Re-Imagining Inventory Optimization With Cognitive Technology

Re-Imagining Inventory Optimization With Cognitive Technology

Re-Imagining Inventory Optimization With Cognitive Technology Inventory optimization is a practice that has been in place for decades. Employees are constantly looking for new ways to work wherein they put in the minimum amount of effort while doing inventory without having an impact on the customer service. There is technology which can collect, index and harmonize various data points that exist in enterprise systems and all external data sources. It is possible to analyze data continuously to detect opportunities and risks to businesses. This way, inventory becomes an investment to any business because it provides accuracy and visibility of all data with software that also predicts the future and suggests the best course of action to optimize all investments.

Why is Inventory Optimization So Hard?

Companies need to make inventory for each material purchased, something that becomes extremely difficult if there is a large number of parts. The large volume forces companies to categorize materials and manage them at a group level. It becomes time consuming and tedious when done manually. The process can get automated with the right technology and the inventory speed can improve rapidly. The second problem is forecasting the supply in the future, based on only historical data. Companies cannot predict any drops that could cost them a lot of revenue.

Cognitive Technology and Inventory Optimization

Cognitive technology can increase the frequency at which inventory is taken. With cognitive technology, companies can detect the change and record the changes in patterns of either supply or demand more readily. When organizations accumulate data, cognitive technology can be a big help in predicting a change in the future. Another benefit to adapting cognitive technology for optimizing inventory is that it is not constrained by the sheer amount of data. With the help of this technology, companies can go through historical demand and supply data, all the inventory levels as well as service levels and back orders that took place over the span of a year or more. It can also check for the accuracy of past forecasts.

Key Takeaways:

  • New cognitive technologies are a big help when it comes to inventory optimization for companies
  • Previously, the forecasting of future demand and supply was not accurate and predictions were made on group-based assumptions
  • With cognitive technology, companies can go through past data accurately and improve the forecasts they make for the future

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