RED CUBE

RED CUBE

Red Cube is a step-change in inventory optimisation tools. It delivers significantly better results than comparable “Optimisation” tools or traditional inventory management methods.


THE COST-WEIGHTED BACK-ORDER® ALGORITHM

The multi-dimensional, Cost-Weight Back-Order algorithm delivers more improvement in inventory performance than any other step in the of inventory optimisation process. By using logic, not magic, the recommended level of inventory is typically 50% less by value and 50% more by quantity than the levels recommended by existing stock control software. It is the differentiator in optimisation.

Red Cube uses a three-dimensional approach to the analysis of historical inventory demand data to produce a unique insight into the cost-risk profile of all parts and components within an inventory. Delivering the results of this Pareto analysis in a 3-dimensional way enables inventory managers to make inventory investment, procurement and supply decisions that are truly optimal.

The 3-D’s analysed by the Red Cube software are:

Demand (consumption)

Dollar (cost)

Delay (lead time)

A fourth dimension, Deviation, can also be factored in to ensure that volatility of demand and variance over time will be captured and reflected in results.

Using Inventory Optimisation’s proprietary Cost-Weighted Back-Order algorithms Red Cube identifies the small percentage of critical parts that account for the greater majority of cost-risk in an inventory. Once this ‘red cube’ of critical inventory is identified, and subsequent ‘yellow cubes’ and ‘green foundations’ supply chain managers can make optimal decisions about inventory investment, stocks held, procurement and supply.

 

Pareto

 

 

 

 

 

 

Red Cube has been thoroughly tested in a range of applications in the defence sector, and is proven to deliver outstanding results for clients. The software is already in use with a number of major defence and aerospace clients Worldwide.

The IO Performance Guarantee: Inventory Optimisation is confident in the results that will be achieved for clients implementing Red Cube to optimise their inventories. Inventory Optimisation guarantees a 300% return on investment within 18 months of implementation.

Red Cube features and benefits

Minimal data required

The minimum data required by the GIODE Cost-Weighted Back-Order® algorithm is: Price, Lead-time (Purchase and/or Repair) and Demand (either historic or forecast). Or, to put it another way the 3 ‘D’s: Dollar, Delay and Demand. Unlike other solutions Red Cube does not require complex data or extensive variables to deliver meaningful insight and analysis. This saves organisations time and money, and also ensures results are delivered quickly.

 Evaluate Existing Performance

To establish the current position (or baseline) against which future improvements are measured, a Demand Emulator in Red Cube calculates the performance of existing inventory against current demand and quantifies the extent of improvement achievable by Inventory Optimisation. This detailed evaluation builds confidence, quantifies the projected ROI and supports the business case for implementation.

 Conduct a Pareto Analysis to identify the “Red Cube”

In a range of inventory, a tiny minority of, so called “Red” items are responsible for the vast majority of total cost-risk.  The GIODE Red Cube® multi-dimensional Pareto analysis identifies these few very high cost-risk items, which comprise the “Red Cube”, so that they can be suitably managed.

 Manage the “Red Cube”

Once the “Red Cube” high cost-risk items are identified they may be subjected to special measures. The GIODE software’s trade-off function enables managers to determine the most cost-effective strategy by calculating the merits of Supply-Chain and/or item reliability changes for each item. The software’s Demand Simulation function then tests the validity and impact of proposed changes.

 Calculate the optimum inventory level

Once the data is updated with the revised strategy for the high cost-risk “Red Cube” items, GIODE proprietary Cost-Weighted Back-Order® algorithm calculates the optimum inventory level for every item including a procurement list.  The process is repeated each order interval; typically monthly.

 Measure Performance

After the baseline has been established, and inventory optimisation implemented, the performance of the inventory is reviewed at, typically monthly, order intervals and the improvements recorded to measure the Return on Investment and so prove the guaranteed improvement is achieved.

 

The Cost-Weighted Back-Order Algorithm

The Red Cube Cost-Weighted Back-Order® algorithm comprises of highly sophisticated proprietary mathematical calculations (unique to IO) developed and refined over years of research, and evaluated during external validation, pilot studies and field trials. In short, it is proven.

As its name suggests, the Cost-Weighted Back-Order algorithm assigns a specific weighting to each item in the range proportionate to its cost, risk of stock-out (Back-Order) and demand/supply volatility (variance).  The concept of this highly sophisticated algorithm is surprisingly simple to explain visually.

 

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The diagram above illustrates how stock levels depend on the multi-dimensional impact of Dollar, Delay, Demand (and Deviation). Items which are costly, have low demand and short lead-times may not be held, especially if the demand and re-supply patterns are highly predictable. Other items, which are inexpensive with very large and erratic demand levels and lead-times, are likely to be held in significant quantity. Costly items with very large and erratic demand levels and lead-times are identified as being in the “Red Cube” during Pareto analysis and subjected to special measures (as previously described) to reduce risk prior to calculating their optimum stock level using the revised strategies. The highly asymmetric results of this process are counter-intuitive with very high levels of stock held of some items and little (or no) stock held of others.  This reflects the results of the Pareto analysis which demonstrates how the requirement is also highly-asymmetric.

The multi-dimensional, Cost-Weighted Back-Order algorithm delivers more improvement in inventory performance than any other factor in the inventory optimisation process.  By using logic, not magic, the recommended level of inventory is typically 50% less by value and 50% more by quantity than the levels recommended by existing stock control software.

It is the differentiator and game-changer in inventory optimisation.

CWBO vs DemSat

 

 

 

 

 

 

 

An example of results achieved in one defence study using the Cost-Weighted Back-Order algorithm.

CASE STUDY
In 2009 the UK Defence Support Group initiated a physical trial on a range of Seddon Atkinson truck stock, to compare the performance of Giode Red Cube® with their existing inventory planning tools. The physical trial used existing data, forecasts and default lead-times for equal comparison of existing tools versus Giode Red Cube.
After the first 6 months of the trial:
• The measured availability of the fleet of trucks Increased.
• The measured Demand Satisfaction Service Level Increased.
• The number of items “Due-Out” for outstanding demands Reduced – by 93%!
• The Inventory value Reduced.

After 12 months of the trial,
• The Measured Availability of the fleet of trucks was Increased.
• The Measured Demand Satisfaction Service Level was Increased.
• The number of outstanding Demands had Reduced – by 66%
• The number of items “Due-Out” for outstanding demands Reduced – by 96%!
• The Inventory value was Reduced – by 12.5%.

By the end of 18 month trial:
• The Measured Availability of the fleet of trucks was still Increased.
• The Measured Demand Satisfaction was still Increased.
• The number of items “Due-Out” for outstanding demands still Reduced – by over 95%!
• The Inventory value had Reduced – by over 20%.

Further Case Studies