(Solution) ROSHN CIPS PIN Risk Profile
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Description
Solution
According to the procurement process model developed by Bailey et al., the Preparation stage lays the groundwork for effective negotiation by categorizing information, coordinating players, and constructing negotiation tactics (Ayantoyinbo et al, 2020). In this case, we apply these principles to ROSHN’s technology spend categories: innovative real estate solutions, communication networks, housing technologies and coordination. This structurally arranged step-by-step procedure facilitates risk profiling processes, team onboarding, agenda setting, negotiation techniques, and location selection decisions for the precise procurement requirements of ROSHN.
Risk Profile
Thus, it is essential to create a risk profile for every technology category to define possible difficulties with suppliers’ reliability, technologies’ incorporation, and market stability. Hence, by identifying risk, ROSHN can turn attention to managing risks and to guaranteeing risk remedy strategies are prepared. It also looks at issues like supplier dependence, technological change, and adherence to best practises in the industry. For example:
Innovative solutions in real estate (e.g., robotics, blockchain): High risk due to the rapid changing environment due to the advancements in technology. These are: Technological Risk and System Integration Risk.
Communication networks (AI, IoT): Moderate risk since these technologies are important to business operations but there are less likely to be many integration problems because of protocols.
Housing solutions (architectural technology): It is of medium risk as it prefers long-term compatibility with solutions and constant support for housing projects.
Project coordination (AI and social media): It has a relatively low risk, but managing projects cannot be optimally done without it.
This risk profile will help ROSHN to focus on specific suppliers and decide how to address risk-related provisions in the contract that are used, for example, to protect data belonging to AI and IoT suppliers.
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