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Construction companies can make supplier choices more consistent and defensible by defining project-specific criteria, comparing suppliers against reliable performance and purchasing records, and documenting how the evidence shaped the decision. Data can inform judgment; it does not replace the need to assess project context. The claim that construction has literally “always” chosen suppliers by gut is not established by the available historical evidence, so the headline is best read as a provocation, not a fact.
Why make supplier selection more explicit?
A supplier that offers the lowest price may not represent the best fit if its capacity, quality, delivery record, or ability to meet project requirements creates other costs or risks. Price still matters, but buyers can consider it alongside other criteria tied to the project’s goals.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11In the UK, RLB’s Procurement Trends 2026 survey reports that four in ten clients do not use value-selection criteria. The report also says use of those criteria dropped by 7% in the public sector; it does not establish that this is a percentage-point change. These are survey findings, not evidence that analytics caused a change or that the same pattern applies in other countries. RLB, Procurement Trends 2026
Explicit criteria help buyers explain why one bid suits a particular project, make comparisons more repeatable, and give future reviews something concrete to assess. The goal is not to make every project use the same formula; it is to make the reasoning visible and appropriate to the work.
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What evidence can buyers use?
Project requirements and bid information
Start with what the project needs rather than with a generic definition of a good supplier. Depending on the work, relevant criteria might include capability for the required scope, quality, delivery reliability, available capacity, commercial fit, sustainability requirements, or resilience. This is a practical set of possible criteria, not a universal standard prescribed by the studies.
Performance and purchasing records
Useful evidence may include delivery records, quality or performance assessments, purchasing transactions, and documented project outcomes. Aalto University researcher Abdollah Noorizadeh’s 2021 doctoral work examined supplier performance evaluations and purchasing transaction data from Finnish construction projects covering 2010–2016. It explored data envelopment analysis (DEA) and ways to combine it with recency, frequency, and monetary value (RFM) concepts when considering supplier-development investment. The dataset period is historical and Finnish; it should not be treated as a current or globally representative industry benchmark. Aalto University, Supplier evaluation and development in construction: data-driven analyses
Limits of the records
A record is only useful for a decision when it is sufficiently complete, relevant, recent, and comparable. A supplier’s performance on different work, under different site conditions, or several years earlier may not predict its fit for the current project. Where evidence is missing or incomparable, flag that limitation rather than treating a score as more certain than its inputs.
How to build a defensible supplier-selection process
- Define project-specific criteria before comparing bids. Identify which requirements matter for this scope and what evidence could show whether each supplier meets them.
- Set and explain the weights. Decide how much each criterion matters relative to the others, and record why those priorities fit this project. Do not choose weights simply because a spreadsheet makes them easy to enter.
- Use observable evidence and mark its limits. Compare bids and suppliers using relevant performance assessments, transactions, and documented outcomes. Note missing, stale, or non-comparable information for human review.
- Apply judgment where the data cannot settle the issue. Consider changing project conditions and risks that are not adequately represented in historic records. Keep a clear account of how those considerations affected the decision.
- Review performance after award. Record outcomes against the criteria used at selection. Use that record to improve future decisions and, where appropriate, supplier-development choices.
A 2012 case study by Fernando Schramm and Danielle Costa Morais describes a construction-company decision model based on SMARTER (Simple Multi-Attribute Rating Technique Exploiting Ranking). It included explicit strategic policies and a post-selection evaluation procedure. The case shows one way to structure a decision; it does not establish that every construction company or market needs that specific method. Schramm and Morais, Decision support model for selecting and evaluating suppliers in the construction industry
How the approaches differ
| Approach | Transparency and repeatability | Fit with project priorities | Evidence and adaptability | Effort and capability |
|---|---|---|---|---|
| Informal judgment | Can be difficult to explain or repeat if the reasons are not recorded. | Can account for context, but priorities may remain implicit. | May draw on experience; conclusions can be hard to compare without documented evidence. | Requires little formal infrastructure, but depends on people retaining and communicating relevant knowledge. |
| Explicit multi-criteria scoring | Makes criteria and relative priorities visible when they are recorded. | Can be tailored to a particular project. | Depends on evidence behind each score and on whether conditions have changed. | Requires time to define criteria, weights, and consistent scoring; a named technique such as SMARTER is one option, not a requirement. |
| Data-supported monitoring or analytics | Can make performance patterns easier to review when inputs and methods are documented. | Needs context-aware interpretation to reflect different projects and conditions. | Depends on sufficient, high-quality, comparable data; older or incomplete records weaken conclusions. | May require digital systems and analytical capability that are not available to every firm. |
This is a practical comparison of trade-offs, not a measured head-to-head ranking. The Czech construction-sector study by Tomáš Hanák and Iva Nekardová found differences between main contractors and subcontractors in supplier-selection criteria and reported that performance measurement was not universal in the sector studied. Its web-questionnaire findings apply to the Czech context and should not be generalized to all firms or countries. Hanák and Nekardová, Selecting and Evaluating Suppliers in the Czech Construction Sector
Where analytics and AI can help—and where they cannot
Analytics can help organize records, monitor key performance indicators, and surface patterns that deserve attention. In its 2025 public-procurement report, the OECD describes AI and machine learning uses such as analyzing procurement data for delivery delays, quality issues, and cost deviations, as well as supporting KPI-based and predictive assessment. The OECD makes these uses conditional on having data that is sufficiently high-quality and complete. This is broader public-procurement guidance, not a construction-specific trial proving that AI improves supplier outcomes across the sector. OECD, Digital transformation of public procurement
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Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Digital readiness varies across the industry
Data-led supplier selection depends partly on whether firms have the systems and records to support it. Infrastructure Australia’s 2025 Infrastructure Market Capacity Report says 64% of surveyed building and construction firms had invested in digitalisation in the preceding 12 months, while 26% reported no digitalisation investment. Those figures describe the report’s Australian survey population; they are not global rates or measures of supplier-selection adoption. The report also describes project-by-project, lowest-cost tendering as a current procurement model that can discourage scalable innovation. Infrastructure Australia, 2025 Infrastructure Market Capacity Report
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For a buyer with limited digital capability, a documented evaluation and a usable record of delivery and quality can still make decisions more reviewable. Sophisticated analytics are not a prerequisite for making criteria explicit.
What the historical evidence does—and does not—show
A UK government supply-chain analysis published in 2013 drew on detailed analysis and interviews with contractors and suppliers to identify potential cost savings and barriers in the construction supply chain. It provides historical context about supply-chain challenges, but does not prove that construction has long relied predominantly on intuition to select suppliers. Department for Business, Innovation & Skills, Construction industry: supply chain analysis
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