Supplier Relationship Management (SRM) is critical yet frequently neglected in procurement.
Despite its strategic importance, SRM often becomes the lowest priority for procurement teams, resulting in significant missed opportunities and unexploited value from contracts.
This neglect can cost organisations dearly in terms of both financial performance and operational effectiveness, as discussed with Moundir Khenfous, Director of Indirect Procurement at CAE, in the below episode of Procurement Reimagined.
Moundir clearly identifies this common oversight: procurement teams spend considerable effort negotiating contracts but often fall short when it comes to effectively managing supplier relationships post-negotiation.
As Moundir emphasises, All of the hard work that went into negotiating a contract, the tears, sweat and blood, are not maximised because you lack the SRM capability.
Why SRM is Traditionally Neglected
Several reasons contribute to the traditional neglect of SRM, including:
- Reactive workload: Procurement teams are frequently pulled into reactive tasks and urgent demands, leaving little room for proactive management.
- Resource constraints: Many procurement teams operate with limited resources, making strategic SRM activities difficult to prioritise.
- Lack of visibility: Insufficient visibility into contracts and data prevents proactive engagement and management of supplier relationships.
Transforming SRM with AI Capabilities
AI technology is uniquely positioned to address these challenges by automating the time-consuming, repetitive tasks that often hinder strategic procurement activities.
According to Moundir, AI capabilities like data summarisation and automated insight generation offer immense potential to elevate SRM significantly.
Key AI capabilities include:
- Data Summarisation: AI can rapidly condense vast amounts of contract data and documentation into actionable insights, saving procurement teams hours of manual review.
- Automated Insight Generation: AI proactively identifies critical opportunities and risks within contracts, enabling procurement teams to act strategically rather than reactively.
- Task Automation: AI handles administrative tasks, freeing procurement professionals to focus more on strategic relationship building and value-added activities.
Practical Use Cases of AI in SRM
Moundir provides insightful examples of how AI can practically transform SRM, including:
- Contract Commitment Management: AI proactively monitors contracts and alerts teams when commitments are at risk of being exceeded, suggesting early renegotiations. For instance, halfway through a contract cycle, AI could advise,
You are about to exceed your minimum commitment. You should consider early negotiation.
- Proactive Utilisation of Contract Provisions: AI ensures teams leverage key contractual provisions. For example, if a procurement team negotiates a valuable swap-right mechanism, AI can prompt them to use it before it becomes obsolete, avoiding unnecessary expenditure on unused assets or licenses.
- Contract Value Maximisation: AI continually assesses and identifies under-utilised contract elements or potential improvements, thus preventing valuable agreements from becoming shelfware.
Elevating SRM from Reactive to Proactive
By adopting AI-driven SRM solutions, procurement teams transition from a reactive posture to a highly proactive and strategic approach. Moundir emphasises, Imagine AI taking care of the legwork, such as crunching the numbers and summarising documentation, allowing you to focus on strategic insights.
With AI handling the heavy lifting, procurement professionals can fully engage in high-value tasks such as strategic supplier relationship management, ultimately extracting greater value and performance from their supplier contracts.
Conclusion
Integrating AI into SRM is not merely about technological innovation; it's about fundamentally reshaping procurement's role within organisations. Procurement teams empowered by AI can ensure contracts consistently deliver their intended value, enhancing operational efficiency and strategic outcomes.
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