Demand Forecasting

Go beyond traditional forecasting and use machine learning technology.

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What it is

  • Demand Forecasting app is a great to to predict future demand for multiple articles based on historical data.
  • We train machine learning algorithms based on historical data to extract patterns and trends – no deep analytical background required.

What it delivers

  • Easy access to sophisticated forecasting technology.
  • Higher accuracy than with traditional forecasting techniques.
  • Integration of domain specific know-how and external data sources (weather, promotions etc.) in customized apps possible.

What are the benefits

  • Improved forecasting accuracy by machine learning techniques.
  • Cost savings through better reource utilization and avoiding over-capacities.
  • Increased operational efficiency in Supply Chain

What is Predictive Analytics?

Predictive Analytics is the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends. Predictive analytics does not tell you what will happen in the future. It forecasts what might happen in the future with an acceptable level of reliability.

In the Demand Forecasting App, we train a neuronal network to extract these trends and patterns form your historical data points. The result of the training process is a fitted model that will be used to predict future demand.

Why is Demand Forecasting important?

In Demand Forecasting, we use data and analytics to predict future customer demand for a specific period as precisely as possible. Accurate Demand Forecasting is important to satisfy customers, minimize inventory costs and optimize cash flow.

Customer Satisfaction

 

Minimize Inventory Costs

 

Optimize Cash Flow

 

Customer Satisfaction

Meeting customer expectations for product availability is primary in Demand Forecasting. If you underestimate or fail to provide the amount of inventory your customers want, you risk losing them to competitors. You could even lose a previously loyal customer for the long term by consistently failing to deliver.

Minimize Inventory Costs

When you accurately forecast demand, you only need space and people to manage the inventory your customers want in the short term. In contrast, poorly projected inventory levels leads to a number of related costs, including:

  • Extra space: The more inventory you hold, the more building space you need to hold it. This problem is especially problematic for retailers that emphasize sales turnover per square footage. Your utilities expenses are also typically higher.
  • Extra people: The more excess, the more people you need to move it and manage it.
  • Waste: Throwing out perished items or obsolete inventory, or marking it down to clear it out, are among the other wastes that result from poor demand forecasting.

Optimize Cash Flow

Accurate demand forecasting has a significant impact on your efficient use of working capital and preservation of cash flow. If you buy too much inventory to meet current demand, you expend cash that you could put to better uses until demand picks up. Instead, your cash is tied up paying for inventory that sits in a storage room. Being hamstrung on cash flow stresses your company’s ability to make debt payments and inhibits your investments in growth and development.

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