Presentation -Krog's Metalfab
-
Upload
parambrahma-panda -
Category
Documents
-
view
650 -
download
222
description
Transcript of Presentation -Krog's Metalfab
Krog’s MetalFab
Group -4
CASE FACTS
Two Plants – One at Chicago and other at MolineFire destroyed Chicago plantProduction affected , expenses incurred due to shifting of
work force Insurance coverage : To compensate for lost profit
CASE FACTS – Accountant Calculation
Sales in 2003 $5,079,094
Predicted Sales (7% Growth) $5,434,630
Actual sales in 2004 $3,845,499
(A) Lost Sales $1,589,131 (B)Profit in 2003 as a apercent of 2003
sales($111,928/5,079,094) $0.0220
Lost profit(A*B) $34,961
Analysis of 2003 Income Statement
200000 300000 400000 500000 600000 7000000
50000100000150000200000250000300000350000400000450000500000
Sales $
CO
GS
$
200000 300000 400000 500000 600000 7000000
5000
10000
15000
20000
25000
30000
Sales $
Sale
s E
xpen
se25
0000
3000
00
3500
00
4000
00
4500
00
5000
00
5500
00
6000
00
6500
000
10000
20000
30000
40000
Sales $
Adm
inis
trat
ive
Exp
ense
Estimating Profit -Account Analysis Method
• COGS and Sales Expense treated as variable cost.• Administrative Expense treated as fixed cost.
CalculationsCOGS/$ Sale $0.89
S. Expense/$ Sale $0.04 Variable Cost $0.93
Fixed Cost / Month $20,250.00 Fixed Cost / Year $243,000.00
Estimated Sales-2004 $5,434,630.58 Estimated Cost $5,297,857.62 Estimated Profit $136,772.96
Actual Profit ($724,210.00)
Lost Profit $860,982
Estimating Profit- High Low Method
Time Period Sales Cost
Highest Sales Aug-03 $602,210 $485,120
Lowest Sales Apr-03 $302,685 $353,584
Variable Cost/ $ Sales $0.44
Fixed Cost /Month $220,660.00
Estimated Profit $400,096.00
Lost Profit $1,124,306.00
Estimating Profit – Regression Method
250000 300000 350000 400000 450000 500000 550000 600000 6500000
100000
200000
300000
400000
500000
600000
f(x) = 0.365054092641811 x + 259418.495698961R² = 0.603574666830169
Scatter Plot of Sales and Cost
Sales
Tot
al C
ost
Estimating Profit Using Least Squares Regression -Without
Removing Outlier Total Cost = 259,418+0.3651xSales
Fixed Component $259,418.00
Variable Component $0.37 2003 Sales $5,079,094.00 Predicted 2004 Sales $5,434,630.58 Estimated Cost $5,097,199.62 Estimated Profit $337,430.96 Actual Profit ($724,210.00)
Lost Profit $1,061,640.96
Estimating Profit- Regression Method -II
Estimating Profit Using Least Squares Regression -After
Removing Outlier
Total Cost = 220338+0.437xSales
Fixed Component $220,338.00
Variable Component
$0.44
2003 Sales $5,079,094.00 Predicted 2004
Sales$5,434,630.58
Estimated Cost $5,018,989.56
Estimated Profit $415,641.02
Actual Profit ($724,210.00)
Loss Profit $1,139,851.02
250000 300000 350000 400000 450000 500000 550000 600000 6500000
100000
200000
300000
400000
500000
600000
f(x) = 0.436967215532063 x + 220338.421806872R² = 0.991499909317905
Scatter Plot of Sales and Cost (Removing Outlier)
Sales
Tot
al C
ost
Recommendation
• Accountant’s analysis incorrect because of large proportion of fixed cost
• Use regression method to estimate costs as it is more accurate.
• Data check is necessary before applying regression