How-to: reduce inventory with safety lead-times (part 2)

Part 2 with Excel simulation on how to reduce inventory with safety lead-times

If you haven’t read ‘Part 1: how to reduce inventory with safety lead-times’ it is a short analogy on how electronic board production is like organizing a meeting between Elon Musk and 9 young new interns. Please read if you have any difficulties to understand or even to explain to colleagues why safety lead-times are mandatory in reducing inventory globally.

In part 2, here is  a simple Excel simulation to capture how efficient it can be.

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Overview: reduce inventory

Here are the results of the simulation:

Security lead time simulation

Now, let’s take a deep dive into the file 🙂

Hypothesis: safety lead-times

Here is a real, classic example of a Bill Of Material (BOM)  with 390 components, 131 articles, for a value of $66.68.

As usual, 50% of the cheapest articles only make up a few percent of the value:

Security lead time simulation

We’ve then created a simple law of probability for a component shipment to be delayed:

Security lead time simulation

And have run 15 simulations with/without safety lead-times:reduce inventory simulation

Results

A new simulation is launched every time you open the file, thus changing the results. But you can see that safety lead-times have — on average — a positive output by actually decreasing your inventory:

Safety lead-time simulation

Of course this simulation is a really simple example. Risk of shortage should not be the same for all the components. Optimized safety lead-times do not have to be of 30 days. But the goal here was to easily grab the interest of safety lead-times.

What you would need to take the analysis one step further:

  • calculate a law of probability article by article (taking into account last communicated manufacturer lead-times, last market available inventories, alternative manufacturing part number availabilities, mpn commodity status, mpn life cycle status, etc…)
  • describe BOM by BOM what is to be optimized (inventory? on time production?)
  • calculate BOM by BOM the optimized number of safety days for each article (for example, you can randomly choose safety lead-times and run simulations to calculate their efficiency, then do it again and again and again to keep the best random selection 🙂

Now, it’s your turn to play! No matter the complexity and accuracy of your calculation method, you’ll see very tangible results. And don’t forget the Elon Musk metaphor to convince your company!

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