Purpose The digitalisation of official statistics has accelerated globally, yet limited empirical evidence exists on its operational impact within national statistics offices in developing countries. This study aims to evaluate the transition to digital consumer price index data collection at Statistics South Africa, framing it as a socio-technical transition that enhances operational efficiency and transforms organisational workflows. Design/methodology/approach A pragmatic case study and mixed-methods approach was used. The study integrated semi-structured interviews with a System and Information Quality survey grounded in the updated DeLone and McLean information systems success model. Findings Results demonstrate substantial improvements in timeliness, accuracy and efficiency through “process compression” within the sampled organisational context. While digitalisation eliminated manual re-entry and enhanced oversight, findings reveal heightened individual accountability through stringent system validation and reduced procedural flexibility for field staff. Quantitative results confirmed high user satisfaction, though infrastructure-dependent reliability remained a critical moderator. Research limitations/implications Generalisability is limited by the single-domain focus and head-office sample, which likely underestimates the severity of infrastructural challenges in remote areas. Practical implications The findings offer guidance for national statistics offices pursuing digital transformation, emphasising the need for offline synchronisation, multi-layered device security and role redeployment aligned to new workflows. Social implications This study shows how digitalisation strengthens the reliability and timeliness of official statistics, supporting more effective public policy and service delivery. Originality/value This study provides empirical insight into a developing-country national statistics office. It extends the DeLone and McLean model to official statistics, offering actionable lessons on managing socio-technical trade-offs in mandatory public-sector digital transformations.
Narayan et al. (Wed,) studied this question.