The DDMRP* method was invented by Carol Ptak and Chad Smith in 2011. I participated in the first European training session of the DDMRP in May 2013 given by Carol Ptak in Paris. I am therefore a CDDP (Certified Demand Driven Professional) from the very beginning.
I was impressed at first sight by what Ms. Ptak’s had built, but it took me some time and experience to understand how DDMRP could add value:
- By positioning inventory buffers strategically to mitigate risk
- Thanks to a simple and visual management of inventory levels and replenishments to be made. It gives back control to planners over their stocks and helps to reduce crisis.
The DDMRP revolution changed the statu quo: going beyond the ERP’s recommendations and statis safety stock calculations and actually plan for replenishments. As Ms. Ptak said, it was about stopping the “precisely wrong” way of doing things based on the MRP calculation of safety stocks and supply, amplifying the “bullwhip “* effects of the chain (shortages and overstocks).
The DDMRP was a real step forward for Supply Chain Management and the DDMRP philosophy greatly inspired the design and principles behind Flowlity. Indeed, we are using the same core principles such as :
- Planning in between visual boundaries (we have the equivalent of red, yellow, green zones)
- Using something close to Daily Usage (Consumption) instead of MRP outputs to compute requirements
- Dynamically adjusting buffers to cover changing risks
However, today I have come to the conclusion that 2011 DDMRP is obsolete and will be replaced by a 2.0. version (as we do at Flowlity) for three main reasons:
- DDMRP’s buffer calculation is quite static and based on black-box parameterization (the coefficients that vary with variability and lead times are arbitrary). Even with a feedback loop, it is still arbitrary and requires a process to be maintained. With Flowlity, we compute our buffers (min-max) dynamically based on AI algorithms that consistently get better and adapt to specific customer use cases.
- DDMRP Average Daily Usage (ADU) is too slow to react to disruptions because it is just a snapshot of the past days. At Flowlity, we do consumption sensing (the equivalent of ADU forecast) using AI, which reacts way faster in times of crisis and to changing conditions.
- DDMRP is not outside-in (as Lora Cecere is defining it). It does not solve the problem of synchronization with the extended Supply Chain (your direct suppliers and customers). Inventory problems are related to the bullwhip effect that is induced by the influence of the external links in the supply chain. It is like a traffic jam! And you don’t solve traffic jams by just having a better car. Even though, the DDMRP is positioning DDAE III as the ultimate goal (see screenshot below), there is no clue in the methodology about how to achieve it. Here, DDMRP will have the same issues as control towers (a vision without a way to execute it). Flowlity is solving this by being a trusted 3rd party : we synchronize different companies without the need for them to share data directly.
DDMRP will be shortly brought to the next level with a solution like Flowlity. It uses artificial intelligence to dynamically and continuously adapt the parameters and quantify the risks for all products and all situations. It also allows extended synchronization of the chain by being a trusted third party.
So let me present you the future of Supply Chain Planning : Flowlity! Our simulations showed a significant improvement in performance compared to DDMRP. On raw materials or finished products, Flowlity needs 30% less inventory than DDMRP and decreases shortages (especially in the situation where Flowlity acts as a third party between two companies). And the sweetest thing is that it is even simpler to setup than a DDMRP 1.0. implementation.
You use DDMRP and want to benchmark your approach with Flowlity? Then contact us and let’s have some fun!
DDMRP : Demand Driven Material Requirements Planning
DDAE : Demand Driven Adaptive Model
Bullwhip: Bullwhip in the supply chain means that a disruption at one point in the chain is amplified by spreading upstream or downstream causing overstocking and disruptions (see article here).
By Jean-Baptiste Clouard