Terminal Volume Forecasting
September 10, 2020
Leading Player in Oil Processing Industry
- In-house forecasting of products was not giving accurate information; company wanted an accurate forecasting model.
- Company wanted our assistance in understanding the appropriate KPI’s / metrics that have a direct influencing impact on the petroleum sales
- Company also wanted a forecasting model which will forecast at a Customer / Channel / Terminal level; to plan the inventory.
Analytics Led Approach
- Selection of Response variables based on Statistical Tests.
- Understand and identify the key KPI’s for each segment
- SPSS to analyze data using Statistical techniques, user friendly (Multiple Regression Analysis)
- Correlation Analysis to identify the relationship.
- Regression Analysis to predict / forecast.
- Pricing – Based on the existing / recent demand, pricing can be done without any intuition (By an Account Manager)
- Trend Analysis. And structured steps to understand the relationships between multiple fields in the datasets.
Critical Success Factors
- Channel Behavior – Depicts the prevailing fluctuation and also helps us in tracking the product at a channel level.
- Pantry Loading – Over loading of products can be avoided and Inventory can be planned accurately to meet demand