Case Study

Forecasting Apprenticeship Numbers with Confidence

Apprentice numbers vary year to year and are often strongly influenced by economic factors, the construction industry job market and the demand for housing in New Zealand. An accurate projection is required to minimise the financial impact from over or under forecasting apprentice numbers and advanced analytical modelling is the key to gaining confidence when forecasting these numbers.


The Building and Construction Industry Training Organisation (BCITO) is the largest provider of construction trade apprenticeships in New Zealand. It is appointed by the Government and tasked with developing and implementing industry qualification for the building and construction sector.

The Challenge

BCITO wanted to gain confidence in forecasting demand for apprentices over the long term so as to proactively position itself to meet the demand for training and reduce potential negative financial impact from over or under forecasting apprentice numbers. In particular, they wanted to build a statistical model to forecast this information over a 3 year period with a good level of accuracy.

The Solution

After working with BCITO subject matter experts, Harmonic applied it’s expertise in advanced analytics to custom build a robust statistical model that provided apprenticeship forecasting over the 3 year period to a high level of confidence.

The model utilised several analytical techniques including time-series, regression, and data visualisation. The model also drew from a range of economic information and incorporates historic trends with industry and econometric forecasts.

Data attributes were also broken down to provide BCITO with a more in-depth understanding of the key attributes and variables that impact apprentice numbers. For example, clear trends, seasonal patterns and important economic attributes were identified.

The Result

  • Improved accuracy in forecasting enabled proactive strategic positioning to meet future demand
  • Improved accuracy in forecasting reduced negative financial impact from over or under forecasting apprentice numbers.
  • Gained insights into key drivers behind apprenticeship numbers.
  • Reduced the chance of negative financial impact caused by inaccurate forecasting
  • Resulting monthly and yearly projections support improved decision making

“We worked with Harmonic to build a model which incorporates historical trends together with industry and econometric forecasts to give us a view of future demand for apprenticeship training. The team at Harmonic displayed considerable expertise in the area for data modelling and forecasting and the resulting report fully met our needs and expectations.”

— Paul Mitchell, Group Manager Support Services, BCITO