Inventory optimisation – how much inventory should I hold?

Inventory optimisation – how much inventory should I hold

Inventory optimisation - how much inventory should I hold?

Inventory provides a necessary buffer in the supply chain to meet the expected demand for product, during the expected lead time to replenish. This is true at a raw material, component, and finished goods levels. The inventory held has a critical impact on customer service, warehouse and operational capacity and working capital requirements for the supply chain.

There are no prizes for having warehouses full of inventory that is not moving. 

In addition, few businesses can withstand the impact of constant service interruptions from inadequate inventory.

In our work, we come across many companies that either operate based on simple rules of x weeks inventory across product categories, or that execute faithfully against a forecast.

The challenge with the x weeks inventory approach is that it fails to take account of individual SKU demand and supply behaviours. Over time the ‘x’ is inflated to a level that reduces service level interruptions within the category, but the blended policy results in many products being over stocked.
 
Faithfully executing to a forecast, translates a frequently 50% – 60% accurate forecast into a 100% inventory commitment. This results in a combination of over-stocking for certain SKUs and a constant scramble within the supply chain to expedite for under forecasted items.
 
 
Many companies are now working with statistical replenishment models, that directly link individual SKU demand and supply behaviour, to targeted customer service levels. Key elements within this approach include;
 
  1. Categorising individual SKU demand behaviours in a framework that expresses variability in time and demand. This is used to determine the appropriate inventory control method.
  2. Mapping supplier lead times and variability in those lead times 
  3. Determining service level requirements by SKU to manage to a targeted level of inventory availability 
  4. Incorporating forecast, seasonality, promotional and lifecycle information
  5. Selecting a planning model – periodic review or continuous review
  6. Developing a replenishment process that provides a first pass recommendation on re-order points, order up to levels and safety stock linked to actual demand and inventory levels
  7.  Applying planner judgement that brings additional intelligence to the process driven recommendations

 

This data driven, process led approach, provides a scalable mechanism to target inventory investments to meet service goals.  It also provides with the tools and the time, to add real value to the process.  Connect with us to learn more about this approach.

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