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Applied AI to improve Retail and supply chain profitability

Foto del escritor: Cesar Lugo MarcosCesar Lugo Marcos

Actualizado: 15 ene

When using machine learning to improve Retail and supply chain profitability, one high impact way is to reduce out of stocks and at the same time improve price and promotion profitability. By doing so, the combined benefits not only add up, but get multiplied each other. Then, when you optimize turnover speed and reduce shrinkage, reducing total cost of inventory, GMROI gets maximized, adding up straight to the bottom line.


Machine learning predictive analytics are just part of the solution. Other than accurately predicting revenue and gross profit increase, as well as price elasticity of demand, we also need to apply research of operations and econometrics to use those predictions in optimization mechanisms, including the ability to analyze multiple scenarios, in order to align them to the current category management strategies and goals.


Also, price automation needs to be considered to balance the optimum prices and promotions with competitive prices, gross margin rules and other price policies, to maintain alignment with customer preferences, and improve the right positioning within the target market.


A solution that combines all those AI and optimization algorithms in a friendly way, to facilitate decisions through augmenting managers Cognitive capabilities, facilitates those decisions, and to adjust as needed thought the merchandising and supply chain management process. One is JuiceMantics, you can learn more:


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