Deep Dive

Supplier sourcing insight solutions may leverage AI to provide AI-enabled purchasing analysis, contract analysis and relationship risk scoring to support sourcing decisions. This capability is particularly useful for purchasing in categories where suppliers are not directly managed under a quality assurance agreement (for these, see Supplier Performance Optimization) but are essential for running your supply chain, for example, secondary packaging materials, personal protective equipment, and some engineering spare parts.

Comprehensive data integration

By combining AI with supplier contracts and purchasing data, a range of new capabilities are unlocked. With HASH, in addition to ingesting structured data, information from "unstructured" sources can also be gathered and integrated with the assistance of Large Language Models. For example, information shared by suppliers, distributors, and other partners in private communications (emails/calls), or competitive and macro intelligence gathered from public sources such as radio transmissions, published news reports, and social media.

Predictive & prescriptive analytics

Machine-learning models layer on top of collected data can be used to forecast demand swings, delivery time variance, or material quality, and then prescribe the best mitigation. Next-generation solutions provide not only a descriptive overview of current data, but actionable recommendations to adjust plans before disruptions occur.

Implementation & Enhancement

Selecting A Solution

When building out and utilizing Supplier Sourcing Insights, it is important to consider:

• Data quality & latency: real-time integration, master-data governance, streaming ETL – requirements to ensuring data is up-to-date.
• Change management: upskilling procurement and supply managers in their usage – start by rolling out Supplier Sourcing Insight solutions as copilots to humans before relying on them in any autonomous capacity.
• Cybersecurity: ensure the system supports granular permissions and access controls consistent with your business requirements, and any partner access (e.g., via portals) is similarly secure.
• Ongoing maintenance costs: does the solution run in the cloud, or must it be hosted internally/on-premises and maintained manually?
• Open-source: is the Supplier Sourcing Insights solution open-source, or is there risk of platform/vendor lock-in?
• Incremental adoption: can the solution be used to target specific use-cases initially to prove its value and deliver quick wins (e.g., high-spend or poorly performing suppliers) before broader roll-out?

Roadmap To Value

A typical Supplier Sourcing Insights built on HASH looks like:

1. Baseline & cleanse data: connect key ERPs, supplier portals and specify any unstructured data sources of interest.
2. Launch visibility layer: real-time event dashboards, basic ML alerts.
3. Add predictive & prescriptive apps: purchasing and supplier contract insights, proscriptive recommendations etc.
4. Continuously learn: reinforce models with new data; driving a culture of decision-intelligence through an "OODA loop".