The influence of the COVID-19 pandemic is profound and enduring to the entire world. A ‘recovery’ to go back in time is unlikely to happen due to the lack of uncertainty in the future. The darkest time will eventually pass, whereas post-pandemic, the era in which the pandemic is perceived to have subsided, can still accelerate existing trends and bring up new uncertainties, such as hybrid working, activity-based working and smart building, to the office real estate sector. Corporate Real Estate (CRE), as real property, is owned and/or leased by organisations for their business activities. While office real estate is facing profound structural changes, the CRE department of organisations needs to evaluate their office status quo and reimagine their office of the future. Scenario planning can act as a valuable tool to help decision-makers evaluate strategies, and office space demand forecast is one of the important indexes that CRE takes into account. Forecasting office space demand by using scenario planning techniques is recommended when the predictability of the external strategic environment is low and the reliability of the organisation’s internal data required for forecasting is high as is the case in this post-pandemic era. This research aims to propose a scenario planning methodology that can be applied to develop scenarios with quantitative office space demands at a corporate level. Such methodology and detailed scenarios are valuable for CRE decision-makers to evaluate their strategy regarding post-pandemic office real estate. This study is developed by operations research. A proper methodology is proposed through the literature study. A pilot study is then taken to apply this methodology to a real-world example. The chosen pilot is the global headquarter of Philips: Philips Center in Amsterdam. In the pilot study, semi-structured interviews and data analytics of an existing survey are conducted, scenarios are developed by following the steps of the proposed methodology. An expert panel was held to help evaluate the replicability and validities of the findings. Embedded mixed methods research is used for this thesis. Qualitative and quantitative data are both analysed through literature study, semi-structured interviews, and an expert panel. A large chunk of quantitative data analysis including using the programming language approach is conducted during survey data analysis. The findings of this research provide CRE with a methodology to develop scenarios with quantitative office space demand. By applying this methodology, the output of post-pandemic office real estate scenarios with corresponding quantitative office space demand can be used by CRE decision-makers to evaluate their business strategies.