Comprehensive data modelling and analysis: E2E supply chain analytics requires data from across the entire supply chain to identify inefficiencies and optimize performance. A proper data model is essential for meaningful insights

Data integration and visualization: integrating data from various sources with advanced analytics provides actionable insights, ensuring a seamless flow of information and enables decision-making. Teams must develop and iterate quickly to maintain traction and reliability

Buy-in and investment: achieving the full benefits of E2E supply chain analytics requires significant investment in technology, training, and even process changes. Garnering leadership buy-in and establish effective thought management is crucial in the success of deploying analytics and intelligence