A Post-Disaster Needs Assessment (PDNA) is an important exercise for the rehabilitation of disaster-affected people to help them rebuild their lives from the ground up. It prioritises collecting data, analysing it for correct assessment of disaster impacts on monsoon rainfall patterns and worsening landslides cascading down from the mountains; deciding rehabilitation priorities; and determining the quantum of expenditures. Assam's flood dynamics have drastically changed due to climate-change-driven impacts on monsoon rainfall patterns and worsening landslides cascading down from the hills of neighbouring states. Flexible, adaptable PDNA templates can help capture the real post-disaster needs of an affected village or town, unlike standardised formats for the entire state or country. Enlarging the list of items included in damage assessment remains important to ensure that the post-disaster needs of a particular village or area are addressed comprehensively and that no affected households are deprived of proportionate compensation due to the exclusion of certain damaged properties. The central and state governments and local administration need a comprehensive assessment for deciding the quantum of financial assistance and prioritising rehabilitation projects, fixing the compensation amount based on the availability of funds and the framework of disaster management. The PDNA tools developed by the National Institute of Disaster Management (NIDM) seek to establish a standardised mechanism for conducting assessments of post-disaster needs for long-term recovery and reconstruction. The standard operating procedures of PDNA, developed by NIDM, rightly highlight the critical gap in relief-centred recovery and reconstruction needs assessments. It points out that the existing system efficiently defines relief assistance amounts for the affected population according to predefined criteria and enables the prompt disbursement of this assistance. However, it fails to comprehensively estimate overall disaster impacts, scientifically estimate recovery and reconstruction needs, or calculate the financial requirements for these purposes. Training officials, employees, and professionals involved in rehabilitation exercises is crucial for Assam to build its capacity to conduct scientific PDNAs that accurately capture the damage impact across various sectors of the economy, including households with different income levels, the private sector, and local industrial units. In addition to material loss, the trauma of losing the sole breadwinner, anxiety over livelihood loss, loss of livestock, concerns about the continuation of children's education, and healthcare needs trigger serious mental health issues for many individuals. More focus on reconstruction priorities such as repair of damaged roads, bridges, and embankments often overshadows this important PDNA component. This situation requires equal priority for addressing the mental stress and mental health conditions of affected individuals, helping them overcome trauma and anxiety, and ensuring that the mental health needs of households do not remain overlooked amidst the overwhelming damage statistics. Another gap identified by the NIDM while developing the SOP is that the amounts of response assistance provided are clearly insufficient for affected families to rebuild their destroyed assets; without other sources of capital for reconstruction, people resort to rebuilding their homes and other assets using lower quality standards and inadequate construction materials, which increases disaster risk rather than reducing it. Compromising on construction quality during the repair and reconstruction of houses due to insufficient rehabilitation assistance increases the vulnerability of these homes to damage from subsequent floods, which is a serious concern; therefore, addressing this critical gap is essential for enhancing resilience against worsening and recurring annual flood waves in the state. Pooling resources under various government schemes and projects to increase availability of rehabilitation assistance to affected individual households needs meticulous estimation. The application of artificial intelligence needs to be explored to improve such estimation based on scientific PDNA conducted by disaster management authorities. Building awareness among flood-hit people about the importance of PDNA and the current status of its application and adaptation is essential to increase transparency in rehabilitation measures and boost confidence among them about getting maximum possible government support for rebuilding their lives. While post-disaster relief and rehabilitation remain crucial interventions by the government to increase flood resilience, the pragmatic approach must be to strengthen disaster risk reduction through both structural and non-structural measures. Flood management in Assam must prioritise structural measures, such as strengthening embankments, roads, bridges, culverts, and drainage channels, as well as constructing flood shelters, which continue to receive adequate funding support from the central government. Ironically, non-structural measures such as community preparedness, basin-level coordination, floodplain zoning, and early warning systems, which involve fewer expenditures but require putting in place improved mechanisms, continue to receive less priority even though these measures play an equally important role in disaster risk reduction and prevent loss of lives. Effective disaster risk reduction prevents annual and recurring disasters from turning into full-blown crises, and it also brings down the expenditures in post-disaster rehabilitation. Nevertheless, conducting PDNA is central to improving rehabilitation, guiding recovery planning, and undertaking interventions aligned with the real needs of flood-affected people.