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Increase Your Part Risk Intelligence with the Power of AI-Supply Chain Risk Intelligence

Published On:

August 1, 2023

Updated On:

August 1, 2023
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Brian York
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Increase Your Part Risk Intelligence with the Power of AI-Supply Chain Risk Intelligence
Author
Brian York Chief Product Officer LevaData
Brian York

Chief Product Officer LevaData

Supply Chain Risk Intelligence with AI

The pandemic was perhaps the biggest wake-up call for direct materials sourcing teams. As supply and demand shocks reverberated through supply chains, teams scrambled to secure parts through whatever means necessary. Most of the time, they paid a premium and had to take extraordinary measures just to get what was needed.

What if more direct materials sourcing teams had access to part risk intelligence and supply chain risk intelligence platforms? They may have been able to better shield their companies from disruptive events. It’s just a matter of time before new supply chain shocks hit, and your process will be tested once again. But this time can be different.

Today, procurement professionals are still trying to manage and optimize their spend with disparate tools and disconnected market intelligence. This is exacerbated even more by the collaboration gap between engineering design and procurement execution. When addressed, this collaboration ultimately ensures the best part selection.

From sourcing from failing suppliers that impacts sourcing resiliency to dealing with unexpected cost fluctuations during market shifts, the way you manage part risk can have a big financial impact on your organization. That’s where part risk intelligence and supply chain risk intelligence platforms can help.

Supply chain risk intelligence platforms that tap into the power of AI to aggregate and contextualize your parts spend can concisely augment a global commodity manager’s ability to make the best sourcing decisions. That’s because advanced analytics make up the core of procurement platforms and provide actionable contextually blended insights.  

These insights are geared toward prioritizing value drivers and prioritizing parts that have the best spend and sourcing resilience opportunities. For example, sophisticated part risk intelligence platforms provide comprehensive qualitative insight and awareness, such as pricing transparency, to quickly compare current pricing against market pricing. With hundreds of data sources and billions of part data points, platform users can quickly understand the corresponding lead time, inventory trends, part age, sources, and even alternate sources—all from a single, comprehensive view.

Here's a deeper dive into some of the features that sophisticated AI-powered direct sourcing platforms can bring to your part risk intelligence strategy:

  • Lead time awareness – A lead time feature at the manufacturer part number (MPN) and part series level can provide insights into the base part source ability the MPN is built upon.
  • Monitor part age and years to end-of-life – Take a quick glimpse into how old or how long a part has been around versus its estimated time left before it reaches end-of-life.  
  • Procurement performance – Compare customer average percent discounts from best distributor prices to obtain a normalized benchmark perspective of purchasing power and negotiation leverage against the community and even set savings goals down to the MPN level.
  • Track supplier health – Assessing part risk also means evaluating the reliability and financial stability of suppliers. If one of your suppliers experiences financial stress or goes out of business, it can cause supply chain disruptions and production delays. AI-powered supply chain risk intelligence platforms can even suggest the best alternative suppliers.
  • Keep tabs on inventory – Understand how inventory levels are trending so you can make decisions about sourcing before sourcing constraints affect your business.

If you’re still relying on traditional tools to navigate part risk, it’s time to update your part risk intelligence strategy. By incorporating hundreds of data sources and contextualizing billions of part data points, direct materials sourcing platforms powered by AI provide real-time intelligence and insights you can’t possibly squeeze out of a spreadsheet.  

Many manufacturers have yet to make the leap to these AI-powered part risk intelligence platforms, so there’s a huge opportunity right now to get ahead of the competition in a very strategic way. An investment now will not only pay immediate dividends but will also set you up longer term to improve margins and add to top-and-bottom-line growth. Why wait?

Frequently Asked Questions (FAQs)

What is supply chain risk intelligence in the context of procurement?

Supply chain risk intelligence refers to the proactive identification, assessment, and management of potential risks within the supply chain, including supplier reliability, market changes, geopolitical issues, and natural disasters. In procurement, it involves gathering and analyzing data to anticipate disruptions, ensure a steady supply of goods, and minimize costs. Effective risk intelligence enables procurement teams to make informed decisions, adjust sourcing strategies, and maintain supply chain resilience.

How does AI improve supply chain risk intelligence?

AI enhances supply chain risk intelligence by analyzing vast amounts of data in real-time, identifying patterns, and predicting potential risks. It can monitor global news, weather patterns, political changes, and supplier performance to flag potential supply chain disruptions. By providing actionable insights, AI helps procurement teams make data-driven decisions, optimize sourcing strategies, and quickly respond to unexpected events, thus improving supply chain resilience and efficiency.

What types of risks can be identified with supply chain risk intelligence?

Supply chain risk intelligence can identify a range of risks, including supplier-related risks (e.g., financial instability, compliance issues), market risks (e.g., price fluctuations, demand changes), geopolitical risks (e.g., trade wars, sanctions), environmental risks (e.g., natural disasters, climate change), and logistical risks (e.g., transportation delays, labor strikes). Early detection of these risks enables procurement teams to take preventive measures and ensure business continuity.

How does AI-driven supply chain risk intelligence reduce supply chain disruptions?

AI-driven supply chain risk intelligence reduces disruptions by continuously monitoring and analyzing data from multiple sources. It can predict potential issues, such as supplier delays, market shifts, or geopolitical events, and provide early warnings. This enables procurement teams to adjust sourcing strategies, find alternative suppliers, or stock up on critical inventory, thereby minimizing the impact of disruptions and maintaining a smooth flow of goods.

Can AI-driven supply chain risk intelligence be customized for specific industries?

Yes, AI-driven supply chain risk intelligence can be tailored to the unique requirements of different industries. For example, in the automotive sector, it can focus on monitoring critical components' suppliers, while in the food industry, it might track agricultural conditions and regulatory compliance. AI models can be trained using industry-specific data, allowing procurement teams to address the most relevant risks and optimize their supply chain strategies accordingly.
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