When the world becomes more complex, a little nuance doesn’t hurt… A binary approach doesn’t usually solve problems.
This adage also applies to the planning of our supply chains.
Our management systems, by definition, are binary – running on computers more at ease with zeros and ones, true/false, than with progressive, nuanced gradation.
The material requirement calculation logic of our ERP systems – whether for distribution or production – goes hand in hand with this principle. The calculated requirement is expressed as a quantity for a date. You need to replenish 10,000 by March 3. If this is respected, it’s good – if not, it’s bad.
If you can’t replenish 10,000, but only 7,500, is that enough to keep the flow going?
If you restock between February 27 and March 7, will it be OK? What is the relative level of risk?
The Theory of Constraints and Demand Driven approaches help to add nuance and help us to make decisions according to gradations.
In real life, it’s often a case of dealing with relative priorities.
I have a means of production whose capacity is finite. What is the most important product I should produce on this equipment today? How long should I produce it before moving on to the next most important product?
I need to restock a container from a supplier. What assortment of items should I include in this container, according to their relative priorities?
I don’t have enough stock of an item. How can I best allocate this stock to satisfy my customers?
I’ve got a queue in front of this means of production, which work order is best to go through first?
I don’t have enough cash or capacity to invest in optimal stock levels. How can I adjust my stock levels accordingly?
By formalizing Demand Driven inventory buffers, time, or capacity buffers – we make these decisions routine, based on a gradation of relative priorities. We are guided by the percentage of buffer consumption. In a queue, there’s no ambiguity: process the reds first, then the yellows – according to their percentage.
In distribution network replenishment, ditto. The same logic applies to filling trucks, loading production equipment… and even to the financial decisions involved in S&OP (Sales & Operations Planning) arbitration.
In today’s digital age, we need to introduce a bit of analog – potentiometers for our planners to adjust and maintain the flow.
However, for this logic to be effective, it is often necessary to question some technical data or planning parameters. Continuous adjustment, with nuances, requires a sufficiently high frequency of adaptation, for incremental decisions.
This may mean replenishing by parcel rather than by full pallet, daily production orders rather than monthly campaigns, questioning fixed horizons, mixed containers rather than full container loads of a single item, and so on. In short, building agility into our models…
