Criticality assessments attempt to answer a deceptively difficult question: how vulnerable is a material’s availability, and why? A mineral may be concentrated in only a few countries, exposed to political instability, difficult to extract, rapidly increasing in demand or subject to environmental and social constraints. Existing methods therefore operate at several levels, including countries, companies and individual products. Some use only one or two indicators, which makes results easy to communicate but risks missing important causes of supply stress. Others incorporate many categories and generate a richer picture, but their results can become difficult for engineers, managers and non-specialists to interpret. ESSENZ, or the Integrated Method to Assess Resource Efficiency, was created to capture economic, environmental and social dimensions of abiotic resource use. Its breadth is also its central practical challenge: 18 separate, unweighted results can reveal complexity without making the next decision obvious.

The researchers developed QuintESSENZ by systematically testing which categories added distinctive and reliable information. The most detailed reduction focused on the ten socio-economic supply-risk categories in the updated ESSENZ+ framework. First, the team calculated pairwise Spearman rank correlations between material-specific characterization factors. These factors translate raw information—such as production shares, reserves, governance conditions or price volatility—into values representing potential constraints on availability. A correlation coefficient close to 1 means that two categories tend to rank materials in similar ways, although it does not prove that the real-world mechanisms behind them are causally linked. The analysis found a very strong relationship between concentration of reserves and concentration of production, with a coefficient of 0.93. Several other categories formed a broader cluster of strong correlations, including trade barriers and the occurrence of co-production. The statistical relationships were highly significant, with reported p-values far below the conventional 0.05 threshold.

Correlation alone was not enough to decide what should survive the reduction. Each category was also scored for the quality of its background data, its discriminatory power and its relevance in previous case studies. Data quality considered how much information came directly from original sources rather than approximation, how frequently the underlying datasets were updated and whether their origins and processing steps were transparent. Discriminatory power measured how effectively a category separated highly critical materials from less critical ones. For this analysis, a material was classified as highly critical when its characterization factor exceeded 20 percent of the maximum factor in that category. Across the 48 materials, the number of highly critical materials ranged from one to six. Case-study relevance was assessed by examining how often a category appeared among the three most important categories in existing ESSENZ or related SCARCE assessments. The researchers gave equal weight to the three scoring dimensions, producing total scores between five and eight.

The resulting selection was strikingly compact. Political instability received the highest overall score, eight, reflecting strong data quality and repeated importance in existing assessments. Concentration of reserves scored seven and was retained as the second socio-economic category. Concentration of production was discarded because it was very strongly correlated with concentration of reserves and received a lower total score. Trade barriers also scored seven, but its underlying data were judged less reliable because the World Economic Forum’s Enabling Trade Index contained substantial approximations and had not been updated since 2016. The other excluded categories captured risks that remain important but were not selected for the streamlined version: demand growth, feasibility of exploration projects, mining capacity, price fluctuation, primary material use and co-production. The decision means that QuintESSENZ focuses on governance-related disruption and dependence on the geographical distribution of known reserves, while leaving several market and extraction risks for a later, more detailed analysis.

The socio-economic reduction was only one part of the new framework. QuintESSENZ retains abiotic resource depletion as its measure of physical availability and keeps both compliance with social standards and compliance with environmental standards under societal acceptance. For environmental impact, the five ESSENZ+ categories—climate change, eutrophication, acidification, water scarcity and smog—are reduced to climate change alone. The researchers selected it because carbon-footprint analysis is widely recognized and commonly used as a single-issue environmental indicator. That simplification comes with a serious warning: a product could perform well on climate change while creating substantial impacts through water consumption, air pollution or nutrient enrichment. In life-cycle assessment, this is known as burden shifting, in which reducing one environmental impact inadvertently increases another. QuintESSENZ therefore contains six categories in total: abiotic resource depletion, political instability, concentration of reserves, climate change, compliance with social standards and compliance with environmental standards.

When the streamlined method was compared with full ESSENZ across the 48 materials, the broad pattern remained remarkably stable. Twelve materials occupied exactly the same position in both rankings, while 18 shifted by only one position. Five changed by two or three positions, and eight moved by four to eight positions. Materials previously identified as highly critical—including beryllium, gallium, germanium, indium, palladium, platinum and rhenium—remained near the top with changes of zero to two positions. Two exceptions, natural gas and sodium, were not flagged as critical by QuintESSENZ because their values for political instability and concentration of reserves were zero, even though other ESSENZ categories gave them non-zero values. Both nevertheless ranked relatively high in the full assessment, at third and seventh among the 48 materials, illustrating why the new tool can identify broad hotspots but cannot safely determine final sourcing or substitution decisions. In product inventories, the characterization factors are multiplied by the mass of each material, so differences between methods may become more pronounced when a product contains large quantities of a material.

The researchers tested how stable their conclusions were under different assumptions and historical datasets. When data quality, discriminatory power or case-study relevance was given a dominant 70 percent weighting, political instability remained the leading category. The second selection changed, however: concentration of reserves remained when data quality was prioritized, while trade barriers replaced it when discriminatory power or case-study relevance received the greatest weight. This result exposes a fundamental value judgment in any simplification exercise: a method optimized for reliable data may not choose the same indicators as one optimized to detect extreme differences or reflect previous applications. A second sensitivity analysis compared ESSENZ datasets from 2016, 2019 and 2024. Although correlations varied substantially for some pairs, concentration of reserves and concentration of production generally remained closely related, and political instability consistently ranked first. The authors conclude that the selected categories are reasonably robust, but recommend repeating the analysis whenever new data become available because supply risks and the quality of their indicators can change over time.

QuintESSENZ is intended for early-stage product design, rapid comparison of material options, internal prioritization and communication with non-experts. A manufacturer could use it to screen a portfolio and decide which components deserve a full supply-risk assessment; an engineer could compare preliminary designs before detailed sourcing information exists; and a management team could use its results to identify strategic questions without interpreting 18 separate outputs. But the method’s simplicity is inseparable from its limitations. It does not capture export restrictions through trade barriers, competition caused by demand growth, dependency on by-products, constraints on new mining projects, production concentration, price shocks, extraction capacity or reliance on primary materials. It also cannot evaluate company-specific suppliers, inventories, logistics or sourcing countries. The researchers warn against using it for supplier selection, contracts, definitive material substitutions, detailed supply-chain management, close quantitative comparisons or public claims that a material is generally low risk. QuintESSENZ is best understood as an alarm bell: useful for telling decision-makers where to look next, but not detailed enough to explain the entire emergency.