The Bullwhip Effect !!
Had a great day, Thursday of last week attending the #SCLHUB2024 event in London. Joining 100 senior Supply Chain professionals to discuss varying subjects from the capture and digitisation of the vast varieties of data, to optimising Planning tool outputs and the impactful exploitation of AI/ML.
The most common theme however was the overwhelming need to harness and surface in one unified harmonised and normalised view, complete real time end to end visibility of the entire Supply Chain. Customers, Retailers, Manufacturers, Suppliers, 3PL, 4PL et al.
It was discussed how the absence of the above is the main contributor to The Bullwhip Effect.
Exacerbated by ongoing Wars, Global financial reaction to political uncertainty and the growingly frequent extreme weather conditions, Supply Chains around the World are being ever increasingly violently whipped causing extreme difficulties for all.
Demand anticipation error, whether it is found to be over or under estimated, leads to amplified volatility the further upstream in the Supply Chain you are. From Customer to Retailers, to Manufacturers to Suppliers, the impact experienced increases exponentially.
In order to dampen the amplitude of the Whip and to minimise this volatility, demand sensing must be greatly improved, returning superior forecast accuracy and fulfilment optimisation KPIs.
This is, of course, achieved by moving to working with constrained plans versus unconstrained plans. By ensuring the base data is fully comprehensive, constantly updated, normalised and harmonised, we enable the realisation of the ROI promised when investing in today’s complex Planning Tools.
But how do we achieve this in practice?
Well InterSystems Supply Chain Orchestrator™ (https://lnkd.in/ewAPCVrC) is uniquely positioned enabling the ability to ingest and analyse masses of disparate data from multiple sources in real time, digitising, harmonising, normalising all data giving a complete end to end Supply Chain Data Fabric.
Additionally, with embedded intelligent processes and real time data analytics, there exists the option to apply AI/Machine Learning to further optimise Supply / Demand Plans - collecting both, historical demand and supply plan data produced by IBPs as well as input from regular manual adjustments (e.g. spreadsheets), to produce prescriptive insights for better forecast planning.
This all results in elimination of manually adjusted plans, greatly improved Supply and Demand forecasting accuracy, optimised inventory allocation and inventory fulfilment, giving near perfect OTIF order fulfilment, multi-point improved OSA and using AI / ML affords the Ultimate Control Tower with prescriptive insights.
