Dear all
I am working on an inventory model in closed-loop supply chain system to optimize the cost of the system. There are lots of model to optimize the cost of the system, but I am looking forward to incorporate the concept of the Analytics to handle the real time inventory.
Looking forward to hearing from you.
with regards
Sumit Maheshwari
Please check the following:
https://www.riverlogic.com/blog/supply-chain-predictive-analytics-what-is-it-and-whos-doing-it
https://www.softwebsolutions.com/predictive-inventory-management.html
https://retalon.com/thought-leadership/predictive-analytics-transforms-inventory-management-in-retail
https://www.erpvar.com/blog/3-ways-to-decrease-your-inventory-cost-with-predictive-analytics
I would recommend using the PDE model for the supply chain system (re-entrant).
You can get acquainted with these models in my papers.
This is a challenging problem, specially for manufacturing companies, needless to say this problem is undergoing lots of research and practically there are no viable examples of companies that have achieved success, best cases have hit a 90% mark (but the metrics of such proclaimed achievements have been highly debatable). As inventory management is being driven by close to real time demand and supply data(analytics) plugged to AI and Machine Learning tools, the potential to reach close to 99% efficiency in CLSCM might become a reality -- but how do we identify and embed external disruptions like COVID19 into this model? and to what extent will these external disruptions impact CLSCM based inventory dynamics?
Hello,
I think that the best way to decrease inventory costs would be to give to supply chain a real collaborative role. For that, supply chain managers have to drive CPFR (Collaborative Planning Forecasting Replenishment) approach, with the goal to avoid bullwhip effects (by information sharing).
Do you see?
Bye
John
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