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EDITOR’S NOTE: I am under embargo regarding the advanced copy I received from ZIP with their Procurement Predictions for 2025. I have gone through the Procurement Insights archive of 2,410 posts from 2007 to today to provide what I believe will be a unique context explaining the evolution of predictions over the past couple of decades.
EDITOR’S NOTE: The following are the details for an upcoming Webinar on “Reinventing Procurement” that I will be attending. As the world enters a new era of economic volatility, technological disruption, and geopolitical instability, procurement is once again at the epicenter of change.
MODEL #1 An agent-based model (ABM) within a Metaprise framework offers several advantages over an equation-based intake and orchestration model in procurement: 1. Procurement Insights Equation-Based Models: Expanding these models often requires redefining equations and parameters, making scalability more challenging. Pitt Site 3.
EDITOR’S NOTE: The following is a reprint of the March 25th, 2015 article The Impact Of An M&A On The Procurement Department This morning I read a post by Roz Usheroff regarding the just announced merger between Kraft and Heinz, and how an employee can both survive and thrive when an M&A occurs.
Procurement Insights isnt just an opinion engine. Its the institutional memory of the procurement profession and the only advisor offering contextual guidance built from decades of archived intelligence. It fills critical gaps in depth, agility, and contextual insight that most traditional analysts and association models overlook.
Hansens Procurement Insights blog does not explicitly describe a “learning loopback process for self-learning algorithms” in the context of procurement or his Agent-based Metaprise model. 20072014), focus on decentralized, agent-based procurement frameworks rather than detailed algorithmic processes. kg margins).
Since May 2007, when the Procurement Insights blog published its first post, one post has consistently garnered attention. “ MODEL 2 ASSESSMENT Using Hansens theory, Ericsson could have identified and acted on critical strands from historical supplychain disruptions, potentially mirroring Nokias success.
Introduction Gardner, (1954) and Huntzinger, (2007) define Purchase price variance (PPV) as a metric used to measure the effectiveness of cost-saving efforts by calculating the difference between the planned cost (standard pricing) allocated for purchasing activities and the actual cost incurred.
Hansens agent-based Metaprise Model directly addresses the core concerns of Chief Procurement Officers (CPOs) by combining human-AI collaboration, real-time adaptability, and ecosystem-wide integration. Example: A global manufacturer unified JD Edwards, NetSuite, and IFS workflows using agents, reducing procurement cycle times by 35%.
With a decade hallmarked so far by constant disruption, consumers are more aware of supplychain and how industry shortages , the gender gap in supplychain, and climate events impact their daily lives and local communities. A term that once only resonated with industry insiders is everywhere.
As noted in previous posts, the Procurement Insights blog doesnt explicitly detail a learning loopback process for self-learning algorithms. However, past posts imply an iterative, adaptive mechanism within an Agent-based Metaprise model, where autonomous agents refine procurement decisions (e.g., cost predictions, supplier scoring).
Hansens Agent-based Metaprise model, as described in Procurement Insights posts (e.g., Mitchell, Spend Matters Chief Research Officer, is a recognized procurement expert who focuses on digital transformation, data analytics, and procurement technology, often emphasizing clean data and process efficiency (e.g.,
It automates procure-to-pay processes, reducing manual friction (PYMNTS, 2023). BillTrust) for P2P, lagging Ramps integrated procurement-to-AP suite (Venue, 2023). However, Ramps front-end procurement (intake forms) remains ahead; Nipendo focuses on back-end AP, not request capture. PO syncing, bill pay).
Editor’s Note: Since May 2007, I have written approximately five weekly posts on this blog – that’s a lot of writing. Given the findings, the myopic adherence to user adoption rate is at the heart of the growing disenchantment with Six Sigma, Lean and other similar-type programs.
1999 Revisited (Video) – Real Agents Leveraging AI GEP Autonomous Agentic AI Agents (High-Level Summary) GEP is set to revolutionize procurement and supplychain operations by introducing autonomous AI agents into the Source-to-Contract (S2C) and Procure-to-Pay (P2P) processes.
In my fall 2004 analyses of a study on the use of web-based applications I made the following observation: It is my position that a true centralization of procurement objectives requires a decentralized architecture that is based on the real-world operating attributes of all transactional stakeholders starting at the local or regional level.
” – Procurement Insights (2024) ERP Agent Swarms refer to the use of multiple autonomous, intelligent software agents working collaboratively within an Enterprise Resource Planning (ERP) system. Adaptability: Agents respond quickly to changing conditions, such as supplychain disruptions or sudden changes in demand.
Integrating my Agent-based Metaprise model with SAPs Joule, as outlined in Procurement Insights (e.g., This hybrid addresses the 2025 tariff challenges (10% baseline, 60% on China, Chinas 84% retaliation) impacting industries like cosmetics and coffee, offering a balance of agility and scalability. gradient descent).
In the third and final AI Gideon Gartner interview question, I ask the following using the RAM 4-Model Assessment Framework: Who is better aligned to serve the procurement industry’s and practitioners’ best interests: Eugene A. Gartner serves 14,000 enterprises globally, including procurement and supplychain leaders.
“What is most interesting about Zycus tremendous growth rate is that it is indicative of the evolution (some would even suggest fruition) of a trend first presented in a Procurement Insights post from August 31, 2007.Titled Scope : Broad and systemic, designed to improve entire procurement processes (e.g.,
1999 – I introduced the Metaprise model (RAM) 2007 – In Dangerous SupplyChain Myths (Part7) , I write about the Metaprise in greater detail, including the results of its implementation in a production environment (Department of National Defence). Hansen ( 4 ).
Hansens Agent-based Metaprise Relational-Agent Model (RAM) and its use of self-learning algorithms in a 2024 exchange on Procurement Insights [web:0]. Hansens Agent-based Metaprise model for its self-learning algorithms, human-AI synergy, and context-adaptive fluidity, as evidenced in his Procurement Insights comments [web:0].
Hansen (founder of Procurement Insights) to steward his original vision , he would almost certainly prefer Jon W. Hansen (Founder, Procurement Insights) Independent thought leadership Gartner Inc. Hansen (Founder, Procurement Insights) Independent thought leadership Gartner Inc. Hall (current CEO of Gartner Inc.)
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