Inventory Optimization Solution

KNIME Analytics Platform
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Dear KNIME Community,

I have read the success story titled “How Kärcher Reduced Inventory by 15% with KNIME While Enhancing Customer Service” on the KNIME website via this How Kärcher reduced inventory by 15% with KNIME while enhancing customer service | KNIME. I found the approach very impressive and believe it would be an ideal solution for my current problem.

I seek support to develop a similar solution and would greatly appreciate any assistance or guidance.

Thank you.

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Hey Didas, welcome (back) to the Forum :-).

I had a quick read through the success story - always impressive what you can make happen with KNIME :-).

Have to admit though to achieve something like this likely requires an individual project be set up inside your organisation to map out the value flow from customer order to production to warehousing to storage… identifying all the systems that create and hold data related to the different processes and working out how they relate to each other and depend on each other.

What is the specific problem you are trying to solve?

As a general idea to get you started I’d recommend to understand what data the system you are closest to is about, where does it come from (upstream processes/systems) and where does it go to next (downstream processes/systems).

The solution to generate the outcome as described in the success story likely involves a range of workflows that solve different parts of a large problem that was broken down into digestible pieces - wouldn’t be surprised if it also involves KNIME hub to avoid having to roll everything out to many locations in KAP - especially when reading from different systems and writing to central DBs may be involved…

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Hi @MartinDDDD,

Thank you for your insightful thoughts. While reading further, I came across a YouTube video where Antonina explained how she reduced her overstocking levels (https://www.youtube.com/watch?v=6TBCsnDMyHM&t=884s). Her approach aligns well with your suggestion of breaking the problem into smaller, manageable chunks.

I would like to connect with you on LinkedIn to discuss this further. Please let me know if you are open to it.

Thanks,
Didas

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Happy to connect and exchange on this topic.

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