Demand forecasting is the process of estimating future customer demand using historical data and other information over a set period of time. Demand forecasting Solution involves quantitative methods such as the use of data, and especially historical sales data, as well as statistical techniques from test markets.
How Demand Forecasting solution helps organisations?
Demand plays a crucial role in the management of every business. It helps an organization to reduce risks involved in business activities and make important business decisions. Apart from this, demand forecasting provides an insight into the organization’s capital investment and expansion decisions.
Techniques of forecasting
Some of the commonly used forecasting techniques are:
- Moving average
- Simple moving average
- Weighted moving average
- Exponential smoothing
- Holt Winter and Croston
The selection of the right technique depends on many factors.
However, analysts need to consider other factors such as Business understanding, Stage of Business (new, growth or steady) and Market understanding to identify the right technique. For example, it’s critical to understand the stage of business as different forecasting techniques get applied at different stages. One product may have a different technique suitable for different geographies. Different techniques give different results, choosing the best requires good expertise.
What is general practice followed in most companies?
The Depot Manager would generate the demand for the next quarter and share the numbers to the Division or Region head, who in turn would moderate the quantities and share it with the marketing team in Excel files. The marketing team would consolidate all the Excel files. Based on the inputs from Depot Managers, previous year trend and inventory holding at Depot, the demand is generated for India as well as Depots. This is shared to the entire team again all in Excel Files. Some of the issues with their planning process were
- The entire process is lengthy and consumes a lot of time.
- Manual consolidation of demand data at each level.
- Rework and moderation of the demand based on assumptions and not on statistical models.
- Consolidation of Inventory and In transit Quantity for various locations
- Manual adjustment on material available dates at Depots became a cumbersome activity.
- Demand planning for the promotional products was difficult as they were not considered as demand drivers.
- Delayed Depot replenishment.
What good practice can be enabled using Planvisage Demand Forecasting solution?
Past sales history of the products at location level is considered and various statistical techniques are run to arrive at the Forecast quantities. Among the various techniques, tool automatically picks up the best fit technique based on the MAP. This then can be released to the Depot managers to moderate the statistically generated forecast. Collaboration mechanism is enabled through the solution to arrive at a consensus forecast based on bottom-up and top-down approach.
It helps companies in
- Advance visibility of which Product sales are likely to go up, which of the products are likely to phase out.
- Provides Depot Managers baseline forecast quantities for them to consider while entering the demand quantities
- Consolidation/ Aggregation in a single window for Division heads, Region Heads or Marketing Team to view
- Role based authorization to view, edit quantities.
- Remarks or reasons and be provided for high or low demand quantity
- Visibility of Inventory levels and In-transit quantities across depots and plants.
- Visibility of replenishment and deployment of Products to Depots
What benefit can be expected using Planvisage solution?
- Forecast Accuracy improves from 55% to 75%
- Sophisticated Statistical Techniques other than just 3 Months Average to predict trend and seasonality at Item – Region combination
- Single unified system to collate data from Area Sales Manager and compare with Statistical Forecast
- Robust processes to efficiently manage dispatch planning and safety targets