The main insights behind Make-to-Availability

Covering narrower area than make-to-stock or manage stock

I have seen too many big mistakes in make-to-availability implementations, especially when availability should not have been offered in the first place. Other mistakes show misunderstanding of the key insights. I wish first to verbalize the main insights, according to my understanding, behind the methodology called ‘replenishment.’ Then, in a subsequent post, discuss the boundaries of the currently known TOC solution for ‘make-to-availability.’

Eli Goldratt coined the term ‘make-to-availability’ to characterize an environment where a promise is made to potential clients that whenever they need the specific items they find it at the specific warehouse. Goldratt thought that by offering stable availability the organization would win much more demand, possibly also for higher price.

Every ‘make-to-stock’ or ‘purchase-to-stock’ is about managing uncertainty. While ‘make-to-availability’ is certainty ‘make-to-stock’ not every time stock is produced or purchased the intent is to provide excellent availability.  Sometimes the message is actually the opposite: “The stock will soon be gone!!!”  The idea of ‘Sales’ is based on the message of scarcity, pushing the client to buy now.

Insight 1 of the TOC solution to managing stock (even when availability is not offered):

We can never perfectly align our stock with the actual demand

This insight immediately leads to recognize the fact that either we have surplus or we face unanswered demand! Question is: what is more damaging – shortages or surplus stock?  Most of the time, but not always, we better hold just a little more rather than disappoint the market.  When a commitment for availability is given, there is no doubt that we have chosen to hold more stock than the average demand, but, not too much.

There are two different sources of uncertainty in managing stock:  the uncertainty of the demand and the uncertainty of the supply.  The common forecasting methods look only at the demand.  The problematic characteristic of any forecast is that the forecasting error grows sharply with the horizon. Recognizing the combined effect of demand and supply and the wish to offer excellent availability leads to the next insight.

Insight 2:

The relevant horizon for assessing the appropriate stock is the lead-time from consumption until replenishment

This insight means we should NOT look for longer horizon forecasts, because the supply has the flexibility to react properly to any change in the demand.

Given the horizon dictated by the supply lead-time – how much stock we need to maintain to ensure excellent availability? The on-hand stock protects the immediate demand.  The stock on-the-way, meaning the open replenishment orders, covers the rest of the time of the horizon.  If that stock yields excellent protection we should keep it constant.  This practically means:

Insight 3:

Any consumption of stock is immediately replenished – not more and not less

In this way the stock in the system, both on-hand and on the way, is kept constant. As long as the stock seems to do the job: keeping excellent availability, while keeping stock that is not in clear excess, there is no need to change the buffer.

Buffer management adds additional capabilities to ensure availability by providing priorities in the execution phase. This ability is critical mainly for manufacturing.

Insight 4:

The state of the on-hand stock relative to the buffer indicates the criticality of the specific replenishment orders

Actually this is a quite revolutionary idea. The common practice is to assign a due-date to the replenishment order and judge the priority of the order accordingly.  However, in managing stock the due-date is artificial as no one really needs all the quantity at any specific future date, and sales during the lead-time could vary and by that impact the priorities.  Thus, instead of assigning dates the buffer management algorithm looks for the actual state of the on-hand stock and bases the priorities of the replenishment orders accordingly.

Buffer management enables another key capability – a new kind of forecasting to get a warning when the stock buffer is too small, unable to ensure excellent availability, or too large, having too much stock. This is an expansion of the former insight.

Insight 5:

The behavior of the on-hand stock can be used to forecast the combined impact of demand and supply that determine the effective stock that ensures excellent availability

The resulting methodology called Dynamic-Buffer-Management (DBM) is based on the above insight and recommends increase or decrease of stock buffers. I call it “forecast” because it predicts the future based on the past.  It is a different sort of forecasting because it looks at the combination of demand and supply and guides the amount of required stock.

Another important insight is to look for the most effective points for holding the stock.

Insight 6:

The main stocks should be held at a central location to reduce the overall level of uncertainty

The direct result is holding less stock for the same level of availability. This insight is relevant both for the distribution channels as well as for those production shop-floors that face common intermediate parts used for different end items. Holding stock of intermediate parts could reduce the response to the demand and reduce the amount of stock in the system.

Warning: While centralizing the stock required at various locations reduces the overall uncertainty, the total impact of that reduction is often exaggerated.  The centralized stock damps the local fluctuations, but it does NOT damp the fluctuations caused by global causes.  For instance, local taste varies with the location, but a change in the economy impacts the demand all over the place.

Next post would deal with the boundaries of the TOC solution for make-to-availability.