st. vincent de paul- sales and opportunity analysis ali ruzo lauren schick sam kenney spencer...
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St. Vincent de Paul- Sales and Opportunity Analysis
Ali RuzoLauren SchickSam Kenney
Spencer Kilpatrick
St. Vincent de Paul• World Wide Catholic Non-profit organization
– Started in the United States in 1845– about 950,000 involved in the society within 132 countries worldwide– Provides direct assistance to anyone suffering or in need for clothing, food, medical
aid, employment and shelter
• All proceeds from the SVdP Thrift Store go to supporting programs such as:– Adult education
• GED, ESL, Parenting workshops, Financial empowerment workshops, Citizenship preparation classes
– Youth Enrichment Programs• Afterschool tutoring, lunch programs, nutrition programs
– Relief Programs• BACK-2-SCHOOL, Christmas shop, Holiday meals
Our Project
• Opportunity of Donations
• Hourly Sales Analysis
• Forecasting Regression Model
Opportunity of Donations
• Survey– 5 questions to gauge willingness to donate and
knowledge of SVdP– Surveyed 4 Catholic schools – Approximately 100 adults
• All outside of 5 mile radius of store to get other input
Have you ever heard about St. Vincent de Paul Thrift store?
79%
21%All
85%
15% Women 190K+
140K-189,999 90K-139,999 40K-89,999 Under 40K
Have you ever donated to St. Vincent de Paul Thrift store?
54%46%
All
60%
40%
Women 190K+
140K-189,999 90K-139,999 40K-89,999 Under 40K
How Willing are you to donate a high end clothing item?
28%
14%20%13%
25% All19%
19%23%15%
23%Women 22%
13%26%17%
22% 190K+
13%
87%
140K-189,999 17%
25%
8%
50%
90K-139,99923%
15%23%15%
23%40K-89,999 14%
14%
29%
43%
Under 40K
Donation Opportunities Conclusions
• Target higher income areas
• Continue to explore donation options outside of 5 mile radius– Place more donation pick up trucks – SMU has agreed to further conversation for next
year
Hourly Sales Analysis
• Analyzed the mean sales data hourly
• Descriptive statistics by:– Hours by day– Days by hour
• Looked for most and least profitable times using a color progression scale
Total Mean Sales
*Most profitable mid-day Tuesday and Saturday*Least profitable Mondays
Mean Sales- Hourly
*Most profitable usually Saturday *Least profitable usually Mondays
Mean Sales- Daily
*Most profitable usually during the middle of the day
Hourly Sales Analysis Conclusions
• Monday is regularly the least profitable– Consider shorter hours of operation– Consider heavier advertisement and promotions
• Saturday and Tuesday are usually the most profitable– Consider scheduling staff appropriately– Continue using coupons and promotions
Regression Model
• Evaluated trend lines of the data
1 58 115 172 229 286 343 400 457 514 571 628 685 742 799 856 913 970 10271084114111981255 $-
$2,000.00
$4,000.00
$6,000.00
$8,000.00
$10,000.00
$12,000.00
f(x) = 1.21157976526779 x + 2004.03302962612R² = 0.149947977293395
Total Sales
Number of Days
Daily Sales- Actual
1/1/2
008
1/24/2
008
2/16/2
008
3/10/2
008
4/2/2
008
4/25/2
008
5/18/2
008
6/10/2
008
7/3/2
008
7/26/2
008
8/18/2
008
9/10/2
008
10/3/2
008
10/26/2
008
11/18/2
008
12/11/2
008 $-
$2,000.00
$4,000.00
$6,000.00
$8,000.00
$10,000.00
$12,000.00
2008 Daily Sales
1/1/2
009
1/22/2
009
2/12/2
009
3/5/2
009
3/26/2
009
4/16/2
009
5/7/2
009
5/28/2
009
6/18/2
009
7/9/2
009
7/30/2
009
8/20/2
009
9/10/2
009
10/1/2
009
10/22/2
009
11/12/2
009
12/3/2
009
12/24/2
009 $-
$1,000.00 $2,000.00 $3,000.00 $4,000.00 $5,000.00 $6,000.00 $7,000.00 $8,000.00
2009 Daily Sales
1/1/2
010
1/21/2
010
2/10/2
010
3/2/2
010
3/22/2
010
4/11/2
010
5/1/2
010
5/21/2
010
6/10/2
010
6/30/2
010
7/20/2
010
8/9/2
010
8/29/2
010
9/18/2
010
10/8/2
010
10/28/2
010
11/17/2
010
12/7/2
010
12/27/2
010 $-
$1,000.00 $2,000.00 $3,000.00 $4,000.00 $5,000.00 $6,000.00 $7,000.00 $8,000.00 $9,000.00
$10,000.00
2010 Daily Sales
Monthly Trends
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 $-
$20,000.00
$40,000.00
$60,000.00
$80,000.00
$100,000.00
$120,000.00
$140,000.00
f(x) = 1099.12259120006 x + 60866.2712891986R² = 0.601571412860553
All Monthly Sales
Monthly Sales by Year
Jan-08
Feb-08
Mar-08
Apr-08
May-08
Jun-08Jul-0
8
Aug-08
Sep-08
Oct-08
Nov-08
Dec-08
$- $10,000.00 $20,000.00 $30,000.00 $40,000.00 $50,000.00 $60,000.00 $70,000.00 $80,000.00 $90,000.00
$100,000.00
2008 Monthly Sales
Jan-09
Feb-09
Mar-09
Apr-09
May-09
Jun-09Jul-0
9
Aug-09
Sep-09
Oct-09
Nov-09
Dec-09
$-
$20,000.00
$40,000.00
$60,000.00
$80,000.00
$100,000.00
$120,000.00
2009 Monthly Sales
Jan-10
Feb-10
Mar-10
Apr-10
May-10
Jun-10Jul-1
0
Aug-10
Sep-10
Oct-10
Nov-10
Dec-10
$-
$20,000.00
$40,000.00
$60,000.00
$80,000.00
$100,000.00
$120,000.00
$140,000.00
2010 Monthly Sales
Day of the Week Trends
10/1/2
007
12/2/2
007
2/2/2
008
4/4/2
008
6/5/2
008
8/6/2
008
10/7/2
008
12/8/2
008
2/8/2
009
4/11/2
009
6/12/2
009
8/13/2
009
10/14/2
009
12/15/2
009
2/15/2
010
4/18/2
010
6/19/2
010
8/20/2
010
10/21/2
010
12/22/2
010
2/22/2
0110.00
2,000.00
4,000.00
6,000.00
8,000.00
Monday
10/2/2
007
12/3/2
007
2/3/2
008
4/5/2
008
6/6/2
008
8/7/2
008
10/8/2
008
12/9/2
008
2/9/2
009
4/12/2
009
6/13/2
009
8/14/2
009
10/15/2
009
12/16/2
009
2/16/2
010
4/19/2
010
6/20/2
010
8/21/2
010
10/22/2
010
12/23/2
010
2/23/2
0110.00
2,000.004,000.006,000.008,000.00
10,000.00
Tuesday
10/3/2
007
12/8/2
007
2/12/2
008
4/18/2
008
6/23/2
008
8/28/2
008
11/2/2
008
1/7/2
009
3/14/2
009
5/19/2
009
7/24/2
009
9/28/2
009
12/3/2
009
2/7/2
010
4/14/2
010
6/19/2
010
8/24/2
010
10/29/2
010
1/3/2
011
3/10/2
0110.00
2,000.00
4,000.00
6,000.00
Wednesday
10/4/2
007
12/9/2
007
2/13/2
008
4/19/2
008
6/24/2
008
8/29/2
008
11/3/2
008
1/8/2
009
3/15/2
009
5/20/2
009
7/25/2
009
9/29/2
009
12/4/2
009
2/8/2
010
4/15/2
010
6/20/2
010
8/25/2
010
10/30/2
010
1/4/2
011
3/11/2
0110.00
2,000.00
4,000.00
6,000.00
Thursday
Day of the Week Trends Cont.
10/5/2
007
11/28/2
007
1/21/2
008
3/15/2
008
5/8/2
008
7/1/2
008
8/24/2
008
10/17/2
008
12/10/2
008
2/2/2
009
3/28/2
009
5/21/2
009
7/14/2
009
9/6/2
009
10/30/2
009
12/23/2
009
2/15/2
010
4/10/2
010
6/3/2
010
7/27/2
010
9/19/2
010
11/12/2
010
1/5/2
011
2/28/2
0110.00
2,000.004,000.006,000.008,000.00
10,000.00
Friday
10/6/2
007
12/3/2
007
1/30/2
008
3/28/2
008
5/25/2
008
7/22/2
008
9/18/2
008
11/15/2
008
1/12/2
009
3/11/2
009
5/8/2
009
7/5/2
009
9/1/2
009
10/29/2
009
12/26/2
009
2/22/2
010
4/21/2
010
6/18/2
010
8/15/2
010
10/12/2
010
12/9/2
010
2/5/2
0110
2000400060008000
1000012000
Saturday
10/7/2
007
12/12/2
007
2/16/2
008
4/22/2
008
6/27/2
008
9/1/2
008
11/6/2
008
1/11/2
009
3/18/2
009
5/23/2
009
7/28/2
009
10/2/2
009
12/7/2
009
2/11/2
010
4/18/2
010
6/23/2
010
8/28/2
010
11/2/2
010
1/7/2
011
3/14/2
0110.00
1,000.002,000.003,000.004,000.005,000.006,000.007,000.00
Sunday
Create Monthly Factors
*Used factors to weight the Regression Model appropriately for each month
y = 1099.1x + 60866R² = 0.6016
Create Daily Factors
y = 1.2116x + 2004R² = 0.1499
*multiplied Y value by both monthly factor and daily factor
Regression-Monthly
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 420
20000
40000
60000
80000
100000
120000
140000
Monthly
Regression-Monthly by Year
1 2 3 4 5 6 7 8 9 10 11 12 $-
$20,000.00
$40,000.00
$60,000.00
$80,000.00
$100,000.00
$120,000.00
$140,000.00
Monthly Forecasts by Year (08-10)
Regression-Daily by Year
1 13 25 37 49 61 73 85 97 109 121 133 145 157 169 181 193 205 217 229 241 253 265 277 289 301 313 325 337 349 361 $-
$1,000.00
$2,000.00
$3,000.00
$4,000.00
$5,000.00
$6,000.00
$7,000.00
$8,000.00
Daily Forecasts by Year (08-10)
Black Friday Factor = 2.18
*Christmas and Thanksgiving are set to zero
Regression Model Daily
10/1/2
007
11/10/2
007
12/20/2
007
1/29/2
008
3/9/2
008
4/18/2
008
5/28/2
008
7/7/2
008
8/16/2
008
9/25/2
008
11/4/2
008
12/14/2
008
1/23/2
009
3/4/2
009
4/13/2
009
5/23/2
009
7/2/2
009
8/11/2
009
9/20/2
009
10/30/2
009
12/9/2
009
1/18/2
010
2/27/2
010
4/8/2
010
5/18/2
010
6/27/2
010
8/6/2
010
9/15/2
010
10/25/2
010
12/4/2
010
1/13/2
011
2/22/2
011 $-
$2,000.00
$4,000.00
$6,000.00
$8,000.00
$10,000.00
$12,000.00
Daily Vs Forecast
Yi (sales)Yc
R2 = 0.52
*the model now explains 52% of the daily sales (rather than only 15% from the original trend line)
Regression Model Monthly
Oct-07
Dec-07
Feb-08
Apr-08
Jun-08
Aug-08
Oct-08
Dec-08
Feb-09
Apr-09
Jun-09
Aug-09
Oct-09
Dec-09
Feb-10
Apr-10
Jun-10
Aug-10
Oct-10
Dec-10
Feb-11
$-
$20,000.00
$40,000.00
$60,000.00
$80,000.00
$100,000.00
$120,000.00
$140,000.00
Monthly Sales vs Forecast
Yi (sales) Yc
R2 = 0.78
*the monthly forecasting model now explains 78% of the sales
Usable Forecasting ModelStatement Output InputIF Checks whether the
condition is met, and returns one value if TRUE and another if FALSE
IF(logical_test, [value_if_true], [value_if_false])
WEEKDAY Returns a number from 1 to 7 identifying the day of the week of the date
WEEKDAY(serial_number, [return_type])
MONTH Returns the month, a number from 1 (January) to 12 (December)
MONTH(serial_number)
DATEDIF returns the difference between two date values, based on the interval specified.
DateDif( start_date, end_date, interval )
DAY Returns the number that represents the date in Microsoft Excel date-time code
DATE(serial_number)
Embedded If-StatementsAn example line from the embedded If-Statement:
=IF(AND(WEEKDAY(L6)=1,MONTH(L6)=1),($J$2*DATEDIF($B$20,L6,"d")+$K$2)*$B$10*$D$4,
IF(AND(WEEKDAY(L6)=2,MONTH(L6)=1),($J$2*DATEDIF($B$20,L6,"d")+$K$2)*$B$4*$D$4,IF(AND(WEEKDAY(L6)=3,MONTH(L6)=1),($J$2*DATEDIF($B$20,L6,"d")+$K$2)*$B$5*$D$4,IF(AND(WEEKDAY(L6)=4,MONTH(L6)=1),($J$2*DATEDIF($B$20,L6,"d")+$K$2)*$B$6*$D$4,IF(AND(WEEKDAY(L6)=5,MONTH(L6)=1),($J$2*DATEDIF($B$20,L6,"d")+$K$2)*$B$7*$D$4,IF(AND(WEEKDAY(L6)=6,MONTH(L6)=1),($J$2*DATEDIF($B$20,L6,"d")+$K$2)*$B$8*$D$4,IF(AND(WEEKDAY(L6)=7,MONTH(L6)=1),($J$2*DATEDIF($B$20,L6,"d")+$K$2)*$B$9*$D$4,…….
Forecasting for 2011
Questions?