Have knowledge of the computer applicability for business forecasting.

Have knowledge of the computer applicability for business
forecasting.

1. Business Forecasting Lanie R. Juera

2. At the end of this presentation, you should be able to: 1. Have knowledge of the computer applicability for business forecasting. 2. Understanding the needs and uses of forecast. 3. Have knowledge of the monitoring and controlling for business forecasting. 4. Understanding the tracking signal of forecast. 5. Have knowledge of the profit forecasting 6. Understanding the three approaches of profit forecast.

3. Forecasting is the prediction or estimation of future events, crucial for decision-making in business. It involves analyzing historical data, trends, and future events to make informed predictions. Business forecasting helps in planning future business development and coping with uncertainty.

4. Computer Applications to Business Forecasting Overview: Organizations today rely heavily on computer applications for business forecasting due to the complexity of data analysis and the need for accurate predictions. Advancements in Technology: Computer-aided forecasting has revolutionized the process, making it practical and affordable for businesses of all sizes. Benefits of Forecasting Software: Automates complex calculations, reducing the need for manual analysis. Simplifies data organization and management, especially for businesses with large datasets. Provides tools for analyzing trends, projecting future sales, and making informed decisions. Excel as a Forecasting Tool: Excel, a widely-used spreadsheet program, offers features such as pivot tables, averaging tools, and graphing, making it suitable for sales forecasting and trend analysis.

5. Need and Uses of Forecasting Importance of Forecasting: Decision Making: Forecasting assists in decision-making processes by providing insights into future sales volume and profits. Error Minimization: Helps minimize errors and inaccuracies by predicting future trends and outcomes. Feasibility Studies: Essential for conducting meaningful feasibility studies before implementing new projects or ventures. Inventory and Raw Material Planning: Provides input for planning and controlling inventories and raw materials efficiently. Prerequisite for Business Success: Forecasting is a prerequisite for success in both manufacturing and service sectors, enabling organizations to make informed decisions and plan effectively for the future.

6. Monitoring and Controlling Forecasts Overview: Forecasting isn't complete once it's done; it requires ongoing monitoring and control to ensure accuracy. Importance of Monitoring: It's essential to understand why actual demand differs from projected forecasts to improve future predictions. Tracking Signal: Utilized for monitoring forecasts by comparing actual demand to forecast values. Calculation: Tracking Signal = RSFE / MAD, where RSFE is the Running Sum of Forecasting Error and MAD is the Mean Absolute Deviation. Interpretation: Positive signals indicate demand exceeds forecast, while negative signals show demand is lower than forecast. Control Limits: Tracking signals are compared to predetermined control limits; exceeding these limits signals a need for reassessment of the forecasting method.

7. Adaptive Smoothing Method Overview: Adaptive smoothing is a monitoring and controlling instrument for forecasts that involves self-adjustment based on tracking signals. Purpose: Ensures continuous monitoring of tracking signals and adjustments to forecast models when necessary. Procedure: Initially, coefficients are selected based on minimizing forecast errors. These coefficients are then adjusted whenever errant tracking signals are detected. Example: In exponential smoothing, adjustments are made to the smoothing constant or beta coefficient if tracking signals exceed predetermined limits. Benefits: Adaptive smoothing improves forecast accuracy by dynamically adjusting forecast models in response to changing demand patterns.

8. Profit Forecasting Overview Importance: Profit forecasting is essential for management decision-making, particularly in competitive markets where profitability determines firm survival. Meaning: Profit forecasting involves projecting future earnings by analyzing sales behavior, commodity prices, costs, and competition. Relationship with Profit Improvement: Profit forecasting guides strategies for improving profitability by analyzing sales forecasts, cost budgets, capital expenditures, and planned profit levels. Objectives: The primary objective of profit forecasting is to enhance the quantum of profit by increasing sales, reducing costs, optimizing capital investment, and assessing alternative investment schemes.

9. Methods of Profit Forecasting Spot Projection: Forecasting entire profit and loss statements by projecting each element separately, subject to wide margins of error due to interrelated revenue and cost forecasting. Break-Even Analysis: Identifying functional relations of revenue and costs to output rate, with profit as a residual, or directly relating profits to output using break-even analysis data. Environmental Analysis: Relating company profits to key variables in its economic environment, such as general business activity and the price level, to forecast profits based on broader economic patterns. Integration of Approaches: These approaches are not mutually exclusive and can be used together for maximum information and accuracy in profit forecasting. Functional relations of costs and output, along with the impact of external economic forces, can enhance the accuracy of profit forecasts.

10. References: Churchill, Jr., Ford, N.M., Walker, Jr., O.C., Johnston, M.W., and Tanner, Jr., J.F. Sales Force Management, 6th ed., Boston: Irwin McGraw-Hill, (2000) Hughes, M.C. Forecasting Practice: Organizational Issues, The Journal of the Operational Research Society, Vol. 52, No. 2, pp 143 –149 (Feb., 2001). Lucey, T, Quantitative Techniques, 6th edition, London: Continuum BookPoweer/ELST, 2002, P.187. Crosby, John V. Cycles, Trends, and Turning Points: Practical Marketing and Sales Forecasting Techniques. NTC Publishing, 2000. Mentzer, John T., and Carol C. Bienstock. Sales Forecasting Management: Understanding the Techniques, Systems, and Management of the Sales Forecasting Process. Sage, 1988.