Plastics Manufacturer Tackles the Ultra Competitive Procurement Marketplace with Arkestro’s Predictive Models
Industry:
Manufacturing
%
savings in first event with incumbent supplier
saved on commodity resins bid
“I was apprehensive at first of trying predictive procurement. But when I saw how easy it was for our suppliers and how fast it created a business impact, going predictive with Arkestro became a no-brainer.”
— VP, Chief Supply Chain Executive at a Global Plastics Manufacturer
The Challenge
Streamlining sourcing stressors
The global plastics manufacturer molds hundreds of millions of parts at multiple US locations per year that requires tens of millions of pounds of different plastic resins. Sourcing for specific products to make their proprietary blends was costly and slow. They needed to streamline their procurement process – quickly.
Immediate supplier savings
Within 72 hours, the company saw an 18% savings with an incumbent supplier who had previously assured that, “I am giving you my best price.” Arkestro ingested internal company data leveraging Arkestro’s machine learning capabilities and predictive models to simulate the supplier’s quotes before even reaching out to the supplier. They were no longer asking for a quote but suggesting an offer to their suppliers.
Overview
This case study focuses on a global contract manufacturing company who primarily molds plastic parts on demand for more than 250 different companies. Over the past 5 years, they have built an impressive platform through the acquisition of over 15 companies and has seen significant organic growth through their global customers base.
The series of acquisitions made it a challenge to integrate different datasets that weren’t fully accurate or updated to the current state. While this data wasn’t the best quality – there was a lot of it – which meant really important insights were difficult to uncover and even when found, often too late.
Approach
Once the Chief Supply Chain Executive introduced the concept of PPO to his CIO and showed that there was no software to install or learn, his team was on board. The team was impressed with how highly intuitive Arkestro was, and how they didn’t have to dig through a dashboard or pull up pivot tables to know if they were getting the right quoted price from the best supplier.
“With PPO, we easily accessed and enriched internal historical data with Arkestro’s predictive models and then augmented these simulations using external real-time market data. Its artificial intelligence and machine learning capabilities allow the platform to learn from the new data and resulting analytics, ensuring the most current and precise information.”
Result
Arkestro has helped to strengthen the company’s relationships with suppliers and eliminated quote fatigue by allowing decisions to be made in a fraction of the time. Suppliers also appreciate being told how far they are from the leading offer, this transparency means they can better target their offers on the parts of the business they are most interested in.
“As the process tracks toward an optimal commercial outcome, our procurement team gets notified with recommendations for award allocation that takes into account the holistic nature of the supplier relationship, commercial history, and even factors like supplier risk and operational performance. What was remarkable to us was that in Arkestro, this process typically takes days, not weeks or months”
Conclusion
With the impressive results experienced thus far, the Chief Supply Chain Executive is excited for the future. He estimates that the company is only using one quarter of the capabilities of PPO, and is focused on greatly expanding the use of the platform across all operations.
“PPO allows our company to get the best pricing from preferred suppliers on favorable terms more frequently. That’s a great value proposition from my vantage point.”
FAQs
Plastics Manufacturing
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What is the main challenge faced by the plastics manufacturer in the procurement marketplace?
The main challenge faced by the plastics manufacturer is navigating the ultra-competitive procurement marketplace. This includes managing supplier relationships, optimizing costs, and ensuring timely delivery of materials.
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How does Arkestro help the plastics manufacturer tackle these challenges?
Arkestro aids the plastics manufacturer by utilizing predictive models to enhance procurement processes. This technology allows for better decision-making, cost savings, and improved supplier performance.
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What are predictive models, and how do they work in procurement?
Predictive models use historical data, machine learning algorithms, and statistical techniques to forecast future events and trends. In procurement, they help predict pricing trends, supplier reliability, and demand fluctuations, enabling more informed purchasing decisions.
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What specific benefits has the plastics manufacturer experienced using Arkestro's predictive models?
The plastics manufacturer has experienced significant benefits, including reduced procurement costs, enhanced supplier negotiation power, and improved overall efficiency in the procurement process.
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Can Arkestro's predictive models be customized for different industries?
Yes, Arkestro’s predictive models are highly adaptable and can be customized to meet the unique needs of various industries beyond plastics manufacturing. This flexibility allows businesses in diverse sectors to optimize their procurement strategies.
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How does Arkestro ensure the accuracy of its predictive models?
Arkestro ensures the accuracy of its predictive models through continuous data updates, machine learning refinement, and validation processes. By incorporating the latest market data and trends, Arkestro maintains high model accuracy.
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What kind of data does Arkestro's predictive model use?
Arkestro’s predictive models use a combination of historical procurement data, market trends, supplier performance metrics, and other relevant data points to generate accurate predictions.
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How quickly can a company see results after implementing Arkestro's predictive models?
Companies can start seeing measurable results within a few months of implementing Arkestro’s predictive models. The timeline can vary based on the complexity of the procurement processes and the volume of data.
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Is it difficult to integrate Arkestro's predictive models into existing procurement systems?
Integrating Arkestro’s predictive models into existing procurement systems is designed to be seamless and straightforward. Arkestro offers support and guidance throughout the integration process to ensure minimal disruption and maximum efficiency.
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How does Arkestro's solution impact supplier relationships?
Arkestro’s solution positively impacts supplier relationships by providing more accurate forecasts and insights, which lead to better negotiation outcomes and stronger, more reliable supplier partnerships.
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What makes Arkestro's approach to procurement unique compared to traditional methods?
Arkestro’s approach to procurement is unique because it leverages advanced predictive analytics and machine learning to proactively manage procurement activities. This contrasts with traditional methods that often rely on reactive strategies and manual processes.
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How can I learn more about Arkestro's predictive models and their application in my industry?
To learn more about Arkestro’s predictive models and how they can be applied to your industry, visit Arkestro’s website or contact their sales team for a personalized consultation.