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Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
Marketing Management
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Marketing Management

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this is a presentation on demand forecasting taking nilkamal as an example .. …

this is a presentation on demand forecasting taking nilkamal as an example ..
note . data is hypothetical

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  • 1. RITESH ASHISH DEEPAK SUDHIR
  • 2. <ul><li>Profile </li></ul><ul><li>We have been in business for the past 50 years manufacturing plastic furniture . </li></ul><ul><li>Vision </li></ul><ul><li>Every house should have a product of our company . </li></ul><ul><li>Mission </li></ul><ul><li>Creating value through convenience. </li></ul>
  • 3. Swot Analysis <ul><li>STRENGTH </li></ul><ul><li>Huge Capital </li></ul><ul><li>Large No. of dealers spread all over the country. </li></ul><ul><li>OPPORTUNITIES </li></ul><ul><li>India’s one of the fastest growing market. </li></ul><ul><li>WEAKNESS </li></ul><ul><li>Problems in future predictions. </li></ul><ul><li>THREATS </li></ul><ul><li>Perception that it’s not environmental friendly. </li></ul>
  • 4. Segmenting &Targeting The Market <ul><li>Segmented markets- </li></ul><ul><li>Households- Low & Middle level </li></ul><ul><li>Commercial industries </li></ul>
  • 5. Sales Of Targeted Market 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
  • 6. Forecasting Demand For The Targeted Markets <ul><li>Delhi </li></ul><ul><li>Bangalore </li></ul><ul><li>Chennai </li></ul>
  • 7. 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
  • 8. Regional Characteristics of the targeted market Source-Brand equity,08 march 06. Attributed to great Indian middle class 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
  • 9. Source: Brand Equity, 08 March 06. Attributed to Indicus Analytics. Expenses On Various Sectors 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
  • 10. Potential Market Size of The Targeted Area Note. In Indian Rs. City Potential Market Size Chennai 10,88,23,300
  • 11. IN CRORES
  • 12. Total Market Potential by Chain Ratio Method Note. In Indian Rs. City Total Market Potential Chennai 10,88,25,000
  • 13. Forecasting Methods <ul><li>Time Series : Simple trend </li></ul><ul><li>Time Series : Moving & Weighted Avg. </li></ul><ul><li>Regression </li></ul>
  • 14. Current Trend (Lower Level Income In Chennai) S A L E S In Lakhs (Rs.) No. Of Years
  • 15.  
  • 16. Forecasting Demand for Lower level in Chennai (09) Forecasted Demand (09) 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
  • 17. RESIDUALS 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
  • 18. Plotting of residuals
  • 19. ......Desktoplow level simple trend <ul><li>Open stat result </li></ul>
  • 20. Current Trend for Medium level in Chennai No. Of Years S A L E S In lakhs (Rs.)
  • 21. Forecasted Demand For Medium Level Household in Chennai S A L E 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)
  • 22. Residual 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
  • 23. Plotting of residuals
  • 24. ......Desktopmedium level simple trend <ul><li>Open stat result </li></ul>
  • 25. Current Trend in Commercial Industries in Chennai S A L E S In Lakhs (Rs.) No. Of Years
  • 26. Forecasted Demand For Commercial Industries in Chennai 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 lakhs Forecasted Demand
  • 27. 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
  • 28. Plotting of residuals
  • 29. ......Desktopcommercial industries simple trend analysis <ul><li>Open stat result </li></ul>
  • 30. Moving Avg. Methods <ul><li>Formula </li></ul><ul><li>Forecasted year = Sum of 3 Previous years </li></ul><ul><ul><ul><ul><ul><li>3 </li></ul></ul></ul></ul></ul>
  • 31. 1
  • 32. Demand Forecast for lower level income household <ul><li>Forecasting Demand = D(06+07+08) </li></ul><ul><li>for 2009 3 </li></ul><ul><li>D of 09 = (27+30+35) = 30.6 (lakhs) </li></ul><ul><li>3 </li></ul><ul><li>D of 09 = 30.6 lakhs </li></ul>Note: All Amounts in Rs.
  • 33. Graphical Representation Sales Graph of previous 8 Periods Note : 1 Period = Avg. Demand Of 3 years Sales Graph of 9 Periods including the forecasted year S A L E S S A L E S No. Of years No. Of years In lakhs In lakhs
  • 34. Household of Medium Level Income <ul><li>Forecasting Demand = D(06+07+08) </li></ul><ul><li>for 2009 3 </li></ul><ul><li>D of 09 = (45+51+55) = Rs. 50.3(lakhs) </li></ul><ul><li>3 </li></ul><ul><li>D of 09 = 50.3 lakhs </li></ul>Note : 1 Period = Avg. Demand Of 3 years
  • 35. Graphical Representation S A L E S S A L E S 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
  • 36. Commercial Industries <ul><li>Forecasting Demand = D(06+07+08) </li></ul><ul><li>for 2009 3 </li></ul><ul><li>D of 09 = (52+54+60) = Rs.55.3 (lakhs) </li></ul><ul><li>3 </li></ul><ul><li>D of 09 = 55.3 lakhs </li></ul>Note: All Amounts in Rs.
  • 37. Graphical representation S A L E S In lakhs No. Of years No. Of years S A L E S In lakhs Sales Graph of previous 8 Periods Sales Graph of 9 Periods including the forecasted year Note : In Indian Rs.
  • 38. Forecasting through Weighted Avg. Method <ul><li>In this we assign different degrees of importance to the values. </li></ul><ul><li>Highest weight is given to the most recent data. </li></ul><ul><li>Formula – </li></ul><ul><li>f(y)= (y 1 +2y 2 + 3y 3 ) </li></ul><ul><li>6 </li></ul>
  • 39. Household (lower level Income) <ul><li>F (09) = 06+2(07)+3(08) </li></ul><ul><li>6 </li></ul><ul><li>F (09) = 27+2(30)+3(35) = Rs.32 lakhs </li></ul><ul><li>6 </li></ul>
  • 40. Graphical Representation S A L E S S A L E S 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.
  • 41. Household (Middle level Income) <ul><li>F (09) = 06+2(07)+3(08) </li></ul><ul><li>6 </li></ul><ul><li>F (09) = 45+2(51)+3(55) = Rs.52 lakhs </li></ul><ul><li>6 </li></ul>
  • 42. Graphical Representation S A L E S S A L E S 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
  • 43. Commercial Industries <ul><li>F (09) = 06+2(07)+3(08) </li></ul><ul><li>6 </li></ul><ul><li>F (09) = 52+2(54)+3(60) = Rs.56.6 lakhs </li></ul><ul><li>6 </li></ul>
  • 44.  
  • 45. Graphical Representation Sales Graph of previous 8 Periods Sales Graph of 9 Periods including the forecasted year S A L E S S A L E S No. Of years No. Of years In lakhs In lakhs
  • 46. F(09)= (-7.731)+(.080*120)+ (.107*250)+(-7-731*.12)+(.594*24) Y= a+b 1 X 1 +b 2 x 2 ..+bnXn f(09)= Rs. 41.9 lakhs Forecasting by Regression (lower level Income) 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
  • 47. ......Desktoplower level multiple regression <ul><li>Open stat result </li></ul>
  • 48. Forecasting by Regression (Middle level Income) Y= a+b 1 X 1 +b 2 x 2 ..+bnXn F(09)= (-23.964)+(18.823*3)+ (.142*250)+(-15.365*.12)+(-.228`*24) f(09)= Rs. 60.7 lakhs 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
  • 49. ......Desktopmiddle level multiple regression <ul><li>Open stat result </li></ul>
  • 50. Forecasting by Regression (Consumer industries ) Y= a+b 1 X 1 +b 2 x 2 ..+bnXn F(09)= (-.717)+(76.111*.24)+ (.334*250)+(-55.750*.12)+(-1.225*24) f(09)= Rs. 64.95 lakhs 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
  • 51. ......Desktopcommercial l multiple regression <ul><li>Open stat result </li></ul>
  • 52. Summary of forecasts 64.95 56.6 55.3 73.72 Con .indus. 60.7 52 50.3 64.35 Middle level 41.9 32 30.6 37.2 Lower level Multiple regression Weighted average Moving average Simple trend analysis Targeted areas
  • 53. Conclusion <ul><li>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 . </li></ul><ul><li>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 .. </li></ul>

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