Continuous measurement and monitoring of project performance is essential for objective goal assessment, early detection of errors and providing timely feedback relevant for successful project management. Traditional project management approaches that are used in the development of technical systems are based on tangible indicators for project performance measurement. However, for the effective project management there is a necessity to embrace the socio-technical perspective – working processes and organizational environment. Sociotechnical perspective can be measured by using operational indicators with an emphasis on behavior, knowledge exchange and ideation aspects. Analysis of interactions between individuals in hierarchical organization structures is a prerequisite for better understanding, monitoring and measuring project performance dynamics. Modeling of dynamics of operational indicators for competencies, innovativeness, communication and motivation on individual and team level, enables proactive management of technical systems development projects and identification of operational risks related to those indicators. Based on literature review and initial empirical studies, the list and network of intangible indicators were proposed. Indicators were grouped into four elements of intellectual capital on individual and team level: Competences and knowledge, Communication and information exchange, Innovativeness and ideation, and Motivation and satisfaction. The proposed list of indicators was used as a starting point for creating a survey, development of work sampling application and integration with IT systems for data gathering that allows monitoring of the performance of individuals and teams in real time. Work sampling has not been used in this context before and allows the quantitative and more objective data collection on activities within the technical systems development at the individual and team level. In addition, aggregation model was defined which allows calculation of aggregated values for each element of intellectual capital. Values for each intellectual capital element were calculated by using the weighting factors obtained with the Potential method and by applying the differential linear weighted aggregation. A case study was carried out in the R&D company whose research and development activities are focused on the development of systems for production, distribution and transformation of electrical energy. After case study had been conducted, analysis of the indicators enabled detailed insight into the performance of activities during the development of embedded control systems and validation of the proposed method. The validation process of the proposed method was divided into two parts: 1. Validation of the feasibility and usefulness of the method, and 2. Validation of results. Validation of the feasibility and usefulness of the method included a comparison with existing literature, the use of case study and discussion about the method usage in a broader context. The first part of the validation confirmed that the individual indicators were set correctly and that the proposed method fulfills its intended purpose in terms of internal consistency and external relevance. For the purposes of validating the results of intangible indicators, comparison was used with the results of the organizational risk analysis method. The second part of the validation confirmed the results of the indicators trends and complementary nature of the proposed method to methods for organisational risk assessment.
2015
PhD thesis
