitability and improve forecasting accuracy, several actions are recommended. First, tighten demand forecasting through enhanced data analysis, incorporating seasonal effects, promotions, and foot traffic indicators. Regular variance analysis should be instituted, with monthly or quarterly reviews to identify early warning signs (Kaplan and Norton, 1996; Horngren et al., 2013).

Second, optimize cost structure by classifying costs into fixed and variable components and adjusting staffing levels in line with sales expectations. If revenue remains weak, consider temporary staffing reductions or shift optimization to control variable labor costs. Simultaneously, review fixed costs such as rent or store operations to identify possible renegotiation opportunities or efficiency improvements (Hilton et al., 2009; Drury, 2013).

Third, explore revenue-enhancing initiatives, including targeted promotions, improved product mix, cross-selling, and tighter inventory management to reduce cost of sales pressure and improve gross margin percentages (Horngren et al., 2013; Kieso et al., 2019).

Finally, implement a rolling forecast process that revises assumptions with actual performance and market indicators, ensuring the organization maintains a dynamic budgeting approach rather than a static plan (Kaplan & Norton, 1996; Atkinson et al., 2012).

Conclusion

The Tp Fashions Houston store data highlight the critical link between revenue performance and profitability. The actual results show a meaningful revenue shortfall and modest expense overruns, resulting in a substantial negative net income. By conducting detailed variance analysis, distinguishing fixed and variable costs, and implementing proactive budgeting practices, the store can improve forecast accuracy, control costs, and identify actionable levers to restore profitability in subsequent periods (Garrison et al., 2019; Drury, 2013).

References

  • Horngren, C.T., Sundem, G.L., Elliott, J.A., Philbrick, D.R. (2013). Introduction to Financial Accounting. Pearson.
  • Weygandt, J.J., Kimmel, P.D., Kieso, D.E. (2019). Financial Accounting. Wiley.
  • Kieso, D.E., Weygandt, J.J., Warfield, J. (2019). Intermediate Accounting. Wiley.
  • Garrison, R.H., Noreen, E.W., Brewer, P.C. (2019). Managerial Accounting. McGraw-Hill Education.
  • Hilton, R.W., Maher, M.W., Selto, F. (2009). Cost Management: Strategies for Business Decisions. McGraw-Hill/Irwin.
  • Drury, C. (2013). Management and Cost Accounting. Cengage.
  • Atkinson, A.A., Kaplan, R.S., Matsumura, E.M., Young, S.M. (2012). Management Accounting: Information for Decision-Making and Strategy. Pearson.
  • Kaplan, R.S., Norton, D.P. (1996). The Balanced Scorecard: Translating Strategy into Action. Harvard Business School Press.
  • Corporate Finance Institute (CFI). (2020). Variance Analysis. Retrieved from https://www.cfi.edu/
  • Investopedia. (n.d.). Gross Margin. Retrieved from https://www.investopedia.com/terms/g/grossmargin.asp

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