RITESH ASHISH

DEEPAKSUDHIR

Profile We have been in business for the past 50

years manufacturing plastic furniture.

Vision Every house should have a product of our

company.

MissionCreating value through convenience.

Swot Analysis

STRENGTH• Huge Capital• Large No. of dealers

spread all over the country.

OPPORTUNITIES• India’s one of the

fastest growing market.

WEAKNESS• Problems in future

predictions.

THREATS• Perception that it’s

not environmental friendly.

Segmenting &Targeting The Market

Segmented markets-

1. Households- Low & Middle level

2. Commercial industries

Year Sales (Lower Level) in Lakhs

Sales (Middle level) in Lakhs

Sales (Consumer Industries) in Lakhs

1999 5 5 12

2000 7 10 20

2001 9 15 28

2002 12 20 33

2003 16 26 39

2004 20 35 44

2005 24 39 48

2006 27 45 52

2007 30 51 54

2008 35 55 60

Sales Of Targeted Market

Forecasting Demand For The Targeted Markets

• Delhi

• Bangalore

• Chennai

Potential Market Attractiveness Of The Area

City India Brand Sales

India Category

Sales

BDI

Delhi 0.041 0.033 124

Bangalore 0.026 0.025 104

Chennai 0.031 0.037 83

Regional Characteristics of the targeted market

City Households (000)

Avg. household income (lakhs p.a)

Avg. household expenditur-e (lakhs p.a)

10+Lakhs p.a (000)s

1+ Crore p.a households

exp / inc index

Chennai 1,485 174 116 25 433 0.67

Source-Brand equity,08 march 06. Attributed to great Indian middle class

City(All figs in Rs Cr)

Food Products

FMCG Dura-bles

Misc. goods/servic-es

Total Market

Chennai 7,902 823 470 10,102 19,297

Source: Brand Equity, 08 March 06. Attributed to Indicus Analytics.

Expenses On Various Sectors

Potential Market Size of The Targeted Area

City Potential Market Size

Chennai 10,88,23,300

Note. In Indian Rs.

ESTIMATED POTENTIAL MARKET SIZE

TOTAL MARKET POTENTIAL = No. Of Potential Buyers * Avg. Quantity Purchased * Avg. Price

Chennai - 4,35,293*1*250= 10,88,23,300

Mumbai - 12,88,365*1*250= 32,20,91,125IN CRORES

Total Market Potential by Chain Ratio Method

City Total Market Potential

Chennai 10,88,25,000

Note. In Indian Rs.

Forecasting Methods

• Time Series : Simple trend

• Time Series : Moving & Weighted Avg.

• Regression

Current Trend (Lower Level Income In Chennai)

0

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30

35

40

S

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L

E

S

In Lakhs (Rs.)

No. Of Years

Y= a + bXa -11541.6b 5.776

Year CALCULATION OF REGRESSION VALUE IN LAKHS(RS.)1999 4.52000 10.32001 16.12002 21.92003 27.62004 33.42005 39.22006 452007 50.82008 56.3

Y= a + bXa -11867.8b 5.94

Year CALCULATION OF REGRESSION VALUE IN LAKHS(RS.)1999 14.22000 20.22001 26.12002 32.12003 38.12004 442005 49.92006 53.82007 53.82008 59.8

Y= -11867.77+5.94(2005)Y= -11867.77+5.94(2006)Y= -11867.77+5.94(2007)Y= -11867.77+5.94(2008)

Y= -11867.77+5.94(1999)Y= -11867.77+5.94(2000)Y= -11867.77+5.94(2001)Y= -11867.77+5.94(2002)Y= -11867.77+5.94(2003)Y= -11867.77+5.94(2004)

CALCULATION OF REGRESSION LINE AND RESIDUALS (COMMERCIAL INDUSTRIES)

CALCULATION OF REGRESSION LINE AND RESIDUALS (MIDDLE LEVEL)

Y= -11541.63+5.776(1999)Y= -11541.63+5.776(2000)Y= -11541.63+5.776(2001)Y= -11541.63+5.776(2002)Y= -11541.63+5.776(2003)Y= -11541.63+5.776(2004)Y= -11541.63+5.776(2005)Y= -11541.63+5.776(2006)Y= -11541.63+5.776(2007)Y= -11541.63+5.776(2008)

Forecasting Demand for Lower level in Chennai (09)

Forecasted Demand(09)

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25

30

35

40

9920

0020

0120

0220

0320

0420

0520

0620

0720

0820

09

Line 1

Line 2

Y= a+bx (Sales= -6793.4 + 3.4*x(2009)

(Sales= 37.2 in lakhs for 2009)

No. of Years

S

A

L

E

S

In Lakhs (Rs.)

Regression Line

Year Original Sales Regression Point

Residual

1999 5 3.2 1.8

2000 7 6.6 .4

2001 9 10 -1

2002 12 13.4 -1.4

2003 16 16.8 -.8

2004 20 20.2 -.2

2005 24 23.6 .4

2006 27 27 0

2007 30 30.4 -.4

2008 35 33.8 1.2

RESIDUALS

Plotting of residuals

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1 2 3 4 5 6 7 8 9 10Series1

..\..\..\Desktop\low level simple trend• Open stat result

Current Trend for Medium level in Chennai

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10

20

30

40

50

60

1999

2001

2003

2005

2007

East

No. Of Years

S

A

L

E

S

In lakhs (Rs.)

Forecasted Demand For Medium Level Household in Chennai

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10

20

30

40

50

60

70

Line 1

Line 2

S

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S

In Lakhs (Rs.)

No. Of Years

62.35 Forecasted Demand

Y= a+bx (Sales= -11541.63 + 5.776*x(2009)

(Sales= 62.35 in lakhs for 2009)

Year Original Sales Regression Value

Residual

1999 5 4.5 .5

2000 10 10.3 -.3

2001 15 16.1 -1.1

2002 20 21.9 -1.9

2003 26 27.6 -1.6

2004 35 33.4 1.6

2005 39 39.2 -.2

2006 45 45 0

2007 51 50.8 .2

2008 55 56.5 -1.5

Residual

Plotting of residuals

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..\..\..\Desktop\medium level simple trend• Open stat result

Current Trend in Commercial Industries in Chennai

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10

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30

40

50

60

70

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

Line 1

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S

In Lakhs (Rs.)

No. Of Years

Forecasted Demand For Commercial Industries in Chennai

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10

20

30

40

50

60

70

80

1999

2001

2003

2005

2007

2009

East

Line 2

Line 2

Y= a+bx (Sales= -11867.7 + 5.94*x(2009)

(Sales=73 .72 in lakhs for 2009)

No. Of Years

S

A

L

E

S

In Lakhs (Rs.) 73.72 lakhsForecasted Demand

Residual

Year Original Sales Regression Value

Residual

1999 12 14.2 -2.2

2000 20 20.2 -.2

2001 28 26.1 1.9

2002 33 32.1 .9

2003 39 38 1

2004 44 44 0

2005 48 49.9 -1.9

2006 52 55.8 -3.8

2007 54 61.8 -7.8

2008 60 67.7 -7.7

Plotting of residuals

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Series1

..\..\..\Desktop\commercial industries simple trend analysis• Open stat result

Moving Avg. Methods

Formula

Forecasted year = Sum of 3 Previous years

3

1Y=Y1+Y2+Y3/3IN LAKHS(RS.)5+7+9/3 77+9+12/3 9.39+12+16/3 12.312+16+20/3 1616+20+24/3 2020+24+27/3 23.624+27+30/3 2727+30+35/3 30.6

30.6

Y=Y1+Y2+Y3/3IN LAKHS(RS.)5+10+15/3 1010+15+20/3 1515+20+26/3 20.320+26+35/3 2726+35+39/3 33.335+39+45/3 39.639+45+51/3 4545+51+55/3 50.3

50.3

Y=Y1+Y2+Y3/3IN LAKHS(RS.)12+20+28/3 2020+28+33/3 2728+33+39/3 33.333+39+44/3 38.639+44+48/3 43.644+48+52/3 4848+52+54/3 51.352+54+60/3 55.3

55.3

2005,2006&20072006,2007&2008Demand for 2009

1999,2000&20012000,2001&20022001,2002&20032002,2003&20042003,2004&20052004,2005&2006

TIME PERIOD

TIME PERIOD1999,2000&20012000,2001&20022001,2002&20032002,2003&20042003,2004&20052004,2005&20062005,2006&20072006,2007&2008Demand for 2009

MOVING AVERAGES METHOD (FOR COMMERCIAL INDUSTRIES)

MOVING AVERAGES METHOD (FOR MIDDLE INCOME LEVEL)

MOVING AVERAGES METHOD (FOR LOWER INCOME LEVEL)TIME PERIOD

1999,2000&20012000,2001&20022001,2002&20032002,2003&20042003,2004&20052004,2005&20062005,2006&20072006,2007&2008Demand for 2009

Demand Forecast for lower level income household

• Forecasting Demand = D(06+07+08)

for 2009 3

• D of 09 = (27+30+35) = 30.6 (lakhs)

3

• D of 09 = 30.6 lakhs

Note: All Amounts in Rs.

Graphical Representation

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25

30

35

3 4 5 6 7 8 9 10

Line 1

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15

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25

30

35

3 4 5 6 7 8 9 10 11

Line 1

Sales Graph of previous 8 Periods

Note : 1 Period = Avg. Demand Of 3 years

Sales Graph of 9 Periods including the forecasted year

S

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No. Of yearsNo. Of years

In lakhsIn lakhs

Household of Medium Level Income

• Forecasting Demand = D(06+07+08)

for 2009 3

• D of 09 = (45+51+55) = Rs. 50.3(lakhs)

3

• D of 09 = 50.3 lakhs

Note : 1 Period = Avg. Demand Of 3 years

Graphical Representation

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20

30

40

50

60

3 4 5 6 7 8 9 10

Line 1

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50

60

3 4 5 6 7 8 9 10 11

Line 1

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No. Of years No. Of years

In lakhs In lakhs

Note : In Indian Rs.

Sales Graph of previous 8 Periods Sales Graph of 9 Periods including

the forecasted year

Commercial Industries

• Forecasting Demand = D(06+07+08)

for 2009 3

• D of 09 = (52+54+60) = Rs.55.3 (lakhs)

3

• D of 09 = 55.3 lakhs

Note: All Amounts in Rs.

Graphical representation

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60

3 4 5 6 7 8 9 10

Line 1

Line 2

Line 3

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In lakhs

No. Of years

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10

20

30

40

50

60

3 4 5 6 7 8 9 10 11

Line 1

Line 2

Line 3

No. Of years

S

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In lakhs

Sales Graph of previous 8 Periods Sales Graph of 9 Periods including the forecasted year

Note : In Indian Rs.

Forecasting through Weighted Avg. Method

• In this we assign different degrees of importance to the values.

• Highest weight is given to the most recent data.

• Formula –

f(y)= (y1+2y2+ 3y3)

6

Household (lower level Income)

• F (09) = 06+2(07)+3(08)

6

• F (09) = 27+2(30)+3(35) = Rs.32 lakhs

6

Graphical Representation

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25

30

35

3 4 5 6 7 8 9 10

Line 1

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25

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35

3 4 5 6 7 8 9 10 11

Line 1

S

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L

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No. Of years No. Of years

In lakhs In lakhs

Sales Graph of previous 8 Periods Sales Graph of 9 Periods including the forecasted year

Note : In Indian Rs.

Household (Middle level Income)

• F (09) = 06+2(07)+3(08)

6

• F (09) = 45+2(51)+3(55) = Rs.52 lakhs

6

Graphical Representation

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30

40

50

60

3 4 5 6 7 8 9 10

Line 1

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60

3 4 5 6 7 8 9 10 11

Line 1

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No. Of years No. Of years

Sales Graph of previous 8 Periods Sales Graph of 9 Periods including the forecasted year

In lakhs In lakhs

Commercial Industries

• F (09) = 06+2(07)+3(08)

6

• F (09) = 52+2(54)+3(60) = Rs.56.6 lakhs

6

Y=Y1+2Y2+3Y3/6IN LAKHS(RS.)5+2*7+3*9/6 7.67+2*9+3*12/6 10.19+2*12+3*16/6 13.512+2*16+3*20/617.316+2*20+3*24/621.320+2*24+3*27/624.824+2*27+3*30/6 2827+2*30+3*35/6 32

32

Y=Y1+2Y2+3Y3/6IN LAKHS(RS.)5+2*10+3*15/6 11.610+2*15+3*20/616.615+2*20+3*26/622.1620+2*26+3*35/629.526+2*35+3*39/635.535+2*39+3*45/641.339+2*45+3*51/6 4745+2*51+3*55/6 52

52

Y=Y1+2Y2+3Y3/6IN LAKHS(RS.)12+2*20+3*28/622.620+2*28+3*33/629.128+2*33+3*39/635.133+2*39+3*44/640.539+2*44+3*48/645.144+2*48+3*52/649.348+2*52+3*54/652.352+2*54+3*60/656.6

56.6

2005,2006&20072006,2007&2008Demand for 2009

1999,2000&20012000,2001&20022001,2002&20032002,2003&20042003,2004&20052004,2005&2006

TIME PERIOD

TIME PERIOD1999,2000&20012000,2001&20022001,2002&20032002,2003&20042003,2004&20052004,2005&20062005,2006&20072006,2007&2008Demand for 2009

WEIGHTED MOVING AVERAGE METHOD (FOR COMMERCIAL INDUSTRIES LEVEL)

WEIGHTED MOVING AVERAGE METHOD (FOR MIDDLE INCOME LEVEL)

WEIGHTED MOVING AVERAGE METHOD (FOR LOWER INCOME LEVEL)TIME PERIOD

1999,2000&20012000,2001&20022001,2002&20032002,2003&20042003,2004&20052004,2005&20062005,2006&20072006,2007&2008Demand for 2009

Graphical Representation

0

10

20

30

40

50

60

3 4 5 6 7 8 9 10

Line 1

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10

20

30

40

50

60

70

3 4 5 6 7 8 9 10 11

Line 1

Line 2

Line 3

Sales Graph of previous 8 Periods Sales Graph of 9 Periods including the forecasted year

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No. Of yearsNo. Of years

In lakhs In lakhs

Sales (Rs.) Income

(000’s)

Price (Rs.) Inflation Rate Durability

(months)

5 30 100 .04 12

7 40 100 .04 12

9 50 120 .06 14

12 61 140 .05 14

16 70 170 .05 16

20 77 180 .08 16

24 88 200 .06 18

27 97 210 .07 20

30 102 220 .08 24

35 110 250 .12 24

F(09)= (-7.731)+(.080*120)+ (.107*250)+(-7-731*.12)+(.594*24)

Y= a+b1X1+b2x2..+bnXn

f(09)= Rs. 41.9 lakhs

Forecasting by Regression (lower level Income)

..\..\..\Desktop\lower level multiple regression• Open stat result

Forecasting by Regression (Middle level Income)

Sales (Rs. In LAKHS)

Income

(In LAKH’s)

Price (Rs.) Inflation Rate Durability

(months)

5 1 100 .04 12

10 1.2 100 .04 12

15 1.35 120 .06 14

20 1.55 140 .05 14

26 1.75 170 .05 16

35 1.90 180 .08 16

39 2 200 .06 18

45 2.4 210 .07 20

51 2.6 220 .08 24

55 2.8 250 .12 24

Y= a+b1X1+b2x2..+bnXn

F(09)= (-23.964)+(18.823*3)+ (.142*250)+(-15.365*.12)+(-.228`*24)

f(09)= Rs. 60.7 lakhs

..\..\..\Desktop\middle level multiple regression• Open stat result

Forecasting by Regression (Consumer industries )

Sales (Rs. In LAKHS)

Industry Growth

(In LAKH’s)

Price (Rs.) Inflation Rate Durability

(months)

12 .03 100 .04 12

20 .05 100 .04 12

28 .08 120 .06 14

33 .05 140 .05 14

39 .06 170 .05 16

44 .10 180 .08 16

48 .11 200 .06 18

52 .16 210 .07 20

54 .18 220 .08 24

60 .20 250 .12 24

Y= a+b1X1+b2x2..+bnXn

F(09)= (-.717)+(76.111*.24)+ (.334*250)+(-55.750*.12)+(-1.225*24)

f(09)= Rs. 64.95 lakhs

..\..\..\Desktop\commercial l multiple regression• Open stat result

Summary of forecasts

Targeted areas

Simple trend analysis

Moving average

Weighted average

Multiple regression

Lower level

37.2 30.6 32 41.9

Middle level

64.35 50.3 52 60.7

Con .indus.

73.72 55.3 56.6 64.95

Conclusion

• We would like to go with weighted average method as this gives maximum weight age to the recent trend and also its results are similar to the moving average method we can say that the forecasting can be some what accurate .

• For others method we are not taking in consideration because in simple trend only one variable defines the sales and we know that there are many other variables which define sales .. And for multiple regression the variables which we have taken consideration does not reflect the strong relation between the dependent and independent variables ..