Join us for the next Dataiku Australia and New Zealand User Group event to learn about the Award Winning Machine Learning Use Case!
The global pandemic has accelerated e-commerce growth with more households shopping online than ever before. Whilst Australia Post, a government business enterprise that provides postal services in Australia and is the country’s leading logistics and integrated services business, has a long and proud history to lean on, they continue to face challenges from ever-increasing parcel volumes and a great digital disruption that is shaking up the wider logistics industry.
A key daily activity, at facilities within their logistics network, relates to shift production managers being tasked with making daily resource/staffing planning decisions, that seek to ensure that they process parcel demand in a timely manner, whilst controlling for cost. Currently, these decisions are being made based on limited, but best-available, information. Too few staffing hours can result in sub-optimal throughput and parcel delays, whilst too many staffing hours can unnecessarily increase labor spend. To address this pain point, their Data Science team developed a shift volume forecasting algorithm in Dataiku. The model provides facility operators with daily shift volume forecasts and translates this information into staffing requirements.