Published on 10/12/2024
National Resistance Movement (NRM) is digitizing its membership register to enhance mobilization and ensure transparency in internal elections.
According to Hon. Rosemary Nansubuga Sseninde, Director of Mobilization and Cadre Identification at the NRM Secretariat, the move will streamline party operations and foster better engagement with members. This initiative aims to modernize the party’s approach to organization, creating a robust platform for communication. By leveraging technology, NRM seeks to strengthen its grassroots networks and empower its members.
“This exercise has created a mobilization opportunity,” Hon. Sseninde explained, highlighting that young people involved in the data entry and verification are being empowered and naturally positioned as future party supporters and mobilizers.
“By engaging the youth, the initiative not only provides them with income but also integrates them into the NRM’s long-term vision.”
The absence of a proper register in previous elections created significant challenges, including disputes during primaries.
According to Sseninde, who is also the team leader for the party digitization in Greater Mpigi, Wakiso and Kampala, the digital register aims to address previous challenges by ensuring a clean and accurate database that supports both mobilization and transparent elections.
During a media briefing on Monday, Sseninde shared impressive progress from the digitalization centres. The register is already facilitating targeted mobilization efforts.
Butambala and Gomba districts have achieved 100% data coverage, while Mpigi is at 81%, Wakiso at 76%, and Kampala at 54%.
Viola Asiimwe, one of the supervisors at the digitalization centre in Kira Municipality, says data entry is way up because the clerks learned the new system quickly, and the verification team is doing a fantastic job.
In Kampala, the NRM digitalization project is almost finished. IT Supervisor Adler Nishkeka says they overcame early network problems. They have strong checks in place – people checking the data, and the system itself catching mistakes like duplicate entries or wrong birth dates, genders, and IDs.
