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How risk aware are your commodity market decisions?

Published by Mike Neal June 08, 2018

 

 

 

 

Market volatility makes decision making a challenge. Amidst market uncertainty, decision makers routinely make risky multi-billion dollar bets based on intuition and gut feel about expected future prices. 

Bringing quantitative tools to bear can help decision makers manage uncertainty. Through the power of predictive analytics, we can not only forecast markets, we can forecast possible market outcomes. Knowing the probabilities of potential prices to occur allows us to make risk aware decisions...better decisions. But the real power comes from the combination of quantified price forecasts, probabilities of prices to occur, and recommendations on how to monetize the forecast.

Human Plus Machine

The DecisionNext approach blends the best insights from your market experts (humans) with data models. The trick is to bring them together in a way that unleashes the power of each, delivering more effective results than either could ever achieve alone.

Both humans and technology bring something unique and important value to the forecasting equation. But both bring problems, too. The trick is to bring them together in a way that unleashes the power of each, delivering more effective results than either could ever achieve alone. 

With the proven results of analytic-driven decisions, there is no excuse today for commodity companies to leave money on the table by using gut feel in today’s volatile market.

Business Use Cases

Buying, pricing, and sales teams need to be able to make confident decisions in commodity markets. DecisionNext uses predictive analytics to make recommendations with specific actions you can take based on a forecast. Let's call this prescriptive analytics since its about the action! The real power comes from combining risk aware forecasts with recommendations on how to monetize the forecast by answering questions like:

  • In light of this price forecast, what should by sales portfolio look like of formula vs spot sales? 
  • What product mix should I produce?
  • How far forward bought should I get to reduce COGS?

With the power of analytics in today's data landscape, commodity companies should be able to focus sales reps on selling the right product in the right time period; help purchasing teams determine how much and when to buy to minimize inventory costs; and evaluate the risk and reward of buy/sell transactions. DecisionNext provides the tools you need to make risk aware decisions in commodity markets.

Advanced Analytics is Essential

Many industries have changed the game with advanced, highly focused analytics. It started on the revenue side of businesses in the early 1980’s with airlines. Today you cannot be competitive in the airline industry without analytics-driven decision-making, referred to in that industry as “revenue management."

Following the airline industry, data analytics begin to take hold in hotels and financial services. Supply chain followed suit. And then retail. 


Adopting analytics-driven forecasting isn’t just a matter or profitability. It’s a matter of survival.

We formed DecisionNext to address this problem; to help companies make sound, empirically based, unbiased, risk aware business decisions in volatile environments. By implementing a rigorous, analytics-driven forecasting process, companies can make more confident decisions through a repeatable process that improves over time through a clear feedback loop, making the market experts on your team AND the mathematical models better. 

You Should Profit from Market Volatility

Predictive analytics helps companies make buying and selling decisions in commodity markets. Are you ready to explore analytics for your business? See for yourself how DecisionNext is reimagining forecasting and decision making in commodities businesses with sophisticated technology. Learn how DecisionNext helps you make risk aware decisions.