Micro Level Forecasting
This method involves analyzing data at a small level to understand demand patterns in specific markets or segments. Additionally, it helps understand demand variations across different market segments.
Example:
IndiaPicture Studio employs micro-level forecasting to anticipate demand for its services. By conducting detailed analyses of specific services like post-production, animation, and voice-over, the firm utilizes historical data and statistical analysis to inform pricing, staffing, and production decisions.
Features:
- Detailed Analysis: Micro-level Forecasting entails thorough analyses of specific products, services, or markets.
- Data-Driven Approach: It relies on historical data and statistical analysis to generate forecasts.
- Short-Term Focus: Micro-level Forecasting primarily focuses on short-term predictions, such as daily or weekly sales forecasts.
Advantages:
- Accuracy: Micro-level Forecasting tends to be more accurate than macro-level forecasting due to its specificity.
- Flexibility: It allows for greater flexibility in adjusting forecasts in response to changing conditions.
- Decision-Making Support: Micro-level Forecasting aids businesses in making well-informed decisions regarding pricing, inventory, and production.
Disadvantages:
- Limited Scope: Micro-level Forecasting may overlook broader market trends and factors.
- Data Requirements: It demands substantial data, which can be resource-intensive to collect.
- Complexity: Micro-level Forecasting can be complex and necessitate specialized statistical analysis skills.
Types of Demand Forecast
Demand Forecasting involves employing predictive analysis of past data to anticipate and project customers’ future demand for products or services. This process aids firms in enhancing supply-related decisions by projecting total sales and revenue for upcoming periods, typically by examining historical data. By utilizing demand forecasting, firms can optimize their inventory management and make informed choices regarding inventory planning, production, pricing, and other operational aspects, all guided by the anticipated future demand patterns.
Geeky Takeaways:
- Demand Forecasting involves predictive analysis of past data to anticipate and project future customer demand.
- This forecasting will help businesses make informed supply-related decisions.
- Demand Forecasting includes active demand forecasting, external macro forecasting, passive demand forecasting, the Delphi method, market research, econometrics, sales, internal demand forecasting, trend projection, expert opinion, micro-level forecasting, barometric forecasting, and sales channel forecasting.
- Other types of demand forecasting include historical data analysis, seasonality analysis, statistical analysis, and macro-level forecasting, among others.
Table of Content
- Types of Demand Forecast
- 1. Active Demand Forecasting
- 2. External Macro Forecasting
- 3. Passive Demand Forecasting
- 4. Delphi Method
- 5. Market Research
- 6. Econometrics
- 7. Sales
- 8. Internal Demand Forecasting
- 9. Trend Projection
- 10. Expert Opinion
- 11. Micro Level Forecasting