A Model-Based Systems Engineering Framework for B2B Sales Process Optimisation : A Case Study of Sales Process Decomposition and Measures of Effectiveness

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Improving sales processes is essential for business-to-business organisations that seek to decrease sales cycle times, reduce inefficiencies and grow profitability. However, sales processes are often treated as linear workflows, even though they are complex and involve people, technologies and information flows. This thesis develops a model-based systems engineering framework (MBSE) for analysing and optimising sales processes. The objective of the thesis is to examine how systems engineering (SE) and enterprise engineering (EE) principles can be merged to create this framework. The framework adapts the first six processes of SE to a sales context. The empirical section of the study partially applies the framework in a qualitative case study of a company’s transactional sales process. The empirical section focused on identifying the business problem, measures of effectiveness (MoEs) and modelling the current state of the sales process using selected MBSE diagrams. Data was collected through semi-structured stakeholder interviews, internal company documentation and direct observations. Interviews were analysed using thematic analysis, while documentation through content analysis. The current sales process was modelled using a context diagram, a block definition diagram, an internal block diagram and an activity diagram. The findings showed that the inefficiencies identified in the sales process are not isolated operational issues interconnected systemic issues. Unclear ownership, siloed working, approval delays, handover issues, workload bottlenecks, process rigidity and data quality were identified as the main challenges. The study found six MoEs for evaluating the sales process. While the MBSE diagrams made visible the dependencies, information flows, decision points and interfaces that contribute to process complexity. The study concluded that sales process optimisation can benefit from engineering rigor. SE can provide a structured approach to decomposition and analysis of the process, while EE supports alignment with the wider organisation and MBSE enables the visualisation of the process complexity.

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