Using Data

Most inventory optimisation tools require extensive, complex and highly accurate data to achieve even a marginally better solution than an existing demand satisfaction inventory planning method.

Inventory Optimisation uniquely recognises that the complexity and quality of data is in reality a significant challenge for most organisations, however sophisticated they are in other respects.

The IO solution therefore has been developed to work with simple data, and the realities of variable or poor quality of data that most organisations and businesses suffer from.

The IO solution delivers an optimal inventory solution even when data quality is poor or inconsistent, or limited in its scope.

Red Cube software

IO has developed a powerful software tool to analyse inventory demand data and optimise an inventory solution in a wide range of market sectors, from defence and commercial aviation through to manufacturers and consumer goods.

Red Cube analyses and measures the cost-risk profile of every single part within an inventory, embracing the universal truths of inventory optimisation that:

      • Demand for parts = Risk
      • Delay in sourcing parts = Risk
      • Demand x Delay = ‘Pipeline’ – the measure of overall Inventory Risk
      • Cost = Preference – the inevitable choice that must be made about which parts to buy given limited financial resources to minimise Inventory Risk.

Using powerful, unique algorithms developed from years of knowledge and testing in real environments, Red Cube delivers a truly optimal solution for inventory planners that focuses on reducing the risks in inventory planning.

The result is a reduction in the investment required to deliver a desired level of performance, and crucially a significant reduction in the shortages that impact operational performance and reliability.

The Cost-Weighted Back-Order Method

Red Cube analysis and ongoing outputs enable Inventory Planners and Managers to move from a reliance on old-fashioned demand satisfaction to the Cost-Weighted Back-Order approach.

The flaw with demand satisfaction methods is that the impact of shortage when a demand is not satisfied (known as Dues-out or Back-Orders) is not properly addressed. Minimising Back-Orders by reference to their actual cost-risk provides a truly optimum result.

Based on a 3-dimenisional and 4-dimensional analysis from Red Cube inventory planners are able to focus procurement and replenishment on the items that are most likely to impact operational availability if a back order were to occur. As a result back orders are minimised whilst operational performance is improved. In other words, an optimum inventory mix is both achieved and maintained.

The IO Cost-Weighted Back-Order® algorithms have proved so effective at delivering improved inventory performance that Inventory Optimisation Ltd are able to contractually guarantee results. Paige uses report as a rallying cry to fix term paper writing help teacher ed

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