Demand Forecast to Optimize Sales Prize

THE COMPANY

Pool of farmers from the west coast of US, operating for over 30 years in the industry. Their mission as global hop suppliers is to connect brewers with family hop farms. As a leader in innovation, quality and client service, it has turned into a resource for brewers since their deliverables base on sustainable solutions and research.

THE CHALLENGE

THE COMPANY needed to forecast monthly deliveries of the different specific crops to redirect the excess of demand to spot market, generating additional income and avoiding aging of stock at the same time.

THE SOLUTION

We have used a time series predictive model to forecast specific demand per variety combined with a risk assessment model (ARIMA / LSTM) to quantify compensation between spot market income and the Company risk for failing contracts with their   customers.

BENEFITSS

  • 160% increase in hop sales in the spot market, 95% confidence for not failing said contracts.
  • Inventory cost reduction resulting from foreseeing future events.
  • Adaptive algorithm which renders robustness before the continuous change of scenarios.
  • Possibility to modify the confidence interval the Company holds to take the risk of stock shortage regarding already entered long-term contracts.
Python