Understanding Demand Forecasting

What is demand forecasting?

• A method for increasing product prices

• A technique for improving customer service

• Demand forecasting is the estimation of future customer demand for a product or service.

• A strategy for reducing inventory levels

Name two qualitative methods of demand forecasting.

• Inventory management

• Expert opinion, Market research

• Sales data review

• Statistical analysis

What is the purpose of time series analysis in demand forecasting?

• To focus solely on external factors affecting demand.

• To eliminate all historical data for better accuracy.

• To calculate the average demand over a single period.

• The purpose of time series analysis in demand forecasting is to analyze historical data to identify trends and patterns for predicting future demand.

Explain the difference between qualitative and quantitative forecasting methods.

• Qualitative forecasting relies solely on historical data.

• Quantitative forecasting is based on expert opinions and intuition.

• Qualitative forecasting uses mathematical models for predictions.

• Qualitative forecasting is subjective and opinion-based, while quantitative forecasting is objective and data-driven.

What is a moving average method in demand forecasting?

• The moving average method is a forecasting technique that averages past demand data to predict future demand.

• A forecasting approach that focuses solely on seasonal trends.

• A method that uses only the most recent demand data for predictions.

• A technique that relies on expert opinions rather than historical data.

How does seasonality affect demand forecasting?

• Seasonality only affects supply chain logistics, not demand.

• Seasonality affects demand forecasting by introducing predictable fluctuations that help businesses anticipate changes in demand throughout the year.

• Seasonality leads to random fluctuations that cannot be predicted.

• Seasonality has no impact on demand forecasting.

What role does historical data play in demand forecasting?

• Historical data is only useful for financial analysis.

• Historical data only confuses the forecasting process.

• Historical data is irrelevant to demand forecasting.

• Historical data is crucial for identifying trends and patterns in demand, enabling accurate forecasting.

Describe the Delphi method of forecasting.

• The Delphi method is a statistical analysis technique that does not involve expert opinions.

• The Delphi method is a forecasting technique that uses a series of questionnaires to gather and refine expert opinions anonymously.

• The Delphi method relies solely on historical data for predictions.

• The Delphi method involves public discussions among experts to reach a consensus.

What is the significance of the mean absolute percentage error (MAPE) in forecasting?

• MAPE is used to calculate the total revenue generated by a business.

• MAPE provides a measure of the total number of forecasts made.

• MAPE is significant as it measures forecasting accuracy in percentage terms, allowing for easy interpretation and comparison.

• MAPE is significant for determining the average cost of production.

How can technology improve demand forecasting accuracy?

• By relying solely on historical sales without any adjustments.

• By using manual calculations to predict future demand.

• By reducing the amount of data collected for analysis.

• Technology improves demand forecasting accuracy by utilizing advanced analytics and machine learning to analyze data and identify patterns.