Forecasting with AI

Use artificial intelligence to improve business forecasting accuracy and efficiency

Learn how you can use AI for forecasting to unlock insights in your data and enhance your business performance and profitability.


What is forecasting?

Business forecasting harnesses the power of your historical data plus innumerable external factors to improve the accuracy and efficiency of the forecasting process.

Demand forecasting in the power industry

The key strategic challenge in the power generation industry is forecasting demand in order to match output with expected load. Many factors go into these forecasts, like weather, time of day, and fuel costs. Forecasting solutions are uniquely equipped to assess all inputs and provide better results than traditional approaches.

Resource cost forecasting for manufacturers

The primary drivers of manufacturing costs are labor, systems, and the cost of raw materials. Whether in CPG, refining, or any other industry, the ability to accurately and quickly forecast input costs directly affects the optimality of product pricing and ultimately the firm’s profitability.

Forecasting currency fluctuations in international fintech

Many fintech companies operate in multiple countries where there is great complexity in forecasting fluctuating currencies and exchange rates. Forecasting solutions keep financial managers ahead of these fast-moving changes and provide a competitive advantage in a landscape where transactions happen in seconds or less.

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    How does AI enable business forecasting?

    AI-enabled business forecasting—whether of costs, prices, customer churn, or currency movements—is a critical contributor to business success, particularly in industries characterized by thousands of quickly-changing external factors. Not only can AI-based forecasting deliver the accuracy your company needs by taking into account all of these factors, an AI-driven solution is also fully autonomous, continuously updating its projections as externalities change, positioning you to make better-informed strategic decisions.

    An important overarching challenge, regardless of your business type, is the ability to forecast growth in demand for your product/service. This directly affects your success in hiring suitable staff levels and planning advance orders for raw materials and other resource needs. Without the ability to forecast accurately and quickly, modern business has no chance of maintaining competitiveness or profitability. The accuracy delivered by AI-based business forecasting solutions offers early adopters a significant advantage over their competitors.

    Get more accurate results

    Traditional business forecasting is a bit of a black art, with some employing quantitative approaches while others prefer qualitative assessments of future trends. AI-based forecasting solutions eliminate the guesswork and subjectivity by analyzing all of the factors that affect your business, even those whose impact may not appear obvious at first.  


    Forecast faster and more efficiently with AI

    Traditional forecasting approaches rely on deep dives into historical data, followed by endless spreadsheet work and mathematical modeling, all of it based on the assumption that the initial inputs remain static, or at least predictable. AI-powered forecasting, by contrast, can incorporate thousands of inputsall of them constantly changingand deliver results without any labor-intensive processes. 

    Be more responsive to rapidly-changing inputs

    Predicting the future requires paying close attention to the past. But in modern business, much historical data performs in highly unpredictable ways. Only AI-driven solutions have the power to take these inconsistencies into account—extracting the signal from the noiseand provide highly reliable forecasts that business managers can count on to develop long-term strategies.

    Forecasting with AI solutions across industries

    Forecasting with AI in manufacturing

    Improve the accuracy and timeliness of your forecasting for both inputs and outputs in your high-volume product manufacturing business. Use AI-powered forecasting to ensure accurate alignment between raw material quantities and the products you manufacture.   

    • Drive down raw material prices and quantities (materials and resources).
    • Respond more quickly to customer demand.
    • Respond to market pricing trends.

    Forecasting with AI in oil and gas

    Improve your response to market swings in raw material costs and oil/gas/petrochemical product output demand and prices. 

    • Respond quickly to market price swings of finished oil and petrochemical products.
    • Reduce raw material costs (i.e., crude oil prices).
    • Understand and respond to natural gas price changes (driven by weather, politics, etc.)

    Forecasting with AI in power generation

    Enhance your agility in responding to market swings in fuel costs and power output demand and prices. Improve staffing accuracy and maintenance schedule efficiency by accurately forecasting when equipment will be in greatest demand.

    • Gain agility in responding to market pricing fluctuations.
    • Understand generation fuel costs more easily and quickly (coal, oil, gas, etc.)
    • Enhance visibility into current/future consumer and business power demand.

    How SparkCognition delivers AI-powered forecasting

    SparkCognition business forecasting with AI applies our patented machine learning (ML) algorithms to your existing historical data on sales, prices, costs, and exogenous factors to predict future values for these important inputs and outputs.

    Our AI-based business forecasting methodology is straightforward and effective, led throughout by SparkCognition AI and domain experts, with minimal time requirements from your staff.

    Step 1: Data ingestion

    To ingest and analyze your historical cost, price, load, and customer data, SparkCognition employs a number of powerful ML techniques. These are effective ways to handle large training sets with extensive sets of features. The models will then create forecast predictions quickly and automatically.

    Step 2: Training data

    After subjecting the data to quality validation and cleaning, deep learning models search for and identify trends in raw material costs, product prices, customer churn, or whichever other business quantities you’re working to forecast.

    Step 3: Model development

    Models are constructed based on local context for real-time forecasting and reporting. As additional data is ingested and analyzed over time, the solution adjusts future forecasts based on historical trends it has identified.

    Learn more about forecasting with AI

    Predicting financial market regimes with AI

    Discover ways in which AI can help to predict market volatility, price changes, and price change directions, giving asset managers a massive advantage over competitors, and increasing long-run stability in unpredictable conditions. Read our case study

    Leveraging AI in banking

    Learn how AI for forecasting helps banks and other financial institutions achieve competitive advantage by applying AI techniques to their historical pricing and performance data, enabling up-to-the-second agility in identifying and seizing market opportunities. Read our white paper

    Optimized energy trading with machine learning

    Learn how Increased accuracy of forecasts and exposure of key drivers of predictions enable companies to improve their bidding strategies, commercial offerings, and production schedules. Read our case study

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