Minimising MOQs- Group Planning & Cycle Based Scheduling

In order to optimise production, procurement and to reduce the MOQs of items, many organisations have implemented group planning. Group planning also known as campaign planning is when the forecast for a grouping of products is combined to trigger a single larger MOQ. This could be grouped by a raw material, semi-finished goods or some other shared attribute.

Other organisations have implemented cycle based scheduling. This is when a production rhythm is defined and planned production is pushed back or pulled forward into the appropriate planning bucket. This is to support with the sharing of MOQs and semi-finished batches, also to allow production to be optimised by manufacturing similar products together to reduce changeovers.

Both of these are excellent initiatives help to increase FLOW by minimising the MOQ of a single item by producing it with items which share the same components or characteristics. The downside of these processes is that they are still driven by forecasting. What is not so clear to many is how DDMRP can still support and operate in this environment. This blog shares how DDMRP can be applied to group planning and cycle based scheduling by using a ‘virtual Min/Max’ buffer logic.

DDMRP Virtual Min / Max Example

The approach to managing both cycle based scheduling and group planning is the same in DDMRP. Let’s look at group planning and take an example of a procured item. (The methodology works exactly the same for items produced in-house)

In this example there are 3 sites that all use the same key ingredient, peanuts. The peanuts come from the same supplier, however each site requires delivery in different formats, e.g. One site receives 5kg bags, another 10kg bags, the third 25kg bags. The supplier has a MOQ for peanuts, how this MOQ is split between the different weights is not important to the supplier, but each delivery to site must be a minimum of 100kg.

Using DDMRP we would create buffers at each factory and a ‘virtual min / max’ buffer at the supplier.

Using the available stock equation at the factories, if factory C dips below top of yellow then a purchase order will be recommended (the quantity will be the difference between top of green and available stock, or 100kg whichever is greatest). This purchase order will be mapped against the ‘Min/Max’ buffer at the supplier and a new order will be generated (for 1000kg). The demand from the factories to the supplier would be mapped using a BOM explosion or a mapping logic to aggregate.

The next step is to decide what we should do with the production planned at the supplier (the purchase order from factory C will not be = 1000kg therefore there will be a remaining quantity). The best solution is to deploy the stock based on a priority dependant on the available stock position against the buffers. This is different to a fair-share logic which splits excess supply evenly against all demand location based purely on forecasted volume.

Deployment in DDMRP will first try to ensure all buffers are at top of red first. If not enough stock is available, then any items in the red zone will be planned to reach the same % of red zone for all factories.

Next, any buffers which have an available stock in the yellow zone would then be prioritised to increase stock to top of yellow. If not enough stock is available, then any items in the yellow zone will be planned to reach the same % of yellow zone for all factories.

Then any buffers which have an available stock in the green zone would then be prioritised to top of green. If not enough stock is available, then any items in the green zone will be planned to reach the same % of green zone for all factories.

Any remaining stock would be shared and will push the buffers over top of Green. The amount of stock over top of green will be an equal % for each buffer.

The aim of this is to ensure all buffers are at the same available stock % vs total buffer. This means the initial purchase order quantity generated at Plant C may be increased or decreased depending on the position of all the buffers.

In order for this method to work efficiently, careful consideration is needed on the sizing of the green zone for each buffer. The green zone would need to be set using the ‘cycle time’ method and should be the same for all buffer locations. This will ensure each buffer will be triggering demand at roughly the same frequency. This will help to prevent excess triggering of demand and thus over supply.

The individual MOQ for each site or bag size would still be respected when the stock is deployed from the supplier. The virtual ‘min/max’ buffer would be sized based on the MOQ of the supplier. When implementing cycle based scheduling the methodology is exactly the same, the key difference is the virtual buffer would be sized using the cycle time method. All other buffers would also be sized using the cycle time method for the same reasons as previously mentioned.

Simulations Modelling

Hopefully the above helps explain how cycle based scheduling and group planning can be delivered using the DDMRP methodology. Coming next, I will share my Excel simulation tool which will allow you to enter your own data and see how group planning / deployment can work for your products in a DDMRP environment.

I am always happy to share any insights from my personal experience implementing DDMRP, cycle based scheduling and group planning, across multiple factories and categories. Also do reach out if there are any questions.

Jonathon Vaiksaar, DDMRP Lead

**New Update: Simulation tool now avaliable!