Definition of Inventory Forecasting
Inventory Forecasting is the process in which the historical sales data, historical purchasing data, current demand planning, planned production, and distribution resource plan data are used for predicting inventory levels in a future time period. Since Inventory is dependent on supply and demand, this forecast is calculated based on the delta between the two.
Based on the specific requirement of business, Inventory Forecasting can be carried out at an item level, product category level, item-location level and at a category-location level. Inventory Forecasting can be used to estimate inventory levels of finished goods, raw material and work in process goods – but is primarily used for finished goods analysis.
Excellent Demand Planning practices can further augment the results of the Inventory Forecasting process. It is recommended to use a scientific and system-driven Inventory Forecasting process for timely and reliable output.
Read More: How Do You Create the Right Inventory Balance?
Key input components of Inventory Forecasting
For a better and informed Inventory Forecasting process, it is important for Supply Chain Managers to understand the various input components and factors that influence the Inventory Forecasting process. The following is an indicative list of input components applicable to most businesses. However, detailed consideration needs to be given to the type of business, type of products, marketing activities and competitor moves for arriving at specific inputs applicable.
The key input components of Inventory Forecasting are:
- Historical sales data
- Historical purchasing data
- Purchasing lead time
- Manufacturing lead time
- Distribution lead time
- Demand Planning
- Supply or Central Planning
- Production Planning
- Raw Material Planning
- Distribution Resource Plan
Read More: Supply Chain Efficiency & Smart Planning Engines
Basic types of Inventory Forecasting
Outlined below are the two basic types of Inventory Forecasting. Selecting the applicable technique of Inventory Forecasting is dependent on the nature of the business, availability of data, product obsolescence risk involved, marketing activities and competitor moves.
1. Quantitative Forecasting
Quantitative technique of forecasting uses past historical data for predicting future inventory levels. Quantitative techniques use Time Series or Associated Model. The techniques may include Simple Average, Simple Moving Average, Weighted Moving Average and Exponential Smoothing.
2. Qualitative Forecasting
Qualitative technique uses judgment or opinion of the respondents who may include experts from respective fields. Delphi is a very popular technique that includes selective experts in the field, who on the basis of their knowledge may project what is likely to happen in the future. The qualitative technique is useful where there is insufficient data and while handling new products or markets.
Read More: Why is Demand Forecasting Important for Effective Supply Chain Management?
Factors affecting Inventory Levels
There are many factors that affect the inventory levels and cause a variation in the projected vs. actual inventory levels. Some of the major factors include – Supplier performance, In-bound Logistics, Production capacity utilization, Equipment breakdown, Quality issues, Actual customer demand, Out-bound Logistics, Competitor moves, Seasonality, Environmental factors, Macroeconomics, Geo-political factors, and Regulatory changes.
A dynamic and agile Inventory Forecasting process can pick up the early warning signals of internal and external factors which can likely have a major impact on the projected inventory levels. Regular monitoring and fine-tuning of the Inventory Forecasting process is crucial for mitigating risks of lost customer orders or product obsolescence.
Characteristics of Inventory Forecasting
Following are the major characteristics of Inventory Forecasting and need to be considered while evaluating the output results for decision making:
- All Inventory Forecasts have inherent errors due to assumptions and hence are always inaccurate. Hence they need to specify expected value, minimum and maximum value and percent of error.
- Short term forecasts are generally more accurate than long-term forecasts.
- Aggregate forecasts are generally more accurate than individual stand-alone forecasts due to a lower standard of deviation.
- In general, farther up the Supply Chain, a company is, the greater is the distortion of information it receives.
Read More: Everything You Need to Know About Forecasting
Role and Importance of Inventory Forecasting in Businesses
Inventory Forecasting is an important business process around which the operational plans of a company are devised. There are three major roles of Inventory Forecasting in effective Supply Chain Management:
- Pivotal in operational planning of Business: Inventory Forecasting is the underlying hypothesis for operational business activities like the estimation of customer service levels, purchasing and production prioritization, re-allocation, and re-positioning of downstream inventory, obsolescence risk assessment, and mitigation.
- Initiating all reprioritization processes of Supply Chain: Inventory Forecasting assists reprioritization and reallocation processes of Supply Chain like fine-tuning of Raw material plan, Purchasing, Inbound Logistics, Manufacturing, Outbound Logistics and fine-tuning of Distribution Resource Plan. Better Inventory Forecasts help optimize inventory levels and capacity utilization.
- Driving all pull-processes of Supply Chain: Inventory Forecasting drives all pull-process of Supply Chain like Order management, Packaging, Distribution, and Outbound Logistics. Better Inventory Forecast improves the Distribution and Logistics and increases Customer Service Levels.