Find out how Oil & Chemicals companies have been able to overcome disruptions and increase forecasting accuracy & service levels.
Demand planning for oil & chemical companies is very difficult, as demand can be very volatile for the following reasons:
Market uncertainty: A number of unpredictable market factors, such as global economic conditions, political events, and natural disasters have a real impact on the demand pattern.
Long lead times: The production processes for oil & chemicals are often complex and time-consuming, with long lead times for procurement, production, and delivery. This can result in difficulties when aligning supply and demand.
Global competition: The oil & chemical industries are highly competitive, with companies operating globally. This can lead to rapid changes in demand due to market shifts.
Environmental and regulatory pressures: The industry is facing increased environmental and regulatory pressures, which can impact demand and create additional difficulties in demand planning.
By leveraging the strengths of AI and combining them with the strengths of humans, oil & chemical companies can understand what drives their demand and translate downstream insights into opportunities that unite different supply chain stakeholders and allow the organization to focus on growth instead of firefighting.
Benefits of AI in Demand Planning
Time to put the market central in your planning processes and align around the volatility of your customers. By combining human knowledge with AI, Garvisempowers planners to makefast and accurate decisionsbased on data, real-time insights, and risk profiles.
Forecast error drops by 30 to 40%
Better decision-making: more stable production schedules
More accurate launch and planning of new products, as these are very costly
4-5 days reduction in safety stock
No implementation costs, immediate value (implement in one day, have results in a week, go live in a month)
Increased service levels
Key features for Oil & Chemicals organizations
Powerful, user-controlled AI to help planners understand the components of demand, not just the total demand
Extensive portfolio management with phase-in, phase-out, and AI-proposed demand ramp-up plans
Demand Sensing to improve forecasting in the short term