8. Measuring Market Opportunities- Forecasting and Market Research
8.0 Introductory Case Study
8.1 Every Forecast is Wrong


  1. ^ what is to beestimated or forecasted
  2. ^ the size of the market
  3. ^ size of the currently penetrated market
  4. ^ target market
  5. ^ top down approach
  6. ^ bottom up approach
  7. ^ break their anticipated demand into pieces and sum the components to create the summary

  8. ^ market segments, cutomers, products are pieces of the sales forecasting process

Before choosing a method to prepare a forecast, one first must know[1] what is to beestimated or forecasted.
First, there’s [2] the size of the potential market, that is, the likely demand from all actual and potential buyers of a product or product class.An estimate of market potential often serves as a starting point for preparing asales forecast, which we explore in more detail later in this module.
For Maddy and Laguë’s venture in Tanzania, prospective investors will want to know how large the potential market for telephone services will be in the coming years, measured perhaps in several ways:

  • in numbers of telephone users,

  • in numbers and/or minutes of calls, and
  • in dollars or Tanzanian shillings
          • * ***
                    • *
                          • * * *
                                        • *
                                            • t is comprised

of those consumers who are likely to have both the willingness and ability to buyand use a phone card or one of ACG’s other services at one of ACG’s pay phones.
There’s also the [3] size of the currently penetrated market, those who are actually using pay phones in Tanzania at the time of the forecast.

Investors will also want to know these figures – the size of the potential and penetrated markets for the marketsegments Maddy and Laguë intend to serve, their [4] target market.
They will also need a sales forecast, in which they predict sales revenues for ACG, for five yearsor so.
How might Maddy and Laguë do these things?

Established organisations employ two broad approaches for preparing a salesforecast: top-downand bottom-up.

Under the top-down approach[5] , a central person or persons take the responsibility for forecasting and prepare an overall forecast, perhaps using aggregate economic data, current sales trends, or other methods we describe shortly.

Under the bottom-up approach [6] , common in decentralised firms,
each part of the firm prepares its own sales forecast, and the parts are aggregated to create the forecast for the firm as a whole. For an example of how managers at Gap Inc. retailing divisions combine both methods to forecast next-year sales, see Exhibit 8.1.----
Exhibit 8.1 Forecasting next year’s sales at GapAt international retailer Gap Inc., forecasting sales for the next year for each of its divisions – Gap, Banana Republic, and Old Navy – is an important process that drives a host of decisions, including how much merchandise to plan to buy for the coming year.
Both top-down and bottom-up approaches are used. At Old Navy, for example, each merchandiser generates a forecast of what level of sales his or her category – women’s knit tops, men’s jeans, and so on – can achieve for the next year.
Group merchandise managers then provide their input and sum these numbers to create a total forecast from a merchandising perspective.

A second bottom-up forecast is generated by the store operations organisation, summing stores and groups of stores.
Simultaneously, a top-down figure is prepared at headquarters in California, using macroeconomic data, corporate growth objectives, and other factors.
The three forecasts are then compared, differences debated, and a final figure on which to base merchandise procurement and expense budgets is determined.
Though the effort to prepare such a forecast is considerable, the broad involvement in the process helps to ensure both knowledgeable input to the forecast as well as subsequent commitment to ‘make the numbers.’ Most important, Old Navy finds that the different processes together with the ensuing discussion lead to substantially better forecasts.
The bottom-up logic also applies to Maddy and Laguë’s task.
They can[7] break their anticipated demand into pieces and sum the components to create the summary
These[8] pieces could be market segments, such as small retailers, mobile
business people, consumers, and so on, or product lines, such as revenue fromphone cards or individual pay phones, voice-mail fees, pager fees, and the like.
Using the bottom-up approach presents numerous advantages.

First, this approach will force themto think clearly about the drivers of demand for each market segment or product line, and thus better understand the real potential of their business and its parts.

Second, they will be forced to make explicit assumptions about the
drivers of demand in each category, assumptions they can debate – and supportwith evidence gathered from their research – with prospective investors and whichthey can later verify as the business unfolds.

Third, such an approach facilitates ‘what if’ planning.
Various combinations of market segments and/or product lines can be combined to build a business plan that looks viable.

  1. client contact systems
  2. collector bias
  3. competitive advantage
  4. competitive intelligence
  5. computerised reorder system
  6. consumer behaviour
  7. data sources
  8. evidence based forecast
  9. experienced user
  10. internal records
  11. just in time
  12. logistical alliance
  13. market potential
  14. market segmentation
  15. market segments
  16. marketing program
  17. marketing research
  18. mass market
  19. mass market strategy
  20. michelin; us west;
  21. micro segmentation
  22. middleman
  23. modified rebuy
  24. multi-functional sales teams
  25. multilevel selling
  26. multiple buying
  27. multiple level relationships
  28. mutual trust
  29. narrow market segment
  30. narrow niche
  31. nationalisation of producers
  32. nerve center
  33. new task buy
  34. nine west group
  35. observation;direct observation' tanzania mobile;
  36. on-time delivery
  37. opportunity; research
  38. order handling
  39. organisation market
  40. organization marketing behaviour
  41. organizational behaviour
  42. organizational customers
  43. organizational demand
  44. organizational market
  45. organizational purchasing behaviour
  46. organizational purchasing process
  47. paperless exchange
  48. parity pricing
  49. personal selling
  50. personal use
  51. political risk
  52. potential market; penetrated market
  53. pre-delivery inspection
  54. pre-sale service
  55. prestige buyer
  56. pretender
  57. primary data
  58. procurement costs
  59. purchasing criteria
  60. qualitative data
  61. qualitative research
  62. quality assurance
  63. quality standards
  64. quantitative data
  65. quantitative research
  66. research objectives
  67. retention programme
  68. routine purchase
  69. sales forecast
  70. semantic differentiation scale
  71. sequence of information
  72. shared costs
  73. short term contracts
  74. social construction
  75. status oriented consumers
  76. stock availability
  77. straight rebuy
  78. supplier bargaining power
  79. supplier performance
  80. supplier reputation
  81. survey
  82. tabulation errors
  83. tanzania mobile
  84. target customers
  85. target market
  86. target marketing
  87. technical experts;
  88. test markets
  89. transaction cost
  90. trend forecasting
  91. trusting patron
  92. underlying consumer demand
  93. unethical demands
  94. unstated but implicit assumptions
  95. users
  96. value analysis
  97. value shopper
  98. vertical integration
  99. visceral thing that cannot be trained
  100. wild guess