Designing a vendor management procedure for engineering, procurement and construction management projects
Bibliographic record
Abstract
Nowadays, project organisation and communications in engineering projects are evidently complicated due to the participation of many specialists and contractors. The work and materials provided by these vendors in turn account for the majority of project costs. Furthermore, vendors have a significant influence on the success or failure of a project, as their performance directly affects the entire result of the business effort. Thus, to guarantee successful completion of engineering projects, it is of high importance to manage numerous vendors efficiently and effectively, which often becomes a challenge for many organisations. This research investigates vendor management in engineering projects and, using this as a basis, seeks to design a vendor management procedure that would serve as a guideline to handling vendors efficiently. The subject is analysed based on an extensive literature review of renowned authors in the field, as well as from the viewpoint of one of the leading engineering and consulting companies located in Finland. The literature review explores this relatively scarce topic by presenting available ideas sourced from diverse authors, while the empirical part of the research reinforces the findings by qualitative interviews conducted among 11 experienced employees of the case company, who shared the practices applied in their offices based in Finland, Sweden, Germany and Canada. The outcome of the research is a demonstration of theoretical and practical vendor management procedures. The theoretical is built on literature review and is suitable for engineering projects in general, while the practical is more comprehensive and represents practices of the case company to handle vendors in EPCM projects. Both encompass the three main phases: pre-contract, contract execution and post-contract, specifying the key activities, responsible roles and documents required when selecting a vendor, administering the contract execution, as well as closing off the contract and evaluating the results achieved. The scientific importance of this subject is the expansion of the knowledge boundaries in the field by filling the void in existing literature with the results of empirical findings, while the practical importance of the research is the thoroughly developed framework to manage vendors in EPCM projects, which will be formally documented in the case company, evaluated internally and its practical guidelines implemented in due course. Future research ought to be undertaken to investigate vendor management in other project types like EPC and to analyse the key differences between the approaches. In addition, it is suggested to explore KPIs that can be applied to evaluate the success of implemented vendor management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.045 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".