Focus and Leverage Part 153

This posting is the final posting in this series about replenishment systems comparing the Min/Max system to TOC’s Dynamic Replenishment.  I finished my last blog posting by listing four criteria that must be in place in order for TOC’s Dynamic Replenishment Model to work effectively.  The reality is that there are actually six criteria as follows:

 

1.    The system reorder amount needs to be based on daily or weekly usage and SKU lead time to replenish.

2.    The system needs to allow for multiple replenish orders, if required. 

3.    Orders are triggered based on buffer requirements, with   possible  daily actions, as  required. 

4.    All SKUs/inventory must be available when needed.

5.    SKU inventory is held at a higher level, preferably at central supply locations or coming directly from the supplier/vendor.

6.    SKU buffer determined by usage rate and replenish supplier lead time. Baseline buffer should be equal to 1.5.   If lead-time is 1 week, buffer is set at 1.5 weeks and then we can adjust the size as required, based on historical data.

 

The TOC Distribution and Replenishment Model tells us that we should hold most of the inventory at the highest level in our supply chain and not at the lowest level like the min/max system.  Yes, we still want inventory at our point of use, but not the majority of it.  One of the major consequences of the min/max system is the distribution of SKUs much too early especially when the same type of inventory or part is used in several locations such as different hospital wards or units.  It’s not uncommon to see, for the same SKU, an excess in one ward and a stock-out in another all because the inventory was pushed down through the supply chain.  This does not happen in the Dynamic Replenishment Model since stocks are pulled through the system based upon usage.

 

In Dynamic Replenishment we eliminate using the minimum target as a trigger to reorder and replace it with a system that monitors our safety buffer and usage on a daily or weekly basis and replenish only what has been used for that time period.  We also eliminate the min/max maximum order quantity in that we only order what has been consumed rather than some maximum level.  What we end up with by using Dynamic Replenishment is much lower inventory levels, in the right location, at the right time, with zero or minimal stock-outs.  In fact, using Dynamic Replenishment we not only virtually eliminate stock-outs, but we do so usually with 40-50% less inventory thus freeing up huge amounts of cash.

 

To further make this point, I want to use a very common example taken from Bruce Nelson and my book Epiphanized in Appendix 5.  In this scenario, Bruce tells us to consider a soda vending machine.  When the supplier (the soda vendor) opens the door on a vending machine, it is very easy to calculate the distribution of prod­ucts sold, or the point-of-use consumption. The soda person knows immediately which inventory has to be replaced and to what level to replace it. The soda person is holding the inventory at the next high­est level, which in on the soda truck, so it’s easy to make the required distribution when needed. He doesn’t leave six cases of soda when only twenty cans are needed. If he were to do that, when he got to the next vending machine he might have run out of the necessary soda because he made distribution too early at the last stop.

 

After complet­ing the required daily distribution to the vending machines, the soda person returns to the warehouse or distribution point to replenish the supply on the soda truck and get ready for the next day’s distribu­tion. When the warehouse makes distribution to the soda truck, they move up one level in the chain and replenish from their supplier. This type of system does require discipline to gain the most benefits. It assumes that regular and needed checks are taking place at the inven­tory locations to determine the replenishment needs. If these points are not checked on a regular basis, it is possible for the system to ex­perience stock-out situations.

 

Remember in back in Focus and Leverage Part 151 and how we demonstrated the effects of the Min/Max replenishment method with what you see in Figure 1.  What you see in Figure 1 are the results of a simulation run by Bruce Nelson using the following criteria (For details and actual data used please refer to Appendix 5 in Epiphanized):

 

1.    The maximum level is 90 items.

2.    The minimum reorder point is 20 items.

3.    The lead time to replenish this SKU from the vendor averag­es 4 weeks. The average is based on the fact that there are times when this SKU can be delivered faster (3 weeks) and other times it delivers slower (5 weeks).

4.    Usage of this SKU varies by week, but on average is equal to about 10 items per week.

Remember, using the Min/Max replenishment method we don’t reorder until we meet or exceed our minimum reorder quantity (i.e. 20 items left in stock).  In Figure 2 we are applying the Dynamic Replenishment Model rules to exactly the same criteria we set for Figure 1. Bruce used the same SKU simulation, and the same period of time, with the same usage numbers. The difference will be in this simulation he changed the rules to fit the TOC Distribution and Replenishment Model.  That is, reorder is based on usage amount and vendor lead time rather than minimum and maximum amount.

Figure 1

 

Let’s now look at this same scenario using Dynamic Replenishment to see what it might look like.

Figure 2

 In Figure 2 Bruce assumed the following:

1.    Maximum level is 90 items. (This is the start point for the current inventory when Dynamic Replenishment was initiated.)

2.    There is no minimum reorder point.  Instead reorder is based on usage and vendor lead time.

3.    Lead time to replenish is still 4 weeks. 

4.    Average usage of the part is about 10 per week.

 

There are several key points observed in Figure 2:

1.    What is most notable is that total inventory required through time has been virtually cut in half when compared to that of Figure 1.

 

2.    There are no stock-out situa­tions present.

3.    The total inventory is maintained within a very stable range over a long period of time.

Searching for SKUs and having to experience the negative impact of stock-outs are a constant problem in many hospital supply-chain systems. These problems aren’t caused by the logistics people, but are instead negative consequences of the supply-chain system and the manner by which it is used.  The concepts and methods associated with Dynamic Replenish­ment can and will positively impact the flow and availability of SKUs within a hospital setting.

Bob Sproull