LECTURE 9 SALES FORECASTING (1)

Page 1: Lecture Overview

  • Lecture 9: Focus on Sales Forecasting and Financial Analysis

Page 2: Difficulties in Financial Analysis for New Products

  • Challenges:

    • Target users often lack knowledge or may not disclose information.

    • Poor execution of market research can lead to inaccurate data.

    • Market dynamics create uncertainties, complicating forecasts.

    • Internal attitudes can bias the financial analysis.

    • Inadequate accounting may lead to misjudgment.

    • Rushing products to market can result in flawed forecasting.

    • Dependence on historical data can be misleading in volatile markets.

    • Rapid technological changes introduce unpredictability.

Page 3: Accuracy of Forecasters

  • Successful Predictions (1967):

    • Artificial organs available by 1982.

    • Human organ transplants expected by 1987.

    • Credit cards largely replacing currency by 1986.

    • Automation predicted in industries and management decisions by 1987.

    • Lunar landing anticipated by 1970.

    • Urbanization projected with three of four Americans living in cities by 1986.

    • Recreation and entertainment expenditures expected to double by 1986.

Page 4: Misjudgments of Forecasters

  • Failed Predictions (1967):

    • Permanent base on the moon was thought possible by 1987.

    • Manned landings on other planets expected by 1980.

    • Urban living largely in high-rises anticipated by 1986.

    • Cars banned from city centers by 1986.

    • Laboratory creation of primitive life expected by 1989.

    • Full-color 3D TV availability globally anticipated.

  • Statistic: About two-thirds of forecasts were ultimately accurate.

Page 5: New Product Forecasting Strategies

  • Forecasting Based on Market:

    • Current Product Technology:

      • Focus on cost reductions and process improvements.

      • Use sales analysis for forecasting.

    • New Product Technology:

      • Focus on line extensions.

      • Use product line and life cycle analysis for forecasting.

    • New Market Opportunities:

      • Identify new product uses or markets.

      • Utilize customer and market analysis.

      • Forecasting types include scenario analysis for innovative products.

  • Source: K. B. Kahn’s contributions in the PDMA Handbook.

Page 6: Solutions for Financial Analysis Problems

  • Improvement Strategies:

    • Enhance the process for existing products.

    • Apply life cycle concepts to financial analysis.

    • Reduce reliance on unreliable forecasts.

    • Focus on what is known rather than assumptions.

    • Evaluate the situation rather than just numeric outcomes (e.g., Campbell Soup example).

    • Commit to low-cost development and marketing strategies.

    • Prepare for associated risks in product launches.

    • Avoid a one-size-fits-all approach in financial analyses.

    • Improve financial forecasting methods continually.

Page 7: Sales Forecasting Using Purchase Intentions

  • Methodology:

    • Use top-two-box scores from concept testing, adjust accordingly.

    • Scores Breakdown:

      • Definitely buy: 5%

      • Probably buy: 36%

    • Calibrated Actual Buy Rates:

      • 80% of 'definitelies' become purchases.

      • 33% of 'probablies' become purchases.

    • Forecasted Market Share Calculation:

      • Market share = (0.8)(5%) + (0.33)(36%) = 16%.

Page 8: A-T-A-R Model for Sales Forecasting

  • Model Assumptions:

    • Assume awareness = 90% and availability = 67%.

    • Trial rate = 16%: proportion of aware and available consumers who try the product.

    • Key Ratios:

      • RS (switching proportion) = 70%.

      • Rr (repeat purchase proportion) = 60%.

    • Calculation for Long-Run Repeat Purchase:

      • Rt = RS / (1 + RS - Rr) = 63.6%.

    • Market Share Calculation:

      • Market Share = Trial x Rt x Awareness x Availability = 16% x 63.6% x 90% x 67% = 6.14%.

Page 9: A-T-A-R Model Results Visualization

  • Results Display:

    • Bar chart indicates success rates and proportions based on the A-T-A-R model.

    • Values presented in context of market share outcomes and forecasts.

Page 10: Forecast of Product Diffusion

  • Sales Forecasting Over Time (in $000s):

    • Values presented for years indicating projected sales from year 0 to year 10, showcasing growth dynamics.

Page 11: Life Cycle Assessment of Financial Analysis

  • Stages of Financial Analysis:

    • 5 Stages:

      1. Concept generation

      2. Concept/project selection

      3. Full screening

      4. Market testing

      5. Evaluation of market life and consumer response.

    • Completeness of Financial Analysis illustrated in life cycle graph (0% to 100%).

Page 12: Concept Evaluation Tools

  • Critical Factors for Evaluation:

    • Strategic Fit: Alignment with corporate vision.

    • Customer Fit: Efficacy in meeting consumer needs.

    • Consumer Fit: Addressing unmet needs effectively.

    • Market Attractiveness: Uniqueness in the competitive landscape.

    • Technical Feasibility: Practical and protectable concepts.

    • Financial Returns: Assessment on breaking even in an appropriate time frame.

  • Source: Erika B. Seamon on Innovative Culture in New Product Development.

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