Retailers have access to the same tools for managing their exposure to market volatility. They can hedge against price increases by locking in futures contracts, and they can tune their positions with options and swaps.
What competing retailers often don’t have is the same access to accurate demand forecasting. The accuracy of these predictions can determine the profitability of one retailer, or the collapse of another.
With the increased complexities of the energy transition, retailers regularly face the existential threat of getting their predictions horribly wrong.
In this paper, we examine:
The four biggest drivers of volatility in the market including:
1) the increase of extreme weather events and the new winter peak
2) the complexity of scaling solar
3) the proliferation of power storage and
4) EVs as amoving target
How conventional demand forecasting is not equipped to handle the increased volume of useful data.
How advanced, AI-powered demand forecasting is making the difference for successful retailers.
With accurate demand forecasts in place, retailers will gain a competitive advantage in acquiring and retaining customers. The money saved with smaller risk premiums and reliable cost-savings in the wholesale market can be put to more aggressive price offerings.
Plus, they can develop more complex customer programs if they have robust models to forecast them and manage the risk.
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