Kenneth B. Kahn Ph.D.

New Product Forecasting Issues

Kenneth B. Kahn, Ph.D.The University of Tennessee

Department of Marketing and Logistics315 Stokely Management Center

Knoxville, Tennessee 37996-0530(865) 974-2609kkahn@utk.edu

Kenneth B. Kahn Ph.D.

New Product Forecasting Issues

Low accuracy (high forecast error)

Low credibility

Limited amount of data available for analysis

Inability to fully capture market complexity, cannibalization, market penetration rate, etc.

Limited amount of time for analysis

Kenneth B. Kahn Ph.D.

New Product Forecast Accuracy

Source: Kenneth B. Kahn, Journal of Product Innovation Management, March 2002

Type of New Product

Average % Accuracy Achieved (Standard

Deviation, Sample Size)

Forecast Horizon in Months (Standard Deviation,

Sample Size)

Cost Improvements 71.62(s=22.46, n=29)

21.15(s=21.15, n=40)

Product Improvements 64.88(s=23.63, n=45)

19.96(s=18.20, n=102)

Line Extensions 62.76(s=22.25, n=45)

20.84(s=18.58, n=97)

Market Extensions 54.33(s=24.02, n=42)

23.58(s=21.26, n=93)

New Category Entries(New-to-the-Company)

46.83(s=24.31, n=30)

34.56(s=35.21, n=45)

New-to-the-World 40.36(s=24.72, n=39)

36.08(s=35.96, n=93)

Note: n = Sample sizeS= Standard deviation

Type of New Product

Average % Accuracy Achieved (Standard

Deviation, Sample Size)

Forecast Horizon in Months (Standard Deviation,

Sample Size)

Cost Improvements 71.62(s=22.46, n=29)

21.15(s=21.15, n=40)

Product Improvements 64.88(s=23.63, n=45)

19.96(s=18.20, n=102)

Line Extensions 62.76(s=22.25, n=45)

20.84(s=18.58, n=97)

Market Extensions 54.33(s=24.02, n=42)

23.58(s=21.26, n=93)

New Category Entries(New-to-the-Company)

46.83(s=24.31, n=30)

34.56(s=35.21, n=45)

New-to-the-World 40.36(s=24.72, n=39)

36.08(s=35.96, n=93)

Note: n = Sample sizeS= Standard deviation

Type of New ProductType of New Product

Average % Accuracy Achieved (Standard

Deviation, Sample Size)

Average % Accuracy Achieved (Standard

Deviation, Sample Size)

Forecast Horizon in Months (Standard Deviation,

Sample Size)

Forecast Horizon in Months (Standard Deviation,

Sample Size)

Cost ImprovementsCost Improvements 71.62(s=22.46, n=29)

71.62(s=22.46, n=29)

21.15(s=21.15, n=40)

21.15(s=21.15, n=40)

Product ImprovementsProduct Improvements 64.88(s=23.63, n=45)

64.88(s=23.63, n=45)

19.96(s=18.20, n=102)

19.96(s=18.20, n=102)

Line ExtensionsLine Extensions 62.76(s=22.25, n=45)

62.76(s=22.25, n=45)

20.84(s=18.58, n=97)

20.84(s=18.58, n=97)

Market ExtensionsMarket Extensions 54.33(s=24.02, n=42)

54.33(s=24.02, n=42)

23.58(s=21.26, n=93)

23.58(s=21.26, n=93)

New Category Entries(New-to-the-Company)New Category Entries(New-to-the-Company)

46.83(s=24.31, n=30)

46.83(s=24.31, n=30)

34.56(s=35.21, n=45)

34.56(s=35.21, n=45)

New-to-the-WorldNew-to-the-World 40.36(s=24.72, n=39)

40.36(s=24.72, n=39)

36.08(s=35.96, n=93)

36.08(s=35.96, n=93)

Note: n = Sample sizeS= Standard deviation

Note: n = Sample sizeS= Standard deviation

Cost Reductions

Kenneth B. Kahn Ph.D.

There is no silver bullet when it comes to new product forecasting.

New product forecasting success is a result of data, experience, cross-functional communication, business knowledge, and being connected to the customer.

Use a toolbox approach when applying new product forecasting techniques.

New product forecasting requires reconciliation of multiple techniques based on judgment and analytical skills.

New product forecasting is a process of assumptions management.

Think in terms of ranges, not specific numbers.

Some Keys to New Product Forecasting Success

Kenneth B. Kahn Ph.D.

Course Agenda

New Product Forecasting Issues and Considerations

Judgmental Approaches for Forecasting New Products

Customer- and Market-Research Based Techniques

Quantitative Approaches for Forecasting New Products

Managing the New Product Forecasting Process