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Optimizing your energy hedging strategy - Which key parameters can you play with?

The past few years have been challenging for industrial energy buyers, with multiple external and internal factors disrupting their modus operandi.

What is the current best-in-class approach to assessing potential energy hedging strategies?

• The magic of optimization
• Key decision parameters
• A blueprint for testing potential strategies

Decision intelligence and the challenges of asset managers

Active asset management is undergoing profound, and often painful change. For example, PwC estimates that by 2027, 16% of existing asset management organisations will have disappeared or been swallowed!

This datasheet explores how active asset managers could leverage decision intelligence and Ai to:

• Secure performance
• Control costs
• Integrate ESG

New to energy hedging? Five best practices for European energy buyers

Faced with market volatility, lots of industrial energy buyers have started experimenting with hedging. Discover five best practices emerging from our conversations with them.

• Risk management
• Performance measurement
• Simplicity vs. sophistication
• Alignement with operations
• Periodic reviews

Testimonial - Boosting energy procurement reports with Datapred

Discover how Opéra Energie, the leading energy broker for professional and enterprise clients in France, uses Datapred to boost client reporting.

• Real-time situation vs. budget
• Simple visualization of past transactions
• Market analyses and forecasts

Four workable way for industrial companies to reduce their energy bill

Most European companies are currently reassessing their energy buying strategies. This nine-page datasheet discusses four ways technology can help save 5% off their energy bill.

• Sweating your assets
• Proactively managing price-adjustment formulas
• Playing with the mix of futures contracts
• Combining spot and term-based transactions

Testimonial - Keeping propane hedging costs under control with Datapred

Discover how Butagaz, the leading provider of bottled and bulk gas solutions, uses the Datapred digital twin to save 3-5% per year on its propane hedging costs.

• Combination of market analyses and industrial optimization
• Scenarios, simulations and recommendations
• Constantly updated foundation for hedging decisions

Direct material procurement - What to expect from machine learning

Machine learning creates new opportunities for commodity, energy and raw material buyers. This three-page datasheet describes the main benefits that Chief Procurement Officers can expect from machine learning.

• Unified view of the market
• Price forecasting
• Better understanding of price risk
• Better alignement with operations
• Effective long-term planning
• Broader hedging opportunities

Getting ahead with Datapred

Raw material and energy procurement is racing into a period of profound change. This 11-page eBook discusses recent Procurement digitization trends and describes how Datapred helps industrial buyers with their digital transformation process.

• More data, more to manage
• A new direction for direct procurement
• Combining the external and internal views
• Impact on the bottom line

Direct material procurement optimization - What's required?

Datapred for Procurement can shave 3-5% off your commodity, energy and raw material spend, year over year. This six-page datasheet discusses the main requirements for using Datapred:

• Price and contextual data
• Costs and constraints
• Wiggle room
• Basic technical stack

Datapred and sustainability

The Datapred buyer checklist

This 4-page datasheet summarizes our answers to Gartner's top 12 questions corporate buyers should ask to AI solution providers.

Key strengths of the Datapred modeling engine

DDatapred includes a powerful modeling engine for continuous intelligence applications. This three-page datasheet discusses the key strengths of that proprietary technology:

• Handling streaming data
• Aggregating multiple models
• Providing explainability
• Accelerating deployment

Bring your own model

Datapred lets you leverage your experience and data science competencies, and bring your own predictive or optimization models to the software. This three-page datasheet discusses how.

Vital checklist for time series modeling

Applying machine learning to time series is tricky. Don't dive into your time series modeling project without checking this three-page life-saving list first.