Modern VMI brings together multiple data streams to speed up and optimize stock levels at a retailer. In order to achieve this, there has to be a mutual agreement between the retailer and supplier to use VMI and subsequently share the relevant data.
Once an agreement has been met, the next step is for the retailer to share data with the supplier; this data usually provides:
Stock levels
In order to achieve the most basic VMI functionality, stock level information is required to keep the supplier updated about reducing stock levels.
Logistics timescales
Accurate forecasting can only be realized by building logistics timelines specific to that particular supply chain into the model.
Seasonal trends
An additional layer of intelligence can then be added to the forecasting model by taking historical seasonal trends from the retailer and feeding those into future stock-level forecasts.
Short-term trends
Achieving the next level of optimization can then be achieved by monitoring short term trends in the data that can be triggered by external factors such as the economy or even the weather.
When all this data has been shared and built into the forecasting model, the VMI solution is ready to be made live. The platform then automatically takes all of these data inputs and produces accurate recommendations to the supplier, who are then equipped to send stock at the optimal time.