The Impact of Gen AI on Direct Material Sourcing

Growing economic uncertainty has compelled businesses to transform the way they operate, especially with regard to processes that are vital to core operations.

Direct material sourcing is a case in point, with cost fluctuations, demand variability, supply uncertainties and increased focus on sustainability having a deep impact on the function.

As such, direct sourcing is complex as it involves procuring raw materials, components and finished goods from suppliers who may be in different regions. 

Prolonged supply chain disruptions have also put a lot of pressure on direct procurement, with critical material shortages threatening to impact production on several occasions in the recent past.

Lack of visibility into the supply chain ecosystem, associated costs, risks and market data has aggravated the issues arising from disruptions and market imbalances.

Many direct sourcing teams do not have access to digital tools needed to get end-to-end visibility and to meet the expanding portfolio of the function. This creates a disconnect between functional goals and day-to-day operations.

Without clear visibility into key data such as supplier risk and performance, forward pricing, market index impact, demand and available supply, teams struggle to make informed decisions, leading to delays and disruptions in the supply chain.

Poor communication and collaboration with supply chain partners also hampers the working of direct sourcing teams. This often creates confusion as there isn’t a single source of truth at any given time, with different stakeholders looking at different datasets. 

At the same time, there is relentless pressure on teams to keep costs in check.
“Procurement metrics have always been about cost management. The cost-centric procurement model, which undervalued supply security, resiliency and agility, has already severely impacted several companies,” Virat Venkataraman, director of consulting at GEP, said in a recent podcast.

How can teams effectively deal with multiple challenges and build a successful direct sourcing strategy? Which learnings can they apply from recent years to mitigate supply-related risks and stay prepared for potential disruptions in the future?

What Can a Direct Sourcing Solution Do?  

At the outset, direct sourcing teams need to quickly come up with a clear strategy to safeguard supplies as well as meet short and long-term objectives. They must adopt a holistic approach to balance their sourcing requirements, supplier network, cost risks and business growth requirements.

And technology should be a key part of their strategy, given the need to digitize processes and the rapid evolution of artificial intelligence (AI) and machine learning.

The need of the hour for direct sourcing is a unified source-to-pay procurement platform that boosts visibility and collaboration and provides category and market intelligence to align sourcing with strategic goals.

“Leaders need to have a solution that drives strategic sourcing with category and market intelligence at the same time,” says Venkataraman. 

A well-designed direct sourcing solution can help manage all types of sourcing events, incorporating bill of materials and cost drivers on a single platform that provides access to the latest specifications, contracts and supplier information.

Teams can leverage enhanced visibility and recommendations into spending patterns, product categories and supplier ecosystems to achieve a fine balance between supplier costs, risks, and business growth needs.

Real-time, multi-dimensional and multi-tier visibility leverages data from internal and external sources to have a comprehensive view of end-to-end processes from sourcing to purchasing. 

Additionally, visibility into market index-driven price updates enables direct sourcing teams to respond to market changes and collaborate with suppliers to conduct quick price updates or renegotiate contracts. 

Further, the platform’s should-cost modeling, cost breakdowns and ‘what-if’ scenario modeling can help optimize costs and understand cost and value drivers from product to component or category level.

Also read: Direct Material Sourcing in the Digital Age: How to Thrive

Generative AI is Set to Change Things 

The incorporation of AI is quickly transforming how direct procurement operates today, with advanced digital tools automating several manual, time-consuming tasks.

Routine functions such as supplier selection and onboarding, contract management, supplier performance management, inventory management and invoice processing have been simplified, thanks to AI-powered procurement software.

With AI taking care of transactional processes, sourcing and procurement teams can focus their efforts on driving enterprise-wide strategic value.

Rapid developments in Generative AI, which can generate unique content in the form of text, images, videos, code snippets and synthetic data, are set to further augment the capabilities of existing AI-based solutions. Along with creative content generation, it is suitable for quick analysis and innovative problem-solving. 

Where can this help direct sourcing specifically? 

To begin with, it can simplify supplier evaluation and selection, a key responsibility for direct sourcing professionals. By assessing multiple parameters such as location, historical performance, pricing, service capability and financial health, Generative AI can identify the most suitable suppliers for the business. 

Further, by deriving market intelligence and historically recorded transactions, it can compute real-time pricing benchmarks to drive supplier negotiations and best pricing strategies. 

Additionally, Generative AI can also automate document creation. It can create requisitions, purchase orders, invoices, RFXs as well as contracts. It can also create the desired type, format and template of these documents for different categories, suppliers and locations.

Supplier relationship management is another key application of generative AI technology for direct sourcing. It can use customized scorecards to periodically run performance evaluations. It can also detect anomalies in the information submitted and go beyond historical patterns to monitor risks associated with different suppliers on an ongoing basis.

Based on its understanding of the supplier landscape, category intelligence, regional nuances and organization-specific requirements, it can help teams identify cost-saving opportunities and enhance efficiency.

A Word of Caution  

While Generative AI can transform several processes within direct procurement, human intervention is still required to run end-to-end procurement operations, says a recent Everest Group and GEP report. 

There is a need for judgment in activities such as the creation of documents for requisitions, purchase orders, invoices, RFXs and contracts, all of which can be customized based on spend category, location and decision-making processes.      

Procurement teams need to exercise due diligence while using generative AI, especially for decision-making.

Convergence is the Need of the Hour  

In addition to technology deployment, direct sourcing must work closely with supply chain professionals to mitigate risks. 

Supply chain convergence, which involves the integration of multiple entities into a unified process that operates seamlessly, is the need of the hour. 

There is a need for procurement and supply chain teams to seamlessly work together to achieve the desired outcomes. 

By working collaboratively on direct material sourcing, teams can, for example, achieve cost savings by optimizing sourcing strategies, reducing inventory costs and improving supplier performance. 

This can also provide end-to-end visibility to track the movement of direct materials, boost quality standards, mitigate disruptions and hit joint business goals. Likewise, they can optimize workflows to improve decision-making and overall performance.

Here’s how GEP is helping procurement organizations leverage Generative AI.

Learn about GEP’s Direct Material Sourcing Software.