Push or pull supply chain, what about be demand driven ?

Today’s Supply Chain managers must define their supply chain strategies regarding multiple methodologies available. But it’s not black and white! You can’t be completely PULL with a spread product mix. Supply chain push, pull or demand driven ?

What about finding the hybrid solution and have a demand driven supply chain?

Thanks to our R&D team we have concrete results with multiple simulations done.

The dilemma between PULL and PUSH supply chain

Everybody knows about Manufacturing Resource Planning (MRPII); created in the 1970s, it is the most widespread planning method in the world.

This methodology plans the manufacturing activities of a company based on demand forecasts: it is what we call a “push flow method”. MRPII is built on multiple processes from strategic to operational levels, from business planning to capacity requirements planning.
However, markets have drastically evolved for the last 30 years, with a highly instable demand from customer, resulting in high nervousness through all Supply Chains; this is the famous “bullwhip effect”.

We found an interessant article about the Bullwhip , here https://fortune.com/2021/10/20/supply-chain-shortages-covid-christmas-presents-company-earnings/

To solve this problematic, industrials tried to move from a “push flow” method to a “pull flow method” such as Kanban or ConWIP (Constant Work in Process).

Push, Kanban or Conwip modelling - Supply chain Push pull or driven by the demand
Push, Kanban or Conwip modelling

To get more information about Kanban : http://supplychain-mechanic.com/?p=316

Since 2011, another promising method has appeared: Demand-Driven MRP. This methodology aims at positioning and dimensioning inventory/time buffers to lower variability sources in the Supply Chains.

Supply Chain simulations’ results between the 3 methodologies

But is it truly more efficient than the Push system ?

The case study is based on Kanban serious game from the “Centre International de la Pédagogie d’Entreprise“ (CIPE). A Discrete-Event Simulation (DES) approach is retained to get predictive results.

The simulation will process different scenarios and show the impact of MRPII strategy vs DDMRP strategy, regarding On-Time Delivery (OTD) and Working Capital (WC, valuation of Work in Process and stocks).

Several sources of variabilities are combined: internal (instability of operating times and setups) and external (spike demand and seasonality of demand).
The case study represents a company producing reducers made of three parts. The goal is first to achieve 100% of OTD (minimum of 99,3%), then to minimize the Working Capital.

5 scenarios have been tested as follow:

5 scenarios - Supply chain Push pull or driven by the demand
Supply Chain’s simulation scenarios parameters

The following table shows the results between MRPII strategy (Push) and DDMRP strategy (Hybrid, Push/pull methodology).

The reference scenario is Scenario 1 with Push policy, set as base 100 for the Working Capital (WC) .

The objective of customer satisfaction (On time Delivery/OTD) is nearly always satisfied with Hybrid policy. Push also reaches satisfactory OTD levels for all scenarios except when demand variability becomes too high (Sc5).

Furthermore, it can be clearly seen that DDMRP requires less Working Capital to achieve the OTD objective.

Moreover, it has been demonstrated that DDMRP is highly stable when facing variabilities, unlike MRPII.

If your Supply Chain is facing variability, the hybrid model will be the optimal solution for tomorrow’s Supply Chain

Therefore, the case study demonstrates that DDMRP is fully effective in regulating the system variability.
On top of that, it has been showed that the stocks distribution is better with DDMRP; stocks are centered on the optimal stock level, unlike MRPII were stock distribution is bimodal: either too much or too low.

To get more information about Simulation and Supply Chain solutions ; https://www.agilea.us/our-services

Push or Pull Supply Chain, what about to be Demand Driven?

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