St. Vincent de Paul- Sales and Opportunity Analysis Ali Ruzo Lauren Schick Sam Kenney Spencer...

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?