7.
Explanation
Qualitative methods of demand forecasting are used when historical data or quantitative information is limited, unreliable, or insufficient. These methods rely on expert judgment, opinions, and qualitative data to make forecasts. Here are various qualitative methods and the criteria for selecting the most suitable one:
1. Market Research: Gathering information through surveys, focus groups, and interviews to understand customer preferences, intentions, and opinions. This method is useful when you need to explore potential demand for a new product.
2. Expert Opinion: Consulting experts, industry specialists, or professionals who have knowledge of the market and can provide insights into future demand trends. It’s valuable when expert judgment is considered reliable.
3. Delphi Method: Involving a panel of experts who provide anonymous, independent forecasts. The experts’ inputs are collected and then refined through multiple rounds of discussion and consensus building. It’s suitable for complex and uncertain situations.
4. Historical Analogy: Drawing parallels with past situations or products to forecast future demand. This method is useful when historical data for a similar product or market exists.
5. Panel Consensus: Bringing together a group of knowledgeable individuals to discuss and collectively estimate future demand. This is useful when you want diverse opinions and inputs for forecasting.
6. Scenario Analysis: Creating different scenarios based on possible future events and estimating demand under each scenario. It’s suitable for situations with high uncertainty, allowing for a range of forecasts.
7. Grassroots Forecasting: Gathering information from individuals close to customers, such as salespeople or retailers, who have direct contact with the market. It’s useful for localized or niche market forecasting.
Criteria for selecting a suitable qualitative method:
1. Data Availability: Consider the availability of relevant data. If historical data is scarce or unreliable, qualitative methods may be more appropriate.
2. Uncertainty Level: Assess the level of uncertainty in the market or industry. Qualitative methods are well-suited for situations with high uncertainty.
3. Time Frame: Consider the time frame for which you need to make forecasts. Some methods may be more time-consuming than others.
4. Budget and Resources: Evaluate the resources available for forecasting. Qualitative methods can vary in terms of cost and expertise required.
5. Accuracy and Reliability: Depending on the nature of the forecast and its importance, you may choose a method that has a track record of providing reliable forecasts.
6. Expertise: Assess the availability of experts or specialists in the field who can contribute to the forecasting process.
7. Scope of Forecast: Determine the scope of the forecast, whether it’s for a new product, a niche market, or a broader industry. Different methods may be more suitable for different scopes.
Ultimately, the choice of a qualitative forecasting method should align with the specific needs and constraints of the forecasting task and the level of accuracy required to support decision-making.