DecisionNext Names Michael Farrand as Global Head of Food

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Published: January 1, 2021

Farrand remarked, “Having had the pleasure of working with the talented DecisionNext team over the past few months it became clear to me that our values and goals aligned well, and that there was real value in creating increased rigor around the food space, especially in our current business climate. The timing is perfect.”

“Michael is going to be tremendously important in DecisionNext’s mission to create massive value for our customers by combining DecisionNext’s machine learning engine with the unique market insights of our customers in the food space,” said Arden Arnold, President of DecisionNext. “He has a unique understanding of the key levers of profitability across the food value chain, and where improved risk management and predictive analytics can drive value,” continued Arnold.

Powered by proprietary machine learning algorithms, DecisionNext allows market experts to bring together the best of human and machine intelligence to improve market visibility and forecast accuracy through transparent, interactive software. By having the ability to not just forecast markets, but simulate market outcomes, decision-makers can more effectively evaluate options in high value, high frequency decisions across sourcing, operations, and sales.

About DecisionNext
DecisionNext enables the world’s largest companies to make risk aware sourcing, operations, and sales decisions in commodity markets through dynamic market simulation software. Powered by proprietary machine learning algorithms, the platform aggregates hundreds of data series, quantifies market risk through probabilistic forecasting, and increases forecast accuracy. Companies use DecisionNext software for procurement, sales, pricing, and risk management analytics.

Industry leaders in agriculture, natural resources, and other commodity businesses are able to communicate a market story internally or through their value chain, ultimately strengthening relationships and improving supply chains.

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