How to fix your overflowing stock situation?

Part 1.

Challenge at hand.

Over the years, I’ve worked with automotive companies, scale-ups, and heavy industry players in various supply chain roles — from raw material planning and customer service to finished goods planning and ultimately leading global operations across 30 countries.

One thing I’ve learned? Stock optimization challenges may appear different on the surface, but the core principles remain remarkably similar. With the right perspective, a solid understanding of the business, and strong cross-functional collaboration, the right solutions are often within reach

Stock reduction, optimization or whatever other term we want to call it, comes down to, few common points. Some of them will be dependent of the size of the organization, some will be unified regardless of it.

1.      Reduction of stock

• Short term- contain the AS-IS situation
• Mid and long term- Stabilized situation in planning and capacity

2.      Unification of portfolio

• Reduction of customer specific items
• Stabilized situation in planning and capacity
• Clarity on the customer offer vs supply performance

Stock initiatives are usually driven from top to bottom, so I would propose we will start the other way around with the plant/ storage point of view and gradually build upwards.

First priorities to consider is to contain the situation (Point 1.1)- make sure we are not increasing the stock further especially on high value/ slow movers- to do ASAP. It is very important but don’t loose your head. Cutting AX and U classified items will bring a quick drop in stock but most probably will take you just a step away from disaster- out of stock. Be careful!

We need to execute with care and a structured approach.

The starting point should be the gathering of the data. Obvious step but very crucial as the result will heavily depend on the data quality. My assumption at this point is that you do not have a tool to support you directly with stock evaluation or maybe you have but you are not sure if the results are true.        

Data and classifications

So, what would be needed from data side?

Now, the next prerequisite would be building on the above data following classifications:

ABC classification based on pieces of goods sold. This is my go-to definition as the more traditional approach, based on the cost per unit or revenue can be misleading. This is tightly dependent on your company.         

To give you an example where simply the cost focused calculation didn’t work for me:

A screw we used in thousands that costed 1 cent per pcs but was essential for all products vs a rarely used aftermarket electric engine that single unit cost exceeded 20k EUR.

The pure PCS calculation also has it drawbacks where again you can have a screw that is used in thousands but is a part of a more seasonal product and a pipe made from copper that is installed in every single item you produce.

That’s why I say you need to pick the right definition of your ABC based on the stock you intend to use it on.

What ever is your final choice, the general recommendation is to follow the 80/20 approach where 20% of PCS sold make up for 80% of movements done.

XYZ for all individual storage point based on the standard ratios: X: 0-25%; Y: 25-50% and Z: 50%+ respectively.        

XYZ is used to capture the variability of the demand for the selected group of items where X is your most stable in demand item and Z is the one with highest variability

UVW per individual storage point that allows to sort your materials based on their process.        

Following a bit altered pareto: U top 20% of prices, V following 40% and W remaining 40% of the price

If you are looking for a good solution in SAP, I highly encourage to visit their Help portal:

Classification 2 tab | SAP Help Portal

But it is a link I highly recommend visiting also for non-SAP approaches as the principles there are well explained and apply to other solutions as well.

Before we jump further, why do we need all this data and calculations? It’s to ensure that we build a basis for a solution that is:        

• sustainable
• time efficient
• no negative impact on our customers both internal and external
• transparent stock situation across the globe
• KPIs set for a global benchmark

What should we be aware of?        

• Hitting the AXU/V/W group will bring a quick win, but carries a huge risk of damage towards the customer
• Addressing the CZU/V/W groups would be the perfect solution but potentially time-consuming.
• Stock optimization is a precision-based exercise
• Doing a top-down instead of bottom-up