Gain machine driven sales predictions, incorporate price sensitivity for sales predictions, establish a Data Science & ML Platform using the Azure ecosystem, Improve accuracy of planning process.
Traditional Sales & Operations Process involves manual activities such as preparation of data, manual forecasting and aggregation of organization wide forecasted v/s actual view. This results in the baseline forecast for the upcoming months. This process may take up to 2 weeks and is entirely manual which may result in lower accuracies of forecast & delays in meeting business requirements. The manual predictions/forecasts by sales teams are always with 1 dimension & generally tend to be less accurate which skews monthly sales forecasts at a broader level.
We have helped several companies create machine-based algorithms using Azure ML to save time & increase accuracy of sales budgeting and planning process by establishing a data platform on Azure creating a single source of truth. We help you extract data across multiple sources using Azure Data Factory & Azure Databricks, engineer the data and store on Azure Data Lake (Blob Storage) and design and create the data warehouse on Azure Synapse. We apply machine-based rules using Azure ML and help Sales & Operations Leaders visualize the forecasts at various granularities like Customer-SKU & Business Unit Category level on Power BI. This helps eliminate manual effort and automate a majority of the planning process. The machine-driven process will also take into consideration price sensitivity which will enable sales teams to visualize forecasts at various price points helping them decide on discounting campaigns.
Azure Components Delivered: