CDPP Forecasting Techniques Flashcards

What is the main goal of demand forecasting in supply chain management?

Answer: To predict customer demand and optimize inventory management

The main goal of demand forecasting in supply chain management is to accurately predict future customer demand for products or services. This prediction is crucial for optimizing various supply chain activities, such as production planning, inventory levels, and resource allocation. Effective demand forecasting helps minimize stockouts, reduce excess inventory costs, and improve overall operational efficiency.

Which of the following is a qualitative forecasting method?

Answer: Delphi method

Qualitative forecasting methods rely on expert judgment, intuition, and subjective assessments rather than purely historical data and mathematical models. The Delphi method is a structured communication technique that involves a panel of experts providing anonymous forecasts, which are then aggregated and refined through several rounds of feedback. This approach is particularly useful when historical data is scarce or unreliable.

What does the moving average forecasting method help to smooth?

Answer: Short-term fluctuations in data

The moving average forecasting method calculates the average of a specific number of past data points to predict future values. Its primary purpose is to smooth out random, short-term fluctuations or noise in historical demand data. By averaging recent observations, it helps to reveal underlying trends and make the forecast less susceptible to erratic spikes or dips, providing a clearer picture of demand.

What is the primary advantage of using a regression model in demand forecasting?

Answer: It predicts demand based on variables that influence demand

Regression models are powerful quantitative forecasting tools that establish a statistical relationship between a dependent variable (demand) and one or more independent variables (factors influencing demand). This allows forecasters to predict demand based on changes in these explanatory variables, such as price, advertising spend, or economic indicators. It provides insights beyond just historical trends, explaining 'why' demand changes.

Why is seasonality an important factor in demand forecasting?

Answer: It helps predict the time periods with highest demand

Seasonality refers to predictable patterns or cycles in demand that occur at regular intervals, such as daily, weekly, or yearly. Recognizing and accounting for seasonality is crucial in demand forecasting because it allows businesses to anticipate periods of high or low demand. This enables better planning for inventory, staffing, production, and marketing efforts to meet customer needs efficiently and avoid stockouts or excess inventory.