National scientific research organisation Council for Scientific and Industrial Research (CSIR) has announced that it will once again be part of the South African elections, using its election night prediction model for the 2024 national and provincial elections.

South Africa is heading for a general election in May 29, with some polls suggesting the governing African National Congress (ANC) could get less than 50% of the vote for the first time in 30 years.

CSIR CEO Dr Thulani Dlamini explained that the CSIR's election prediction model relies on the analysis of voter behaviour patterns and the sequence in which voting results are announced on election day.

“…when combined, these two principles enable the team to group voters or voting districts based on their past voting behaviour, utilising a statistical clustering method,” said Dlamini.

He noted that the CSIR’s election prediction model was not a polling system, but rather a model that uses statistical and mathematical analysis to predict election outcomes.

This, he said showcased how statistical clustering and some mathematical algorithms can achieve good predictions from a small sample of results.

The election prediction model operated on the basis of reducing the bias resulting from the ‘non-randomness’ of the incoming results that arise from the order in which the results were received, he added.

Dlamini explained that this model was first introduced by the CSIR during the 1999 general elections, saying the scientific research organisation employed this model to predict the election outcomes at various levels, such as national, provincial and municipal, during the last 10 South African elections.

He noted that when applied in previous elections, the model typically achieved a high degree of accuracy at a national level once about 5% of the results had been tallied.

“…owing to the way the model works, the predictions become more stable and accurate as more voting districts are counted, ultimately converging to the final results once all voting districts have been declared,” he said.

He declared that the organisation possessed robust capabilities in mathematics and statistics, which were applied to deliver precise results and could be customised for various forms of predictive analysis and forecasting.

Dlamini noted that the CSIR’s predictive modelling capabilities allowed for this to be tailor-made for other predictive analysis work, saying the organisation had the capability to assist other countries that may require such a tool to support election transparency and engagement.