Currently there are many disruptions in the supply chain worldwide. Purchasing managers say delivery times for manufacturers worldwide are deteriorate. Shipping a 40-foot container from Shanghai to New York has been $ 2,500 in 2019 and is now over $10’000. The chip shortage made it into the general news headlines. In earning calls this year, CEOs mentioned Supply Chain Glitches 412% more often than last year.
For supply planning, this means more costs, but especially a challenge to get enough supplies to keep production running. The word of the year has become “build a resilient supply chain”.
To just name 2 examples from clients:
- One of the largest consumer goods companies completely removed inventory as a KPI this year
- A pharmaceutical company now orders their supply 2 years in advance. They increased safety stocks and lead time buffers
Building all this resiliency leads to higher cost. But how high is this cost? A more concrete example: what is the effect on cash flow and costs of adding 2 weeks of buffer for supply deliveries? With today’s tools, simulating planning constraints to answer this simple question involves a lot of custom spreadsheet work by subject matter experts.
Simulate planning constraints
With GenLots you can now simulate planning constraints.
At the basis of GenLots is the calculation of an optimal supply plan given a large set of parameters. Our proprietary algorithm then respects all those parameters and creates a plan suggesting when to order how much supply for production, reducing costs in the process. The simulator is the logical extension, enabling the optimization of the parameters themselves.
The process consists of 3 simple steps:
- Select materials
- Select up to 20 different planning parameters to change
- GenLots calculates the supply plans for the original parameters and the scenario. You can then compare costs easily over the whole portfolio or material by material
Among the parameters are essentials such as service levels, safety stocks, Minimum Order Quantities.
A concrete example – 2 weeks of safety time
Let’s take the example question from the beginning, “What is the effect of adding 2 weeks of safety margins?”
In the new GenLots simulator, we selected 18 materials of our demo set and added 10 work days of safety time. Looking at the result:
Overall, the 2 additional weeks increase inventory by 15 % and cost $ 84’000 over a year. Scrolling down I can see that there is one material in particular which contributes most of the costs. Clicking on it, I see the plans with the original parameters and with the 2 weeks of added safety:
The supply plan doesn’t seem to change much, but It is actually a very expensive product representing $ 6.3M of spend. Increasing its inventory by 14% through a 2 week buffer will cause $30’000 of additional costs. So for the other 17 materials analyzed, I can add 2 weeks of safety time without worries, but this one I might check in more detail whether it is worth it.
This is one example of how to simulate planning constraints with GenLots. A sample of other questions it gets an answer to:
- What are my optimal safety stocks for a given service level?
- What is the effect of different minimum order quantities negotiated with suppliers on my inventory?
- How high are savings gained by faster goods reception processing?
Continuously self-improving master data
It has always been at the heart of GenLots to make hidden costs visible, then optimise them for improvement of service, cash and cost with our proprietary algorithms. Our next goal with the simulator is to automate, such that improved planning parameters are proactively proposed to the planner every day. This will enable planning systems, which are generally static and updated very rarely, to become a driver for efficiency.
