**In global supply chains**: In 2025, procurement is shifting from low-cost sourcing to strategic cost transparency and value optimisation. Techniques like should-cost modelling and value analysis, supported by AI, are driving more insightful supplier collaboration and predictive decision-making for resilient, cost-effective operations.
In 2025, procurement leaders are increasingly shifting away from traditional cost-cutting approaches towards adopting strategic methodologies centred on cost transparency and value optimisation. This evolving perspective marks a move beyond the pursuit of the lowest prices, emphasising instead the need for greater visibility and control over the total cost of ownership in supply chains.
Key tools driving this transformation include value analysis and should-cost modelling. These techniques allow organisations to scrutinise supplier pricing and product specifications critically, uncover hidden cost-saving opportunities, and make decisions that enhance long-term operational performance and value creation. The pandemic and persistent inflationary pressures have been significant catalysts for this change, exposing the limitations of the old low-cost sourcing paradigm and encouraging a reassessment of what constitutes true value in procurement.
Value analysis, for example, involves evaluating components and processes through a cost-versus-performance lens. Procurement teams are asking pointed questions such as whether a component is unnecessarily over-engineered, if packaging can be altered without compromising protection, or whether generic parts could replace branded ones without negative consequences. This approach helps reduce costs without sacrificing product reliability, safety, or sustainability.
ESCATEC, a manufacturing and supply chain specialist, serves as a notable case. During the COVID-19 pandemic, ESCATEC played a pivotal role in scaling production of cold chain data loggers essential for Pfizer’s vaccine distribution efforts. By supporting the production of second-generation temperature-monitoring devices under intense logistical demands, ESCATEC helped ensure product reliability. At its peak, its automated facility manufactured 170,000 units per month for Controlant, whose cold chain-as-a-service technology contributed to a reported 99.99% delivery success rate for billions of vaccines worldwide.
Data underpins the effectiveness of value analysis strategies. Procurement professionals are increasingly relying on should-cost models rather than supplier quotes or historical costs. Should-cost modelling builds fact-based cost estimates by analysing labour, materials, logistics, and overhead expenses, providing a robust basis for price validation, negotiation, and internal decision-making.
Artificial intelligence (AI) is playing a growing role in enhancing these efforts. Large enterprises use AI tools to analyse thousands of products, identify cost-saving opportunities previously overlooked, and gain detailed insights into cost drivers. Cross-functional collaboration supports a holistic view that informs supplier negotiations and operational improvements. An illustrative example is American Airlines, which utilised should-cost modelling to refine bids for full-truckload transportation services linked to its $1 billion inventory. By developing detailed cost structures for each shipping route, the airline was able to negotiate more accurately and mitigate a previous 200% variance in bids across approximately 500 annual requests for quotes.
In 2025, procurement decisions are viewed within a broader, integrated context through scenario planning, combining should-cost modelling and value analysis to understand downstream impacts fully. The conversation is shifting from solely considering “how much does it cost?” to examining “what are we getting for the cost and where is waste occurring?” This broader perspective positions suppliers as collaborative partners in continuous improvement rather than mere cost centres. Early supplier engagement, transparent sharing of cost models, and joint exploration of material or process changes often produce more favourable outcomes than adversarial negotiations.
Procurement leaders are also mindful of balancing cost-saving efforts against potential risks. For instance, a marginal reduction in cost that increases product return rates by 5% could negate savings through warranty claims and damage to brand reputation. Strategic decision-making involves assessing short-term savings alongside possible long-term erosion of value, requiring both analytical rigour and operational experience.
Leading organisations are now adopting predictive costing and design-to-value modelling powered by AI. These advanced tools analyse historical spending, supply chain behaviour, and real-time market data to forecast cost trends, detect anomalies, and propose optimised product designs. Automated sourcing events triggered by AI can respond rapidly to market changes, enabling procurement teams to act pre-emptively and strategically.
Overall, should-cost modelling and value analysis are cementing their roles as fundamental elements of contemporary procurement strategies. With the integration of AI and predictive analytics, procurement functions evolve into proactive, insight-driven operations that influence product design, supplier collaboration, and market strategies. This approach is fostering supply chains that are not only more cost-effective but also more resilient and aligned with organisational goals. The SupplyChain publication is reporting on these emerging trends shaping procurement leadership in 2025.
Source: Noah Wire Services
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