AI Demand Forecasting Use Cases

Sense changing market demand using Predactica’s advanced AI/ML forecasting

Forecast product demand at individual SKU, group & store level

Demand Forecasting is a critical process for any type of business, be it Retail, Manufacturing, Supply chain or Finance. By forecasting the demand for its product and service accurately, it helps in reducing the risk and make efficient financial decisions that impact profit margins, cash flow, staff, and resource allocation, and overall spend. Almost all business strategic plannings are done around demand forecasting.

Predactica Forecasting tool differentiators:

Both Statistical and advanced ML/AL based Forecasting methods
Extensive EDA and Preprocessing steps
Auto ML capability
No-code model development and inbuilt ML Ops
Cloud native with enterprise scale

Demand forecasting for manufacturing industries

As a manufacturer forecasting the demand for their line of products becomes quintessential. Homogenous goods or multiple manufacturing units, it helps manufacturers in improving their profitability. Not just that though! Knowing accurately what the demand for their product is can help manufacturers in the following ways and more.

Demand forecasting for retail, procurement, and dynamic pricing

Predicting customer demand is a cornerstone task for businesses that manage supplies and procurement. Another common application is predicting prices and rates for products and services that dynamically adjust prices depending on demand and revenue targets.

Energy Demand Forecasting

Energy demand forecasting provides the basis for making decisions in power system planning and operations. The complex energy consumption ecosystem is dependent on various factors such as environment, climate, and socio-economic situations customer live in. Also, with wholesale energy around, traders, producers and distributors need accurate energy demand forecasting to optimize their planning and operation. Using Predactica’s advanced neural network timeseries models one could accurately predict the seasonality, and other anomalies in consumption behaviors. Here are a few important business and operation metrics that can be optimized.

Forecasting use cases in healthcare

Time series analysis and forecasting became the key technique applied in healthcare to predict the spread of Covid-19. It can be used for disease transmission predictions, mortality ratios, the spread of epidemic, and more. Chronic conditions such as diabetes, cardio and oncology type of diseases require accurate forecasting in drug demand and pharmacy supply chain optimization to make the drugs and services available to the patients for better disease management and higher pharmacy ratings.

Anomaly detection for fraud detection, cyber security, and predictive maintenance

Anomaly detection is one of the common machine learning tasks that looks for outliers in the way data points are normally distributed. While it doesn’t necessarily have to be time series data, anomaly detection often goes hand in hand with it. Detecting anomalies in time series entails finding irregular spikes or valleys that significantly deviate from the way seasons and trends look.

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