Digitala verktyg för analys av handlingar i anbudsprocesser inom byggsektorn

The construction companies’ continual pursuit of competitive advantages through low-cost strategies combined with the delivery of what the client demands is crucial for the organization’s survival. Since winning bids is decisive for profitability, efficiency in the bidding phase emerges as a critical success factor. The process is characterized by extensive interaction among multiple actors, complex document management, and the need to balance time and resource investments against the bid’s accuracy. In a project based and temporary organizational structure, each new project becomes a fresh start, which contributes to duplicated efforts and lost efficiency if the bid is not won. Digitalization has proven capable of reducing inefficiencies through improved information management, yet in the construction sector manual work processes, inadequate digital infrastructure, and cultural resistance to change persist. To identify how digitalization can streamline the sorting of procurement requirements in documents during bidding procedures, as well as to analyze how the needs of tenderers can be met to reduce time consumption and costs, three research questions guided the work. These encompassed a mapping of current handling of tender documentation and its challenges, an investigation of possible digitalization solutions for the process, and an examination of the requirements that should be imposed on both software and users to ensure a successful digital transition. The study demonstrates that decision-making regarding a bid can take anywhere from a few seconds to several weeks, depending on the project’s complexity and the organization’s structure. By introducing digital tools for document orientation and requirements sorting, such as searchable, indexed databases and AI driven text analysis tools, significant efficiency gains can be achieved. Automated filtering and validation in the early stages enable faster go/no-go decisions and reduce the need for supplementary review rounds. The respondents exhibit an openness to digital solutions but highlight the lack of resources and internal expertise as barriers to technology investments. The analysis underscores that effective digital support requires industry specific adaptations. Semantic text analysis must be trained on the construction sector’s terminology to correctly extract key requirements, while image recognition should be developed to interpret technical drawings and symbols. To enhance user acceptance, intuitive interfaces with natural language interaction and personalized user profiles are essential. Moreover, the importance of robust security to protect corporate and personal data is emphasized. Finally, three main factors for successful implementation are identified: industry adapted semantic text analysis, specialized image recognition, and personalized, conversational interfaces. Together, these components can lower the learning threshold, streamline the bidding process, and free up resources for more qualified tasks.