Samenvatting

Road and City Mobility (RCM) is a business unit of Siemens Netherlands. RCM’s core business is to provide infrastructure solutions for its customers. Generally, 80% of RCM’s revenue is generated by projects; the other 20% of the overall revenue is generated by the sales of products (e.g. electronic variable traffic signs). Therefore, it is of great importance that RCM keeps looking for new projects. Projects are normally acquired via European tenders, meaning that competitors all over Europe can enroll for that project. It regularly happens that projects do not turn out to be as planned, this is also applicable for RCM. The management of RCM acknowledged that this is true. However, they know that certain risk might occur for certain projects, but this is somewhat of a gut feeling. The relationship between project class and risks has not been analyzed yet. The aim of this research is, therefore, to prove whether there is a relationship between project class and project risk events. This information will provide the management of RCM with predictions of risks that might occur for certain project classes. Hence, RCM’s management is able make a well thought consideration of even signing the contract, based on the risk events that were predicted for that project.
Thus, the main research question can be formulated as follows: “What relationships can be determined between RCM’s project classifications and risk indicators?” The main research question was supported by four sub research questions: “What are project classifications and why are they applied?” “What are risk indicators and why are they applied?” “How does RCM classify projects?” “What are the relationships between project classification and risk indicators?”
Project classification is the process of grouping projects together in different classes. Different classes of projects have different characteristics. The three main purposes of project categorization are: 1) strategic alignment (assign priority for projects), 2) capability specialization (project delivery capability) and 3) promote project approach (provide a common language for project management).
When we look at how Siemens describes the purposes of its classification framework, we can see that they are very alike. Siemens classifies its projects for four main uses: 1) as a criterion for determining the escalation level, 2) as a criterion for engaging Legal and other experts, 3) for determining the level of detail of minimum requirements for the process, such as documentation requirements and 4) for choosing and assigning project managers to carry out the project, with the required certification level. We can see that Siemens’ purposes 2, 3 and 4 correspond with the literature’s purposes 2 and 3.
Generally, Siemens classifies its project based on a questionnaire. This questionnaire contains fifteen questions in the field of financial, contractual, technical and organizational matters. Based on the answers to each question, a final point is given to that project. A project receives a project class of either A, B, C or S, according to its order volume and points. However, the algorithm that assigns the project class depends very much on order volume. Let X be a small project of a low order volume of EUR 500,000 and the highest points (higher points, means higher risks). Project X will never be a B project even if it has significant identified risks, simply because its order volume is below EUR 10,000,000 (note that A projects have the highest order volumes and S, small, projects have the lowest order volumes). This classification framework did not look that promising for correlating project classes with risks, at first sight. Therefore, a literature based system engineering framework was used for this
J.T.L. de Zwart – Project classes and project risks
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research as well. However, Siemens also implemented a classification of risks for each project, which is divided into: corruption risk and business risk. Both risk assessments can have a score of 1, 2 or 3 (1 meaning high risk and 3 meaning low risk). Siemens uses both assessments for assigning a project with a risk class. The risk class, however, is simply that the higher score leads (corruption risk of 3, business risk of 2, leads to a score of 2). Moreover, the assessments are also questionnaire based, where contractual risks weights the most in the algorithm of assigning a risk score. Therefore, the risk code was not used during this research.
In this research, project types (system engineering classification framework) and LoA class (Siemens classification framework) were studied in terms of risks. Risks are considered to be events that can have negative consequences for project objectives. These risks are, however, unique for each project. But, just as projects, grouping them into risk indicators makes it possible to run statistical tests. Hence, the purpose of risk indicators is that they make statistical analysis possible. Because of this, researchers can make conclusions regarding these risk indicators, leading to increased knowledge of risk events.
Now that project classification and risk indicators have been discussed, we can move to the next part: analysis. Data of 17 projects were gathered and each project controller filled in a questionnaire regarding risk indicators for their project. The questionnaire was Likert scale based with six risk scales (0 risk had no impact, 1, risk had almost no impact, …, 5 risk had significant impact). The risk list contained a total of 38 risks, which were divided into six macro risk indicators: contractual and legal risks, technical risks, quality risks, cost risks, project team and management risks and sub-contractor risks.
Results of the tests (Chi-square tests) had shown that the system engineering classification framework does not distinguish risk for certain project types. Therefore, in this case, this framework is not a sufficient framework when it comes to the relationship between project types and project risk events. The Siemens classification framework does show a difference in terms of occurred risks and the impact of the risks occurred. The results showed that small projects (S projects) face some risks with limited impact. B projects tend to have the most risk impact points (meaning that risks score high points on the Likert scale). Hence, there is a difference in terms of risks occurred and impact of those risks for Siemens’ project classes. Therefore, Siemens’ classification framework is a sufficient tool when it comes to the impact of risks for projects. In addition to that, different projects face different risks. However, many risks are the same for each type of project, but differ in terms of the Likert scale. The tests showed that technical risks dominated the macro risk indicators for all projects, making it an important macro risk indicator. When we zoom in a bit further, we can see that the most significant risks for all project types are: delay in solving technical disputes, tight planning, change order negotiation and unclear design specifications and requirements. However, other risks differ for each project types.
Based on the findings, we can state that there is a relationship between project types and risk indicators. Bigger, more complex projects tend to have more risk events with greater impact on the project than smaller, less complex projects. Thus, using Siemens’ project classes as a way to predict risks can be effective, as the classes differ in terms of risks. However, I would recommend having a closer look at a project’s technical characteristics before signing the contract, as technical risks were the most severe risks in the risk indicator list.